2025-08-26T19:42:37.6313519Z Current runner version: '2.328.0' 2025-08-26T19:42:37.6319784Z Runner name: 'i-04da9546f7741a2d4' 2025-08-26T19:42:37.6320691Z Runner group name: 'Default' 2025-08-26T19:42:37.6321595Z Machine name: 'ip-10-0-28-8' 2025-08-26T19:42:37.6324611Z ##[group]GITHUB_TOKEN Permissions 2025-08-26T19:42:37.6326942Z Contents: read 2025-08-26T19:42:37.6327505Z Metadata: read 2025-08-26T19:42:37.6328101Z ##[endgroup] 2025-08-26T19:42:37.6330459Z Secret source: Actions 2025-08-26T19:42:37.6331316Z Prepare workflow directory 2025-08-26T19:42:37.6854281Z Prepare all required actions 2025-08-26T19:42:37.6895904Z Getting action download info 2025-08-26T19:42:37.9829654Z Download action repository 'pytorch/test-infra@main' (SHA:0192d56cb596bb73b125bd368553908cc5c513f0) 2025-08-26T19:42:39.8646157Z Download action repository 'pytorch/pytorch@main' (SHA:77bc959fe122bfd131e339ca36cab445a1860806) 2025-08-26T19:42:53.3181485Z Download action repository 'actions/setup-python@a26af69be951a213d495a4c3e4e4022e16d87065' (SHA:a26af69be951a213d495a4c3e4e4022e16d87065) 2025-08-26T19:42:53.6408309Z Download action repository 'aws-actions/configure-aws-credentials@ececac1a45f3b08a01d2dd070d28d111c5fe6722' (SHA:ececac1a45f3b08a01d2dd070d28d111c5fe6722) 2025-08-26T19:42:53.8971992Z Download action repository 'aws-actions/amazon-ecr-login@062b18b96a7aff071d4dc91bc00c4c1a7945b076' (SHA:062b18b96a7aff071d4dc91bc00c4c1a7945b076) 2025-08-26T19:42:54.1064760Z Download action repository 'seemethere/upload-artifact-s3@baba72d0712b404f646cebe0730933554ebce96a' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-08-26T19:42:54.4323788Z Getting action download info 2025-08-26T19:42:54.5576150Z Download action repository 'actions/checkout@v4' (SHA:08eba0b27e820071cde6df949e0beb9ba4906955) 2025-08-26T19:42:54.8578741Z Getting action download info 2025-08-26T19:42:54.9541119Z Download action repository 'nick-fields/retry@v3.0.0' (SHA:7152eba30c6575329ac0576536151aca5a72780e) 2025-08-26T19:42:55.1471061Z Getting action download info 2025-08-26T19:42:55.2586444Z Download action repository 'nick-fields/retry@3e91a01664abd3c5cd539100d10d33b9c5b68482' (SHA:3e91a01664abd3c5cd539100d10d33b9c5b68482) 2025-08-26T19:42:55.4512290Z Getting action download info 2025-08-26T19:42:55.6074726Z Uses: pytorch/pytorch/.github/workflows/_linux-test.yml@refs/heads/main (262640fd220236042fbf4443cc163c8838c84c3d) 2025-08-26T19:42:55.6078806Z ##[group] Inputs 2025-08-26T19:42:55.6079193Z build-environment: linux-jammy-py3.13-clang12 2025-08-26T19:42:55.6082336Z test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]} 2025-08-26T19:42:55.6085852Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:42:55.6086678Z sync-tag: 2025-08-26T19:42:55.6087488Z timeout-minutes: 240 2025-08-26T19:42:55.6087770Z use-gha: 2025-08-26T19:42:55.6087998Z dashboard-tag: 2025-08-26T19:42:55.6088260Z s3-bucket: gha-artifacts 2025-08-26T19:42:55.6088543Z aws-role-to-assume: 2025-08-26T19:42:55.6089124Z disable-monitor: false 2025-08-26T19:42:55.6089775Z monitor-log-interval: 5 2025-08-26T19:42:55.6090213Z monitor-data-collect-interval: 1 2025-08-26T19:42:55.6090556Z ##[endgroup] 2025-08-26T19:42:55.6090985Z Complete job name: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:42:55.6608366Z A job started hook has been configured by the self-hosted runner administrator 2025-08-26T19:42:55.6713449Z ##[group]Run '/home/ec2-user/runner-scripts/before_job.sh' 2025-08-26T19:42:55.6722268Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:42:55.6722926Z ##[endgroup] 2025-08-26T19:42:56.9069853Z Runner Type: lf.linux.4xlarge 2025-08-26T19:42:56.9070363Z Instance Type: c5.4xlarge 2025-08-26T19:42:56.9070646Z AMI Name: unknown 2025-08-26T19:42:56.9098345Z AMI ID: ami-05ffe3c48a9991133 2025-08-26T19:43:02.3068893Z ##[group]Run pytorch/test-infra/.github/actions/setup-ssh@main 2025-08-26T19:43:02.3069388Z with: 2025-08-26T19:43:02.3070002Z github-secret: *** 2025-08-26T19:43:02.3070780Z instructions: All testing is done inside the container, to start an interactive session run: docker exec -it $(docker container ps --format '{{.ID}}') bash 2025-08-26T19:43:02.3071632Z activate-with-label: false 2025-08-26T19:43:02.3071921Z label: with-ssh 2025-08-26T19:43:02.3072193Z remove-existing-keys: true 2025-08-26T19:43:02.3072496Z fail-silently: true 2025-08-26T19:43:02.3072766Z env: 2025-08-26T19:43:02.3073017Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:43:02.3073306Z ##[endgroup] 2025-08-26T19:43:02.4254719Z Please see https://github.com/pytorch/pytorch/wiki/Debugging-using-with-ssh-for-Github-Actions for more info. 2025-08-26T19:43:02.4256181Z Not on pull request and ciflow reference could not be extracted, skipping adding ssh keys 2025-08-26T19:43:02.4404231Z ##[group]Run pytorch/pytorch/.github/actions/checkout-pytorch@main 2025-08-26T19:43:02.4404704Z with: 2025-08-26T19:43:02.4404927Z no-sudo: true 2025-08-26T19:43:02.4405185Z submodules: recursive 2025-08-26T19:43:02.4405471Z fetch-depth: 0 2025-08-26T19:43:02.4405708Z env: 2025-08-26T19:43:02.4405953Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:43:02.4406245Z ##[endgroup] 2025-08-26T19:43:02.4492741Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T19:43:02.4493775Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T19:43:02.4502519Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:43:02.4502931Z env: 2025-08-26T19:43:02.4503185Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:43:02.4503514Z ##[endgroup] 2025-08-26T19:43:02.4593846Z ##[group]Run # Use all available CPUs for fetching 2025-08-26T19:43:02.4594320Z # Use all available CPUs for fetching 2025-08-26T19:43:02.4594691Z cd "${GITHUB_WORKSPACE}" 2025-08-26T19:43:02.4595043Z git config --global fetch.parallel 0 2025-08-26T19:43:02.4595461Z git config --global submodule.fetchJobs 0 2025-08-26T19:43:02.4595841Z  2025-08-26T19:43:02.4596227Z # Clean workspace. The default checkout action should also do this, but 2025-08-26T19:43:02.4596723Z # do it here as well just in case 2025-08-26T19:43:02.4597069Z if [[ -d .git ]]; then 2025-08-26T19:43:02.4597387Z  if [ -z "${NO_SUDO}" ]; then 2025-08-26T19:43:02.4597723Z  sudo git clean -ffdx 2025-08-26T19:43:02.4598015Z  else 2025-08-26T19:43:02.4598271Z  git clean -ffdx 2025-08-26T19:43:02.4598555Z  fi 2025-08-26T19:43:02.4598786Z fi 2025-08-26T19:43:02.4604199Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:43:02.4604607Z env: 2025-08-26T19:43:02.4604919Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:43:02.4605231Z NO_SUDO: true 2025-08-26T19:43:02.4605474Z ##[endgroup] 2025-08-26T19:43:02.4755611Z ##[group]Run actions/checkout@v4 2025-08-26T19:43:02.4755934Z with: 2025-08-26T19:43:02.4756198Z ref: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:43:02.4756732Z fetch-depth: 0 2025-08-26T19:43:02.4756979Z submodules: recursive 2025-08-26T19:43:02.4757260Z show-progress: false 2025-08-26T19:43:02.4757550Z repository: pytorch/pytorch 2025-08-26T19:43:02.4758016Z token: *** 2025-08-26T19:43:02.4758261Z ssh-strict: true 2025-08-26T19:43:02.4758504Z ssh-user: git 2025-08-26T19:43:02.4758770Z persist-credentials: true 2025-08-26T19:43:02.4759065Z clean: true 2025-08-26T19:43:02.4759327Z sparse-checkout-cone-mode: true 2025-08-26T19:43:02.4759648Z fetch-tags: false 2025-08-26T19:43:02.4759897Z lfs: false 2025-08-26T19:43:02.4760150Z set-safe-directory: true 2025-08-26T19:43:02.4760436Z env: 2025-08-26T19:43:02.4760664Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:43:02.4760941Z ##[endgroup] 2025-08-26T19:43:02.5867066Z Syncing repository: pytorch/pytorch 2025-08-26T19:43:02.5868476Z ##[group]Getting Git version info 2025-08-26T19:43:02.5868993Z Working directory is '/home/ec2-user/actions-runner/_work/pytorch/pytorch' 2025-08-26T19:43:02.5869727Z [command]/usr/bin/git version 2025-08-26T19:43:02.5870034Z git version 2.47.1 2025-08-26T19:43:02.5879044Z ##[endgroup] 2025-08-26T19:43:02.5887905Z Copying '/home/ec2-user/.gitconfig' to '/home/ec2-user/actions-runner/_work/_temp/e58dc1d9-a024-4c16-bbb7-fb5d9b40a01f/.gitconfig' 2025-08-26T19:43:02.5906481Z Temporarily overriding HOME='/home/ec2-user/actions-runner/_work/_temp/e58dc1d9-a024-4c16-bbb7-fb5d9b40a01f' before making global git config changes 2025-08-26T19:43:02.5907545Z Adding repository directory to the temporary git global config as a safe directory 2025-08-26T19:43:02.5911410Z [command]/usr/bin/git config --global --add safe.directory /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-08-26T19:43:02.5950071Z Deleting the contents of '/home/ec2-user/actions-runner/_work/pytorch/pytorch' 2025-08-26T19:43:02.5952994Z ##[group]Initializing the repository 2025-08-26T19:43:02.5957560Z [command]/usr/bin/git init /home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-08-26T19:43:02.5986665Z hint: Using 'master' as the name for the initial branch. This default branch name 2025-08-26T19:43:02.5987316Z hint: is subject to change. To configure the initial branch name to use in all 2025-08-26T19:43:02.5987935Z hint: of your new repositories, which will suppress this warning, call: 2025-08-26T19:43:02.5988390Z hint: 2025-08-26T19:43:02.5988705Z hint: git config --global init.defaultBranch 2025-08-26T19:43:02.5989064Z hint: 2025-08-26T19:43:02.5989418Z hint: Names commonly chosen instead of 'master' are 'main', 'trunk' and 2025-08-26T19:43:02.5990040Z hint: 'development'. The just-created branch can be renamed via this command: 2025-08-26T19:43:02.5990534Z hint: 2025-08-26T19:43:02.5990759Z hint: git branch -m 2025-08-26T19:43:02.5991296Z Initialized empty Git repository in /home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/ 2025-08-26T19:43:02.5995840Z [command]/usr/bin/git remote add origin https://github.com/pytorch/pytorch 2025-08-26T19:43:02.6019658Z ##[endgroup] 2025-08-26T19:43:02.6020120Z ##[group]Disabling automatic garbage collection 2025-08-26T19:43:02.6023415Z [command]/usr/bin/git config --local gc.auto 0 2025-08-26T19:43:02.6046314Z ##[endgroup] 2025-08-26T19:43:02.6046736Z ##[group]Setting up auth 2025-08-26T19:43:02.6052670Z [command]/usr/bin/git config --local --name-only --get-regexp core\.sshCommand 2025-08-26T19:43:02.6077117Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'core\.sshCommand' && git config --local --unset-all 'core.sshCommand' || :" 2025-08-26T19:43:02.6348291Z [command]/usr/bin/git config --local --name-only --get-regexp http\.https\:\/\/github\.com\/\.extraheader 2025-08-26T19:43:02.6371271Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local --name-only --get-regexp 'http\.https\:\/\/github\.com\/\.extraheader' && git config --local --unset-all 'http.https://github.com/.extraheader' || :" 2025-08-26T19:43:02.6622994Z [command]/usr/bin/git config --local http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-08-26T19:43:02.6663803Z ##[endgroup] 2025-08-26T19:43:02.6664290Z ##[group]Fetching the repository 2025-08-26T19:43:02.6671493Z [command]/usr/bin/git -c protocol.version=2 fetch --prune --no-recurse-submodules origin +refs/heads/*:refs/remotes/origin/* +refs/tags/*:refs/tags/* 2025-08-26T19:43:47.7137740Z From https://github.com/pytorch/pytorch 2025-08-26T19:43:47.7138540Z * [new branch] 160583 -> origin/160583 2025-08-26T19:43:47.7139175Z * [new branch] 2.6.0.dev20241004+ -> origin/2.6.0.dev20241004+ 2025-08-26T19:43:47.7139751Z * [new branch] 5addvllmbuild -> origin/5addvllmbuild 2025-08-26T19:43:47.7140408Z * [new branch] AaronWang04_addmmfusion_perftest -> origin/AaronWang04_addmmfusion_perftest 2025-08-26T19:43:47.7141149Z * [new branch] HDCharles-2.6.0-release-notes -> origin/HDCharles-2.6.0-release-notes 2025-08-26T19:43:47.7142555Z * [new branch] ISSUE-154849 -> origin/ISSUE-154849 2025-08-26T19:43:47.7144605Z * [new branch] JackCaoG/dynamo_make_fx_non_core_aten_ops -> origin/JackCaoG/dynamo_make_fx_non_core_aten_ops 2025-08-26T19:43:47.7146521Z * [new branch] PR-AOTInductorNoneBug -> origin/PR-AOTInductorNoneBug 2025-08-26T19:43:47.7148390Z * [new branch] PR-AOTInductorNoneBugFix -> origin/PR-AOTInductorNoneBugFix 2025-08-26T19:43:47.7149910Z * [new branch] PR-FixConfigsIssue -> origin/PR-FixConfigsIssue 2025-08-26T19:43:47.7151628Z * [new branch] PR-NoneBugFix-viable -> origin/PR-NoneBugFix-viable 2025-08-26T19:43:47.7152973Z * [new branch] PR-ResetToZero -> origin/PR-ResetToZero 2025-08-26T19:43:47.7154675Z * [new branch] Update-Flash-Packaging -> origin/Update-Flash-Packaging 2025-08-26T19:43:47.7156656Z * [new branch] VLA_exp -> origin/VLA_exp 2025-08-26T19:43:47.7158626Z * [new branch] add-missing-args-normalization -> origin/add-missing-args-normalization 2025-08-26T19:43:47.7160397Z * [new branch] add-user-guide-structure -> origin/add-user-guide-structure 2025-08-26T19:43:47.7161828Z * [new branch] addVllmPin -> origin/addVllmPin 2025-08-26T19:43:47.7163502Z * [new branch] add_compile_benchmarking -> origin/add_compile_benchmarking 2025-08-26T19:43:47.7165049Z * [new branch] add_windows_testing_back -> origin/add_windows_testing_back 2025-08-26T19:43:47.7166840Z * [new branch] addbuildvllm -> origin/addbuildvllm 2025-08-26T19:43:47.7168492Z * [new branch] addmm-heuristic -> origin/addmm-heuristic 2025-08-26T19:43:47.7170150Z * [new branch] addsimde -> origin/addsimde 2025-08-26T19:43:47.7172729Z * [new branch] adi/acl_upgrade -> origin/adi/acl_upgrade 2025-08-26T19:43:47.7173951Z * [new branch] adi/test -> origin/adi/test 2025-08-26T19:43:47.7175553Z * [new branch] adi/test_bgemm -> origin/adi/test_bgemm 2025-08-26T19:43:47.7177317Z * [new branch] adi/test_fusions -> origin/adi/test_fusions 2025-08-26T19:43:47.7178925Z * [new branch] adi/test_onednn_v3.9 -> origin/adi/test_onednn_v3.9 2025-08-26T19:43:47.7181245Z * [new branch] adi/test_presve_change -> origin/adi/test_presve_change 2025-08-26T19:43:47.7182364Z * [new branch] adi/test_timm -> origin/adi/test_timm 2025-08-26T19:43:47.7183752Z * [new branch] adi/testpresve_change -> origin/adi/testpresve_change 2025-08-26T19:43:47.7185913Z * [new branch] aditew01/test/vec_bf16 -> origin/aditew01/test/vec_bf16 2025-08-26T19:43:47.7187296Z * [new branch] ah-globalfeedback-hook -> origin/ah-globalfeedback-hook 2025-08-26T19:43:47.7188499Z * [new branch] alt-disable -> origin/alt-disable 2025-08-26T19:43:47.7190541Z * [new branch] angelayi/aoti_additional_files -> origin/angelayi/aoti_additional_files 2025-08-26T19:43:47.7191686Z * [new branch] angelayi/aoti_inductor_fx -> origin/angelayi/aoti_inductor_fx 2025-08-26T19:43:47.7193233Z * [new branch] angelayi/assert_tensor_metadata_device -> origin/angelayi/assert_tensor_metadata_device 2025-08-26T19:43:47.7194292Z * [new branch] angelayi/benchmark -> origin/angelayi/benchmark 2025-08-26T19:43:47.7195946Z * [new branch] angelayi/benchmark2 -> origin/angelayi/benchmark2 2025-08-26T19:43:47.7197610Z * [new branch] angelayi/change_pytree_serialization -> origin/angelayi/change_pytree_serialization 2025-08-26T19:43:47.7199157Z * [new branch] angelayi/cpp_loader -> origin/angelayi/cpp_loader 2025-08-26T19:43:47.7200908Z * [new branch] angelayi/custom_op_subgraph -> origin/angelayi/custom_op_subgraph 2025-08-26T19:43:47.7202237Z * [new branch] angelayi/customop -> origin/angelayi/customop 2025-08-26T19:43:47.7203791Z * [new branch] angelayi/is_symbolic_tracing -> origin/angelayi/is_symbolic_tracing 2025-08-26T19:43:47.7205182Z * [new branch] angelayi/logging.bak -> origin/angelayi/logging.bak 2025-08-26T19:43:47.7206534Z * [new branch] angelayi/logging2 -> origin/angelayi/logging2 2025-08-26T19:43:47.7208034Z * [new branch] angelayi/no_so_weight -> origin/angelayi/no_so_weight 2025-08-26T19:43:47.7209447Z * [new branch] angelayi/opoverload -> origin/angelayi/opoverload 2025-08-26T19:43:47.7210803Z * [new branch] angelayi/pytree -> origin/angelayi/pytree 2025-08-26T19:43:47.7212210Z * [new branch] angelayi/save_error -> origin/angelayi/save_error 2025-08-26T19:43:47.7213598Z * [new branch] angelayi/scan_layers -> origin/angelayi/scan_layers 2025-08-26T19:43:47.7214954Z * [new branch] angelayi/symint_input -> origin/angelayi/symint_input 2025-08-26T19:43:47.7216396Z * [new branch] angelayi/tensor_nn_module_meta -> origin/angelayi/tensor_nn_module_meta 2025-08-26T19:43:47.7217683Z * [new branch] angelayi/test_cpp -> origin/angelayi/test_cpp 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2025-08-26T19:43:48.2918509Z * [new branch] xmfan/disable_duck_shape -> origin/xmfan/disable_duck_shape 2025-08-26T19:43:48.2919656Z * [new branch] xmfan/fca_cpp_node_passthrough -> origin/xmfan/fca_cpp_node_passthrough 2025-08-26T19:43:48.2920463Z * [new branch] xmfan/issue_123374 -> origin/xmfan/issue_123374 2025-08-26T19:43:48.2921843Z * [new branch] xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/post_3945954741e2d37023c5d6954f9483008e0892f9 2025-08-26T19:43:48.2922767Z * [new branch] xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 -> origin/xmfan/pre_3945954741e2d37023c5d6954f9483008e0892f9 2025-08-26T19:43:48.2923547Z * [new branch] xmfan/segfault_test -> origin/xmfan/segfault_test 2025-08-26T19:43:48.2924582Z * [new branch] xmfan/single_step -> origin/xmfan/single_step 2025-08-26T19:43:48.2925561Z * [new branch] xmfan/sth_0829 -> origin/xmfan/sth_0829 2025-08-26T19:43:48.2926631Z * [new branch] xmfan/test -> origin/xmfan/test 2025-08-26T19:43:48.2928079Z * [new branch] yguo/debug-0226-constexpr -> origin/yguo/debug-0226-constexpr 2025-08-26T19:43:48.2929127Z * [new branch] yguo/new_latest_changes -> origin/yguo/new_latest_changes 2025-08-26T19:43:48.2930289Z * [new branch] yguo/patch_constexpr_changes -> origin/yguo/patch_constexpr_changes 2025-08-26T19:43:48.2931364Z * [new branch] yihan_quantization -> origin/yihan_quantization 2025-08-26T19:43:48.2932799Z * [new branch] yiming/add_jit_trace_benchmark -> origin/yiming/add_jit_trace_benchmark 2025-08-26T19:43:48.2933690Z * [new branch] yiming/add_nativert_benchmark -> origin/yiming/add_nativert_benchmark 2025-08-26T19:43:48.2934657Z * [new branch] yiming/bootcamp -> origin/yiming/bootcamp 2025-08-26T19:43:48.2935999Z * [new branch] zainr/canary-test -> origin/zainr/canary-test 2025-08-26T19:43:48.2937111Z * [new branch] zainr/cleanup-gh-runners -> origin/zainr/cleanup-gh-runners 2025-08-26T19:43:48.2938219Z * [new branch] zainr/git-push-v2 -> origin/zainr/git-push-v2 2025-08-26T19:43:48.2939180Z * [new branch] zainr/pull-migration-c -> origin/zainr/pull-migration-c 2025-08-26T19:43:48.2939959Z * [new branch] zainr/test2 -> origin/zainr/test2 2025-08-26T19:43:48.2941080Z * [new branch] zainr/unstable -> origin/zainr/unstable 2025-08-26T19:43:48.2941855Z * [new branch] zainr/unstable-xla -> origin/zainr/unstable-xla 2025-08-26T19:43:48.2942883Z * [new branch] zainr/uv-pip-fix -> origin/zainr/uv-pip-fix 2025-08-26T19:43:48.2944162Z * [new branch] zainr/vs-aarch64 -> origin/zainr/vs-aarch64 2025-08-26T19:43:48.2945503Z * [new branch] zasdfgbnm-patch-3 -> origin/zasdfgbnm-patch-3 2025-08-26T19:43:48.2946632Z * [new branch] zb2p -> origin/zb2p 2025-08-26T19:43:48.2947917Z * [new branch] zdevito-patch-1 -> origin/zdevito-patch-1 2025-08-26T19:43:48.2949027Z * [new branch] zero_grad_optimization -> origin/zero_grad_optimization 2025-08-26T19:43:48.2950107Z * [new branch] zeros-and-scatter-part2 -> origin/zeros-and-scatter-part2 2025-08-26T19:43:48.2951707Z * [new branch] zhxchen17/scratch/0 -> origin/zhxchen17/scratch/0 2025-08-26T19:43:48.2953174Z * [new branch] zhxhcen17/moodycamel -> origin/zhxhcen17/moodycamel 2025-08-26T19:43:48.2954592Z * [new branch] zxiiro/main -> origin/zxiiro/main 2025-08-26T19:43:48.2955596Z * [new branch] zxiiro/test -> origin/zxiiro/test 2025-08-26T19:43:48.2956821Z * [new tag] bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug -> bc2caa7fdf006894eff7af936babde69ab5a40f8-huydhn-debug 2025-08-26T19:43:48.2957415Z * [new tag] ci/binaries/77164 -> ci/binaries/77164 2025-08-26T19:43:48.2958576Z * [new tag] ciflow/binaries/153920 -> ciflow/binaries/153920 2025-08-26T19:43:48.2959438Z * [new tag] ciflow/binaries/158104 -> ciflow/binaries/158104 2025-08-26T19:43:48.2959960Z * [new tag] ciflow/binaries/160229 -> ciflow/binaries/160229 2025-08-26T19:43:48.2960688Z * [new tag] ciflow/binaries/160853 -> ciflow/binaries/160853 2025-08-26T19:43:48.2961371Z * [new tag] ciflow/binaries/161257 -> ciflow/binaries/161257 2025-08-26T19:43:48.2962220Z * [new tag] ciflow/binaries_libtorch/156049 -> ciflow/binaries_libtorch/156049 2025-08-26T19:43:48.2962945Z * [new tag] ciflow/binaries_wheel/156049 -> ciflow/binaries_wheel/156049 2025-08-26T19:43:48.2963704Z * [new tag] ciflow/binaries_wheel/158733 -> ciflow/binaries_wheel/158733 2025-08-26T19:43:48.2964686Z * [new tag] ciflow/binaries_wheel/160207 -> ciflow/binaries_wheel/160207 2025-08-26T19:43:48.2965458Z * [new tag] ciflow/h100-symm-mem/151845 -> ciflow/h100-symm-mem/151845 2025-08-26T19:43:48.2966096Z * [new tag] ciflow/h100-symm-mem/155923 -> ciflow/h100-symm-mem/155923 2025-08-26T19:43:48.2966745Z * [new tag] ciflow/h100-symm-mem/157635 -> ciflow/h100-symm-mem/157635 2025-08-26T19:43:48.2967704Z * [new tag] ciflow/h100-symm-mem/159562 -> ciflow/h100-symm-mem/159562 2025-08-26T19:43:48.2968172Z * [new tag] ciflow/h100-symm-mem/159889 -> ciflow/h100-symm-mem/159889 2025-08-26T19:43:48.2968923Z * [new tag] ciflow/h100-symm-mem/160825 -> ciflow/h100-symm-mem/160825 2025-08-26T19:43:48.2969598Z * [new tag] ciflow/h100-symm-mem/161008 -> ciflow/h100-symm-mem/161008 2025-08-26T19:43:48.2970269Z * [new tag] ciflow/h100-symm-mem/161090 -> ciflow/h100-symm-mem/161090 2025-08-26T19:43:48.2970900Z * [new tag] ciflow/h100-symm-mem/161214 -> ciflow/h100-symm-mem/161214 2025-08-26T19:43:48.2971561Z * [new tag] ciflow/h100-symm-mem/161217 -> ciflow/h100-symm-mem/161217 2025-08-26T19:43:48.2972215Z * [new tag] ciflow/h100-symm-mem/161232 -> ciflow/h100-symm-mem/161232 2025-08-26T19:43:48.2973379Z * [new tag] ciflow/h100-symm-mem/161257 -> ciflow/h100-symm-mem/161257 2025-08-26T19:43:48.2974122Z * [new tag] ciflow/h100-symm-mem/161309 -> ciflow/h100-symm-mem/161309 2025-08-26T19:43:48.2975023Z * [new tag] ciflow/h100-symm-mem/161470 -> ciflow/h100-symm-mem/161470 2025-08-26T19:43:48.2975585Z * [new tag] ciflow/h100-symm-mem/161471 -> ciflow/h100-symm-mem/161471 2025-08-26T19:43:48.2976304Z * [new tag] ciflow/h100-symm-mem/161532 -> ciflow/h100-symm-mem/161532 2025-08-26T19:43:48.2977485Z * [new tag] ciflow/h100-symm-mem/161533 -> ciflow/h100-symm-mem/161533 2025-08-26T19:43:48.2978568Z * [new tag] ciflow/h100/159158 -> ciflow/h100/159158 2025-08-26T19:43:48.2979174Z * [new tag] ciflow/h100/161225 -> ciflow/h100/161225 2025-08-26T19:43:48.2980334Z * [new tag] ciflow/inductor-perf-test-nightly-rocm/151845 -> ciflow/inductor-perf-test-nightly-rocm/151845 2025-08-26T19:43:48.2981056Z * [new tag] ciflow/inductor-perf-test-nightly-x86-zen/161512 -> ciflow/inductor-perf-test-nightly-x86-zen/161512 2025-08-26T19:43:48.2982058Z * [new tag] ciflow/inductor-periodic/158137 -> ciflow/inductor-periodic/158137 2025-08-26T19:43:48.2982571Z * [new tag] ciflow/inductor-periodic/160807 -> ciflow/inductor-periodic/160807 2025-08-26T19:43:48.2983308Z * [new tag] ciflow/inductor-periodic/161461 -> ciflow/inductor-periodic/161461 2025-08-26T19:43:48.2984357Z * [new tag] ciflow/inductor-periodic/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 -> ciflow/inductor-periodic/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 2025-08-26T19:43:48.2985492Z * [new tag] ciflow/inductor-periodic/3e5b021f217a42ae55dc690083f67a28126808ed -> ciflow/inductor-periodic/3e5b021f217a42ae55dc690083f67a28126808ed 2025-08-26T19:43:48.2986573Z * [new tag] ciflow/inductor-periodic/f912c93344caa74e24c8164a2e25fe84a8203073 -> ciflow/inductor-periodic/f912c93344caa74e24c8164a2e25fe84a8203073 2025-08-26T19:43:48.2987045Z * [new tag] ciflow/inductor-rocm/151845 -> ciflow/inductor-rocm/151845 2025-08-26T19:43:48.2987632Z * [new tag] ciflow/inductor-rocm/159158 -> ciflow/inductor-rocm/159158 2025-08-26T19:43:48.2988503Z * [new tag] ciflow/inductor-rocm/160671 -> ciflow/inductor-rocm/160671 2025-08-26T19:43:48.2989315Z * [new tag] ciflow/inductor-rocm/161180 -> ciflow/inductor-rocm/161180 2025-08-26T19:43:48.2989951Z * [new tag] ciflow/inductor-rocm/161225 -> ciflow/inductor-rocm/161225 2025-08-26T19:43:48.2990878Z * [new tag] ciflow/inductor-rocm/161521 -> ciflow/inductor-rocm/161521 2025-08-26T19:43:48.2991725Z * [new tag] ciflow/inductor-windows/160406 -> ciflow/inductor-windows/160406 2025-08-26T19:43:48.2992462Z * [new tag] ciflow/inductor/148492 -> ciflow/inductor/148492 2025-08-26T19:43:48.2993055Z * [new tag] ciflow/inductor/151845 -> ciflow/inductor/151845 2025-08-26T19:43:48.2993735Z * [new tag] ciflow/inductor/154694 -> ciflow/inductor/154694 2025-08-26T19:43:48.2994396Z * [new tag] ciflow/inductor/155072 -> ciflow/inductor/155072 2025-08-26T19:43:48.2995012Z * [new tag] ciflow/inductor/155152 -> ciflow/inductor/155152 2025-08-26T19:43:48.2995679Z * [new tag] ciflow/inductor/155153 -> ciflow/inductor/155153 2025-08-26T19:43:48.2996309Z * [new tag] ciflow/inductor/155154 -> ciflow/inductor/155154 2025-08-26T19:43:48.2996976Z * [new tag] ciflow/inductor/155501 -> ciflow/inductor/155501 2025-08-26T19:43:48.2997595Z * [new tag] ciflow/inductor/155502 -> ciflow/inductor/155502 2025-08-26T19:43:48.2998256Z * [new tag] ciflow/inductor/155503 -> ciflow/inductor/155503 2025-08-26T19:43:48.2998955Z * [new tag] ciflow/inductor/155557 -> ciflow/inductor/155557 2025-08-26T19:43:48.2999938Z * [new tag] ciflow/inductor/155608 -> ciflow/inductor/155608 2025-08-26T19:43:48.3000875Z * [new tag] ciflow/inductor/155923 -> ciflow/inductor/155923 2025-08-26T19:43:48.3001572Z * [new tag] ciflow/inductor/155928 -> ciflow/inductor/155928 2025-08-26T19:43:48.3002698Z * [new tag] ciflow/inductor/156875 -> ciflow/inductor/156875 2025-08-26T19:43:48.3003221Z * [new tag] ciflow/inductor/156967 -> ciflow/inductor/156967 2025-08-26T19:43:48.3003945Z * [new tag] ciflow/inductor/157298 -> ciflow/inductor/157298 2025-08-26T19:43:48.3004618Z * [new tag] ciflow/inductor/157572 -> ciflow/inductor/157572 2025-08-26T19:43:48.3005332Z * [new tag] ciflow/inductor/157635 -> ciflow/inductor/157635 2025-08-26T19:43:48.3006102Z * [new tag] ciflow/inductor/157743 -> ciflow/inductor/157743 2025-08-26T19:43:48.3006785Z * [new tag] ciflow/inductor/157767 -> ciflow/inductor/157767 2025-08-26T19:43:48.3007455Z * [new tag] ciflow/inductor/157944 -> ciflow/inductor/157944 2025-08-26T19:43:48.3008149Z * [new tag] ciflow/inductor/158061 -> ciflow/inductor/158061 2025-08-26T19:43:48.3008907Z * [new tag] ciflow/inductor/158097 -> ciflow/inductor/158097 2025-08-26T19:43:48.3009653Z * [new tag] ciflow/inductor/158098 -> ciflow/inductor/158098 2025-08-26T19:43:48.3010346Z * [new tag] ciflow/inductor/158104 -> ciflow/inductor/158104 2025-08-26T19:43:48.3011052Z * [new tag] ciflow/inductor/158137 -> ciflow/inductor/158137 2025-08-26T19:43:48.3011712Z * [new tag] ciflow/inductor/158321 -> ciflow/inductor/158321 2025-08-26T19:43:48.3012403Z * [new tag] ciflow/inductor/158609 -> ciflow/inductor/158609 2025-08-26T19:43:48.3013366Z * [new tag] ciflow/inductor/158932 -> ciflow/inductor/158932 2025-08-26T19:43:48.3013917Z * [new tag] ciflow/inductor/159003 -> ciflow/inductor/159003 2025-08-26T19:43:48.3014609Z * [new tag] ciflow/inductor/159158 -> ciflow/inductor/159158 2025-08-26T19:43:48.3015456Z * [new tag] ciflow/inductor/159274 -> ciflow/inductor/159274 2025-08-26T19:43:48.3016126Z * [new tag] ciflow/inductor/159387 -> ciflow/inductor/159387 2025-08-26T19:43:48.3016921Z * [new tag] ciflow/inductor/159473 -> ciflow/inductor/159473 2025-08-26T19:43:48.3017588Z * [new tag] ciflow/inductor/159664 -> ciflow/inductor/159664 2025-08-26T19:43:48.3018570Z * [new tag] ciflow/inductor/159778 -> ciflow/inductor/159778 2025-08-26T19:43:48.3019202Z * [new tag] ciflow/inductor/159835 -> ciflow/inductor/159835 2025-08-26T19:43:48.3019833Z * [new tag] ciflow/inductor/159889 -> ciflow/inductor/159889 2025-08-26T19:43:48.3020738Z * [new tag] ciflow/inductor/159923 -> ciflow/inductor/159923 2025-08-26T19:43:48.3021436Z * [new tag] ciflow/inductor/159944 -> ciflow/inductor/159944 2025-08-26T19:43:48.3022114Z * [new tag] ciflow/inductor/160080 -> ciflow/inductor/160080 2025-08-26T19:43:48.3023078Z * [new tag] ciflow/inductor/160111 -> ciflow/inductor/160111 2025-08-26T19:43:48.3023788Z * [new tag] ciflow/inductor/160156 -> ciflow/inductor/160156 2025-08-26T19:43:48.3024577Z * [new tag] ciflow/inductor/160180 -> ciflow/inductor/160180 2025-08-26T19:43:48.3025514Z * [new tag] ciflow/inductor/160198 -> ciflow/inductor/160198 2025-08-26T19:43:48.3026289Z * [new tag] ciflow/inductor/160258 -> ciflow/inductor/160258 2025-08-26T19:43:48.3026926Z * [new tag] ciflow/inductor/160266 -> ciflow/inductor/160266 2025-08-26T19:43:48.3027598Z * [new tag] ciflow/inductor/160282 -> ciflow/inductor/160282 2025-08-26T19:43:48.3028512Z * [new tag] ciflow/inductor/160323 -> ciflow/inductor/160323 2025-08-26T19:43:48.3029452Z * [new tag] ciflow/inductor/160324 -> ciflow/inductor/160324 2025-08-26T19:43:48.3030342Z * [new tag] ciflow/inductor/160325 -> ciflow/inductor/160325 2025-08-26T19:43:48.3031329Z * [new tag] ciflow/inductor/160326 -> ciflow/inductor/160326 2025-08-26T19:43:48.3031855Z * [new tag] ciflow/inductor/160327 -> ciflow/inductor/160327 2025-08-26T19:43:48.3032773Z * [new tag] ciflow/inductor/160328 -> ciflow/inductor/160328 2025-08-26T19:43:48.3033510Z * [new tag] ciflow/inductor/160329 -> ciflow/inductor/160329 2025-08-26T19:43:48.3034475Z * [new tag] ciflow/inductor/160431 -> ciflow/inductor/160431 2025-08-26T19:43:48.3035614Z * [new tag] ciflow/inductor/160448 -> ciflow/inductor/160448 2025-08-26T19:43:48.3036286Z * [new tag] ciflow/inductor/160449 -> ciflow/inductor/160449 2025-08-26T19:43:48.3036954Z * [new tag] ciflow/inductor/160467 -> ciflow/inductor/160467 2025-08-26T19:43:48.3037739Z * [new tag] ciflow/inductor/160470 -> ciflow/inductor/160470 2025-08-26T19:43:48.3038488Z * [new tag] ciflow/inductor/160483 -> ciflow/inductor/160483 2025-08-26T19:43:48.3039156Z * [new tag] ciflow/inductor/160527 -> ciflow/inductor/160527 2025-08-26T19:43:48.3040209Z * [new tag] ciflow/inductor/160532 -> ciflow/inductor/160532 2025-08-26T19:43:48.3041633Z * [new tag] ciflow/inductor/160539 -> ciflow/inductor/160539 2025-08-26T19:43:48.3042214Z * [new tag] ciflow/inductor/160580 -> ciflow/inductor/160580 2025-08-26T19:43:48.3042944Z * [new tag] ciflow/inductor/160601 -> ciflow/inductor/160601 2025-08-26T19:43:48.3043626Z * [new tag] ciflow/inductor/160611 -> ciflow/inductor/160611 2025-08-26T19:43:48.3044355Z * [new tag] ciflow/inductor/160669 -> ciflow/inductor/160669 2025-08-26T19:43:48.3045013Z * [new tag] ciflow/inductor/160670 -> ciflow/inductor/160670 2025-08-26T19:43:48.3045734Z * [new tag] ciflow/inductor/160671 -> ciflow/inductor/160671 2025-08-26T19:43:48.3046628Z * [new tag] ciflow/inductor/160677 -> ciflow/inductor/160677 2025-08-26T19:43:48.3047210Z * [new tag] ciflow/inductor/160690 -> ciflow/inductor/160690 2025-08-26T19:43:48.3047940Z * [new tag] ciflow/inductor/160763 -> ciflow/inductor/160763 2025-08-26T19:43:48.3048638Z * [new tag] ciflow/inductor/160772 -> ciflow/inductor/160772 2025-08-26T19:43:48.3049760Z * [new tag] ciflow/inductor/160798 -> ciflow/inductor/160798 2025-08-26T19:43:48.3050432Z * [new tag] ciflow/inductor/160807 -> ciflow/inductor/160807 2025-08-26T19:43:48.3051188Z * [new tag] ciflow/inductor/160836 -> ciflow/inductor/160836 2025-08-26T19:43:48.3051872Z * [new tag] ciflow/inductor/160861 -> ciflow/inductor/160861 2025-08-26T19:43:48.3052546Z * [new tag] ciflow/inductor/160883 -> ciflow/inductor/160883 2025-08-26T19:43:48.3053230Z * [new tag] ciflow/inductor/160888 -> ciflow/inductor/160888 2025-08-26T19:43:48.3053957Z * [new tag] ciflow/inductor/160903 -> ciflow/inductor/160903 2025-08-26T19:43:48.3054595Z * [new tag] ciflow/inductor/160913 -> ciflow/inductor/160913 2025-08-26T19:43:48.3055436Z * [new tag] ciflow/inductor/160941 -> ciflow/inductor/160941 2025-08-26T19:43:48.3056021Z * [new tag] ciflow/inductor/160943 -> ciflow/inductor/160943 2025-08-26T19:43:48.3056733Z * [new tag] ciflow/inductor/160991 -> ciflow/inductor/160991 2025-08-26T19:43:48.3057768Z * [new tag] ciflow/inductor/160997 -> ciflow/inductor/160997 2025-08-26T19:43:48.3058320Z * [new tag] ciflow/inductor/161003 -> ciflow/inductor/161003 2025-08-26T19:43:48.3059027Z * [new tag] ciflow/inductor/161026 -> ciflow/inductor/161026 2025-08-26T19:43:48.3059758Z * [new tag] ciflow/inductor/161032 -> ciflow/inductor/161032 2025-08-26T19:43:48.3060668Z * [new tag] ciflow/inductor/161040 -> ciflow/inductor/161040 2025-08-26T19:43:48.3061322Z * [new tag] ciflow/inductor/161055 -> ciflow/inductor/161055 2025-08-26T19:43:48.3062010Z * [new tag] ciflow/inductor/161062 -> ciflow/inductor/161062 2025-08-26T19:43:48.3062690Z * [new tag] ciflow/inductor/161069 -> ciflow/inductor/161069 2025-08-26T19:43:48.3063364Z * [new tag] ciflow/inductor/161092 -> ciflow/inductor/161092 2025-08-26T19:43:48.3064035Z * [new tag] ciflow/inductor/161093 -> ciflow/inductor/161093 2025-08-26T19:43:48.3064741Z * [new tag] ciflow/inductor/161097 -> ciflow/inductor/161097 2025-08-26T19:43:48.3065416Z * [new tag] ciflow/inductor/161098 -> ciflow/inductor/161098 2025-08-26T19:43:48.3066127Z * [new tag] ciflow/inductor/161100 -> ciflow/inductor/161100 2025-08-26T19:43:48.3066905Z * [new tag] ciflow/inductor/161107 -> ciflow/inductor/161107 2025-08-26T19:43:48.3067970Z * [new tag] ciflow/inductor/161110 -> ciflow/inductor/161110 2025-08-26T19:43:48.3068610Z * [new tag] ciflow/inductor/161117 -> ciflow/inductor/161117 2025-08-26T19:43:48.3069257Z * [new tag] ciflow/inductor/161118 -> ciflow/inductor/161118 2025-08-26T19:43:48.3069950Z * [new tag] ciflow/inductor/161123 -> ciflow/inductor/161123 2025-08-26T19:43:48.3070667Z * [new tag] ciflow/inductor/161124 -> ciflow/inductor/161124 2025-08-26T19:43:48.3071341Z * [new tag] ciflow/inductor/161125 -> ciflow/inductor/161125 2025-08-26T19:43:48.3071999Z * [new tag] ciflow/inductor/161126 -> ciflow/inductor/161126 2025-08-26T19:43:48.3073010Z * [new tag] ciflow/inductor/161144 -> ciflow/inductor/161144 2025-08-26T19:43:48.3073759Z * [new tag] ciflow/inductor/161148 -> ciflow/inductor/161148 2025-08-26T19:43:48.3074439Z * [new tag] ciflow/inductor/161158 -> ciflow/inductor/161158 2025-08-26T19:43:48.3075480Z * [new tag] ciflow/inductor/161178 -> ciflow/inductor/161178 2025-08-26T19:43:48.3076082Z * [new tag] ciflow/inductor/161190 -> ciflow/inductor/161190 2025-08-26T19:43:48.3077013Z * [new tag] ciflow/inductor/161208 -> ciflow/inductor/161208 2025-08-26T19:43:48.3077668Z * [new tag] ciflow/inductor/161225 -> ciflow/inductor/161225 2025-08-26T19:43:48.3078435Z * [new tag] ciflow/inductor/161229 -> ciflow/inductor/161229 2025-08-26T19:43:48.3079242Z * [new tag] ciflow/inductor/161237 -> ciflow/inductor/161237 2025-08-26T19:43:48.3079928Z * [new tag] ciflow/inductor/161241 -> ciflow/inductor/161241 2025-08-26T19:43:48.3080827Z * [new tag] ciflow/inductor/161246 -> ciflow/inductor/161246 2025-08-26T19:43:48.3081527Z * [new tag] ciflow/inductor/161274 -> ciflow/inductor/161274 2025-08-26T19:43:48.3082633Z * [new tag] ciflow/inductor/161278 -> ciflow/inductor/161278 2025-08-26T19:43:48.3083175Z * [new tag] ciflow/inductor/161279 -> ciflow/inductor/161279 2025-08-26T19:43:48.3084348Z * [new tag] ciflow/inductor/161288 -> ciflow/inductor/161288 2025-08-26T19:43:48.3085070Z * [new tag] ciflow/inductor/161314 -> ciflow/inductor/161314 2025-08-26T19:43:48.3085783Z * [new tag] ciflow/inductor/161320 -> ciflow/inductor/161320 2025-08-26T19:43:48.3086458Z * [new tag] ciflow/inductor/161336 -> ciflow/inductor/161336 2025-08-26T19:43:48.3087152Z * [new tag] ciflow/inductor/161337 -> ciflow/inductor/161337 2025-08-26T19:43:48.3087870Z * [new tag] ciflow/inductor/161338 -> ciflow/inductor/161338 2025-08-26T19:43:48.3088527Z * [new tag] ciflow/inductor/161339 -> ciflow/inductor/161339 2025-08-26T19:43:48.3089342Z * [new tag] ciflow/inductor/161340 -> ciflow/inductor/161340 2025-08-26T19:43:48.3090035Z * [new tag] ciflow/inductor/161341 -> ciflow/inductor/161341 2025-08-26T19:43:48.3090726Z * [new tag] ciflow/inductor/161342 -> ciflow/inductor/161342 2025-08-26T19:43:48.3091427Z * [new tag] ciflow/inductor/161343 -> ciflow/inductor/161343 2025-08-26T19:43:48.3092114Z * [new tag] ciflow/inductor/161344 -> ciflow/inductor/161344 2025-08-26T19:43:48.3092791Z * [new tag] ciflow/inductor/161345 -> ciflow/inductor/161345 2025-08-26T19:43:48.3093476Z * [new tag] ciflow/inductor/161346 -> ciflow/inductor/161346 2025-08-26T19:43:48.3094174Z * [new tag] ciflow/inductor/161347 -> ciflow/inductor/161347 2025-08-26T19:43:48.3094880Z * [new tag] ciflow/inductor/161348 -> ciflow/inductor/161348 2025-08-26T19:43:48.3095558Z * [new tag] ciflow/inductor/161349 -> ciflow/inductor/161349 2025-08-26T19:43:48.3096275Z * [new tag] ciflow/inductor/161350 -> ciflow/inductor/161350 2025-08-26T19:43:48.3097226Z * [new tag] ciflow/inductor/161351 -> ciflow/inductor/161351 2025-08-26T19:43:48.3097765Z * [new tag] ciflow/inductor/161353 -> ciflow/inductor/161353 2025-08-26T19:43:48.3098483Z * [new tag] ciflow/inductor/161354 -> ciflow/inductor/161354 2025-08-26T19:43:48.3099148Z * [new tag] ciflow/inductor/161355 -> ciflow/inductor/161355 2025-08-26T19:43:48.3099846Z * [new tag] ciflow/inductor/161362 -> ciflow/inductor/161362 2025-08-26T19:43:48.3100549Z * [new tag] ciflow/inductor/161363 -> ciflow/inductor/161363 2025-08-26T19:43:48.3101235Z * [new tag] ciflow/inductor/161382 -> ciflow/inductor/161382 2025-08-26T19:43:48.3101911Z * [new tag] ciflow/inductor/161383 -> ciflow/inductor/161383 2025-08-26T19:43:48.3102602Z * [new tag] ciflow/inductor/161385 -> ciflow/inductor/161385 2025-08-26T19:43:48.3103385Z * [new tag] ciflow/inductor/161396 -> ciflow/inductor/161396 2025-08-26T19:43:48.3104107Z * [new tag] ciflow/inductor/161397 -> ciflow/inductor/161397 2025-08-26T19:43:48.3104825Z * [new tag] ciflow/inductor/161404 -> ciflow/inductor/161404 2025-08-26T19:43:48.3105489Z * [new tag] ciflow/inductor/161405 -> ciflow/inductor/161405 2025-08-26T19:43:48.3106227Z * [new tag] ciflow/inductor/161406 -> ciflow/inductor/161406 2025-08-26T19:43:48.3107122Z * [new tag] ciflow/inductor/161409 -> ciflow/inductor/161409 2025-08-26T19:43:48.3108075Z * [new tag] ciflow/inductor/161410 -> ciflow/inductor/161410 2025-08-26T19:43:48.3108620Z * [new tag] ciflow/inductor/161414 -> ciflow/inductor/161414 2025-08-26T19:43:48.3109768Z * [new tag] ciflow/inductor/161416 -> ciflow/inductor/161416 2025-08-26T19:43:48.3110042Z * [new tag] ciflow/inductor/161420 -> ciflow/inductor/161420 2025-08-26T19:43:48.3110771Z * [new tag] ciflow/inductor/161431 -> ciflow/inductor/161431 2025-08-26T19:43:48.3111472Z * [new tag] ciflow/inductor/161435 -> ciflow/inductor/161435 2025-08-26T19:43:48.3112412Z * [new tag] ciflow/inductor/161440 -> ciflow/inductor/161440 2025-08-26T19:43:48.3113054Z * [new tag] ciflow/inductor/161447 -> ciflow/inductor/161447 2025-08-26T19:43:48.3113695Z * [new tag] ciflow/inductor/161452 -> ciflow/inductor/161452 2025-08-26T19:43:48.3114484Z * [new tag] ciflow/inductor/161453 -> ciflow/inductor/161453 2025-08-26T19:43:48.3115123Z * [new tag] ciflow/inductor/161458 -> ciflow/inductor/161458 2025-08-26T19:43:48.3115805Z * [new tag] ciflow/inductor/161461 -> ciflow/inductor/161461 2025-08-26T19:43:48.3116515Z * [new tag] ciflow/inductor/161464 -> ciflow/inductor/161464 2025-08-26T19:43:48.3117233Z * [new tag] ciflow/inductor/161466 -> ciflow/inductor/161466 2025-08-26T19:43:48.3117913Z * [new tag] ciflow/inductor/161468 -> ciflow/inductor/161468 2025-08-26T19:43:48.3118623Z * [new tag] ciflow/inductor/161469 -> ciflow/inductor/161469 2025-08-26T19:43:48.3119357Z * [new tag] ciflow/inductor/161474 -> ciflow/inductor/161474 2025-08-26T19:43:48.3120136Z * [new tag] ciflow/inductor/161477 -> ciflow/inductor/161477 2025-08-26T19:43:48.3121042Z * [new tag] ciflow/inductor/161485 -> ciflow/inductor/161485 2025-08-26T19:43:48.3121657Z * [new tag] ciflow/inductor/161486 -> ciflow/inductor/161486 2025-08-26T19:43:48.3122369Z * [new tag] ciflow/inductor/161487 -> ciflow/inductor/161487 2025-08-26T19:43:48.3123066Z * [new tag] ciflow/inductor/161495 -> ciflow/inductor/161495 2025-08-26T19:43:48.3123995Z * [new tag] ciflow/inductor/161497 -> ciflow/inductor/161497 2025-08-26T19:43:48.3124552Z * [new tag] ciflow/inductor/161499 -> ciflow/inductor/161499 2025-08-26T19:43:48.3125292Z * [new tag] ciflow/inductor/161512 -> ciflow/inductor/161512 2025-08-26T19:43:48.3125964Z * [new tag] ciflow/inductor/161521 -> ciflow/inductor/161521 2025-08-26T19:43:48.3126668Z * [new tag] ciflow/inductor/161526 -> ciflow/inductor/161526 2025-08-26T19:43:48.3127355Z * [new tag] ciflow/inductor/161530 -> ciflow/inductor/161530 2025-08-26T19:43:48.3128367Z * [new tag] ciflow/inductor/3b9a386 -> ciflow/inductor/3b9a386 2025-08-26T19:43:48.3129220Z * [new tag] ciflow/inductor/3d4b92b -> ciflow/inductor/3d4b92b 2025-08-26T19:43:48.3130255Z * [new tag] ciflow/inductor/d224ac7 -> ciflow/inductor/d224ac7 2025-08-26T19:43:48.3130992Z * [new tag] ciflow/linux-aarch64/159737 -> ciflow/linux-aarch64/159737 2025-08-26T19:43:48.3131631Z * [new tag] ciflow/linux-aarch64/160078 -> ciflow/linux-aarch64/160078 2025-08-26T19:43:48.3132281Z * [new tag] ciflow/linux-aarch64/160080 -> ciflow/linux-aarch64/160080 2025-08-26T19:43:48.3133043Z * [new tag] ciflow/mps/155923 -> ciflow/mps/155923 2025-08-26T19:43:48.3133697Z * [new tag] ciflow/mps/157553 -> ciflow/mps/157553 2025-08-26T19:43:48.3134323Z * [new tag] ciflow/mps/157635 -> ciflow/mps/157635 2025-08-26T19:43:48.3135094Z * [new tag] ciflow/mps/160839 -> ciflow/mps/160839 2025-08-26T19:43:48.3135732Z * [new tag] ciflow/mps/161511 -> ciflow/mps/161511 2025-08-26T19:43:48.3136656Z * [new tag] ciflow/nightly/158104 -> ciflow/nightly/158104 2025-08-26T19:43:48.3137556Z * [new tag] ciflow/periodic-rocm-mi300/161180 -> ciflow/periodic-rocm-mi300/161180 2025-08-26T19:43:48.3138608Z * [new tag] ciflow/periodic/054a2fd -> ciflow/periodic/054a2fd 2025-08-26T19:43:48.3139658Z * [new tag] ciflow/periodic/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 -> ciflow/periodic/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 2025-08-26T19:43:48.3140070Z * [new tag] ciflow/periodic/156491 -> ciflow/periodic/156491 2025-08-26T19:43:48.3141058Z * [new tag] ciflow/periodic/161013 -> ciflow/periodic/161013 2025-08-26T19:43:48.3141831Z * [new tag] ciflow/periodic/2a6d37d -> ciflow/periodic/2a6d37d 2025-08-26T19:43:48.3142589Z * [new tag] ciflow/periodic/317eeb8 -> ciflow/periodic/317eeb8 2025-08-26T19:43:48.3143354Z * [new tag] ciflow/periodic/3c32 -> ciflow/periodic/3c32 2025-08-26T19:43:48.3144353Z * [new tag] ciflow/periodic/3e98831 -> ciflow/periodic/3e98831 2025-08-26T19:43:48.3145551Z * [new tag] ciflow/periodic/94512-point -> ciflow/periodic/94512-point 2025-08-26T19:43:48.3146920Z * [new tag] ciflow/periodic/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 -> ciflow/periodic/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 2025-08-26T19:43:48.3147543Z * [new tag] ciflow/periodic/csl/test87519 -> ciflow/periodic/csl/test87519 2025-08-26T19:43:48.3148519Z * [new tag] ciflow/periodic/csltest88275 -> ciflow/periodic/csltest88275 2025-08-26T19:43:48.3149272Z * [new tag] ciflow/periodic/csltest88761 -> ciflow/periodic/csltest88761 2025-08-26T19:43:48.3150113Z * [new tag] ciflow/periodic/release_1.12 -> ciflow/periodic/release_1.12 2025-08-26T19:43:48.3151226Z * [new tag] ciflow/periodic/release_1.12.0 -> ciflow/periodic/release_1.12.0 2025-08-26T19:43:48.3152047Z * [new tag] ciflow/periodic/sha-ec5b83 -> ciflow/periodic/sha-ec5b83 2025-08-26T19:43:48.3152977Z * [new tag] ciflow/rocm-mi300/159158 -> ciflow/rocm-mi300/159158 2025-08-26T19:43:48.3153524Z * [new tag] ciflow/rocm-mi300/161040 -> ciflow/rocm-mi300/161040 2025-08-26T19:43:48.3154228Z * [new tag] ciflow/rocm-mi300/161180 -> ciflow/rocm-mi300/161180 2025-08-26T19:43:48.3154837Z * [new tag] ciflow/rocm-mi300/161225 -> ciflow/rocm-mi300/161225 2025-08-26T19:43:48.3155795Z * [new tag] ciflow/rocm-mi300/161429 -> ciflow/rocm-mi300/161429 2025-08-26T19:43:48.3156757Z * [new tag] ciflow/rocm-mi355/160215 -> ciflow/rocm-mi355/160215 2025-08-26T19:43:48.3157447Z * [new tag] ciflow/rocm/148492 -> ciflow/rocm/148492 2025-08-26T19:43:48.3158093Z * [new tag] ciflow/rocm/151845 -> ciflow/rocm/151845 2025-08-26T19:43:48.3159369Z * [new tag] ciflow/rocm/152526 -> ciflow/rocm/152526 2025-08-26T19:43:48.3159920Z * [new tag] ciflow/rocm/156491 -> ciflow/rocm/156491 2025-08-26T19:43:48.3160690Z * [new tag] ciflow/rocm/158352 -> ciflow/rocm/158352 2025-08-26T19:43:48.3161358Z * [new tag] ciflow/rocm/159158 -> ciflow/rocm/159158 2025-08-26T19:43:48.3161944Z * [new tag] ciflow/rocm/160215 -> ciflow/rocm/160215 2025-08-26T19:43:48.3162643Z * [new tag] ciflow/rocm/160671 -> ciflow/rocm/160671 2025-08-26T19:43:48.3163611Z * [new tag] ciflow/rocm/160676 -> ciflow/rocm/160676 2025-08-26T19:43:48.3164324Z * [new tag] ciflow/rocm/161180 -> ciflow/rocm/161180 2025-08-26T19:43:48.3164909Z * [new tag] ciflow/rocm/161225 -> ciflow/rocm/161225 2025-08-26T19:43:48.3166134Z * [new tag] ciflow/rocm/161277 -> ciflow/rocm/161277 2025-08-26T19:43:48.3166880Z * [new tag] ciflow/rocm/161429 -> ciflow/rocm/161429 2025-08-26T19:43:48.3167782Z * [new tag] ciflow/rocm/161496 -> ciflow/rocm/161496 2025-08-26T19:43:48.3169252Z * [new tag] ciflow/s390/160893 -> ciflow/s390/160893 2025-08-26T19:43:48.3170215Z * [new tag] ciflow/slow/01c7106 -> ciflow/slow/01c7106 2025-08-26T19:43:48.3170936Z * [new tag] ciflow/slow/0577043 -> ciflow/slow/0577043 2025-08-26T19:43:48.3172238Z * [new tag] ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym -> ciflow/slow/0d5b74da0cab798fbfdb9caa53fad816999c8386-sdym 2025-08-26T19:43:48.3172630Z * [new tag] ciflow/slow/0e81104 -> ciflow/slow/0e81104 2025-08-26T19:43:48.3173869Z * [new tag] ciflow/slow/161182 -> ciflow/slow/161182 2025-08-26T19:43:48.3174552Z * [new tag] ciflow/slow/161395 -> ciflow/slow/161395 2025-08-26T19:43:48.3175293Z * [new tag] ciflow/slow/1732077 -> ciflow/slow/1732077 2025-08-26T19:43:48.3176274Z * [new tag] ciflow/slow/187eb7c -> ciflow/slow/187eb7c 2025-08-26T19:43:48.3177304Z * [new tag] ciflow/slow/1faef89 -> ciflow/slow/1faef89 2025-08-26T19:43:48.3178386Z * [new tag] ciflow/slow/3920ec1 -> ciflow/slow/3920ec1 2025-08-26T19:43:48.3179338Z * [new tag] ciflow/slow/3b7c6b2 -> ciflow/slow/3b7c6b2 2025-08-26T19:43:48.3180127Z * [new tag] ciflow/slow/59a3759 -> ciflow/slow/59a3759 2025-08-26T19:43:48.3180990Z * [new tag] ciflow/slow/70ef0bb -> ciflow/slow/70ef0bb 2025-08-26T19:43:48.3181739Z * [new tag] ciflow/slow/788ff06 -> ciflow/slow/788ff06 2025-08-26T19:43:48.3183196Z * [new tag] ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym -> ciflow/slow/8751002215790a3a88750faa8f4366933e296693-sdym 2025-08-26T19:43:48.3183563Z * [new tag] ciflow/slow/9d85864 -> ciflow/slow/9d85864 2025-08-26T19:43:48.3184475Z * [new tag] ciflow/slow/9ffad5b -> ciflow/slow/9ffad5b 2025-08-26T19:43:48.3185190Z * [new tag] ciflow/slow/a206e8b -> ciflow/slow/a206e8b 2025-08-26T19:43:48.3186218Z * [new tag] ciflow/slow/a837609 -> ciflow/slow/a837609 2025-08-26T19:43:48.3186964Z * [new tag] ciflow/slow/af841f3 -> ciflow/slow/af841f3 2025-08-26T19:43:48.3188375Z * [new tag] ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym -> ciflow/slow/da3aba1e46157c4df504b067477cdf2b3c96b194-sdym 2025-08-26T19:43:48.3188762Z * [new tag] ciflow/torchbench/158137 -> ciflow/torchbench/158137 2025-08-26T19:43:48.3189737Z * [new tag] ciflow/trunk/148492 -> ciflow/trunk/148492 2025-08-26T19:43:48.3190772Z * [new tag] ciflow/trunk/151845 -> ciflow/trunk/151845 2025-08-26T19:43:48.3191452Z * [new tag] ciflow/trunk/153784 -> ciflow/trunk/153784 2025-08-26T19:43:48.3192098Z * [new tag] ciflow/trunk/154694 -> ciflow/trunk/154694 2025-08-26T19:43:48.3192883Z * [new tag] ciflow/trunk/156418 -> ciflow/trunk/156418 2025-08-26T19:43:48.3193626Z * [new tag] ciflow/trunk/157196 -> ciflow/trunk/157196 2025-08-26T19:43:48.3194381Z * [new tag] ciflow/trunk/157537 -> ciflow/trunk/157537 2025-08-26T19:43:48.3195053Z * [new tag] ciflow/trunk/157767 -> ciflow/trunk/157767 2025-08-26T19:43:48.3195710Z * [new tag] ciflow/trunk/157944 -> ciflow/trunk/157944 2025-08-26T19:43:48.3196390Z * [new tag] ciflow/trunk/158104 -> ciflow/trunk/158104 2025-08-26T19:43:48.3196988Z * [new tag] ciflow/trunk/158541 -> ciflow/trunk/158541 2025-08-26T19:43:48.3197971Z * [new tag] ciflow/trunk/158733 -> ciflow/trunk/158733 2025-08-26T19:43:48.3199048Z * [new tag] ciflow/trunk/158747 -> ciflow/trunk/158747 2025-08-26T19:43:48.3199775Z * [new tag] ciflow/trunk/159158 -> ciflow/trunk/159158 2025-08-26T19:43:48.3200453Z * [new tag] ciflow/trunk/159387 -> ciflow/trunk/159387 2025-08-26T19:43:48.3201132Z * [new tag] ciflow/trunk/159562 -> ciflow/trunk/159562 2025-08-26T19:43:48.3201864Z * [new tag] ciflow/trunk/159835 -> ciflow/trunk/159835 2025-08-26T19:43:48.3202450Z * [new tag] ciflow/trunk/159889 -> ciflow/trunk/159889 2025-08-26T19:43:48.3203201Z * [new tag] ciflow/trunk/159923 -> ciflow/trunk/159923 2025-08-26T19:43:48.3203900Z * [new tag] ciflow/trunk/160156 -> ciflow/trunk/160156 2025-08-26T19:43:48.3204605Z * [new tag] ciflow/trunk/160180 -> ciflow/trunk/160180 2025-08-26T19:43:48.3205301Z * [new tag] ciflow/trunk/160198 -> ciflow/trunk/160198 2025-08-26T19:43:48.3206007Z * [new tag] ciflow/trunk/160258 -> ciflow/trunk/160258 2025-08-26T19:43:48.3206679Z * [new tag] ciflow/trunk/160431 -> ciflow/trunk/160431 2025-08-26T19:43:48.3207351Z * [new tag] ciflow/trunk/160448 -> ciflow/trunk/160448 2025-08-26T19:43:48.3208021Z * [new tag] ciflow/trunk/160449 -> ciflow/trunk/160449 2025-08-26T19:43:48.3208682Z * [new tag] ciflow/trunk/160527 -> ciflow/trunk/160527 2025-08-26T19:43:48.3209482Z * [new tag] ciflow/trunk/160532 -> ciflow/trunk/160532 2025-08-26T19:43:48.3210210Z * [new tag] ciflow/trunk/160671 -> ciflow/trunk/160671 2025-08-26T19:43:48.3210887Z * [new tag] ciflow/trunk/160677 -> ciflow/trunk/160677 2025-08-26T19:43:48.3211767Z * [new tag] ciflow/trunk/160692 -> ciflow/trunk/160692 2025-08-26T19:43:48.3212479Z * [new tag] ciflow/trunk/160781 -> ciflow/trunk/160781 2025-08-26T19:43:48.3213154Z * [new tag] ciflow/trunk/160825 -> ciflow/trunk/160825 2025-08-26T19:43:48.3213789Z * [new tag] ciflow/trunk/160836 -> ciflow/trunk/160836 2025-08-26T19:43:48.3214805Z * [new tag] ciflow/trunk/160866 -> ciflow/trunk/160866 2025-08-26T19:43:48.3215515Z * [new tag] ciflow/trunk/160915 -> ciflow/trunk/160915 2025-08-26T19:43:48.3216216Z * [new tag] ciflow/trunk/160991 -> ciflow/trunk/160991 2025-08-26T19:43:48.3216951Z * [new tag] ciflow/trunk/160992 -> ciflow/trunk/160992 2025-08-26T19:43:48.3217655Z * [new tag] ciflow/trunk/161004 -> ciflow/trunk/161004 2025-08-26T19:43:48.3218350Z * [new tag] ciflow/trunk/161016 -> ciflow/trunk/161016 2025-08-26T19:43:48.3219308Z * [new tag] ciflow/trunk/161023 -> ciflow/trunk/161023 2025-08-26T19:43:48.3219944Z * [new tag] ciflow/trunk/161026 -> ciflow/trunk/161026 2025-08-26T19:43:48.3220566Z * [new tag] ciflow/trunk/161032 -> ciflow/trunk/161032 2025-08-26T19:43:48.3221449Z * [new tag] ciflow/trunk/161035 -> ciflow/trunk/161035 2025-08-26T19:43:48.3222050Z * [new tag] ciflow/trunk/161040 -> ciflow/trunk/161040 2025-08-26T19:43:48.3222838Z * [new tag] ciflow/trunk/161094 -> ciflow/trunk/161094 2025-08-26T19:43:48.3223497Z * [new tag] ciflow/trunk/161097 -> ciflow/trunk/161097 2025-08-26T19:43:48.3224239Z * [new tag] ciflow/trunk/161098 -> ciflow/trunk/161098 2025-08-26T19:43:48.3224893Z * [new tag] ciflow/trunk/161100 -> ciflow/trunk/161100 2025-08-26T19:43:48.3225548Z * [new tag] ciflow/trunk/161106 -> ciflow/trunk/161106 2025-08-26T19:43:48.3226247Z * [new tag] ciflow/trunk/161110 -> ciflow/trunk/161110 2025-08-26T19:43:48.3227126Z * [new tag] ciflow/trunk/161114 -> ciflow/trunk/161114 2025-08-26T19:43:48.3227711Z * [new tag] ciflow/trunk/161117 -> ciflow/trunk/161117 2025-08-26T19:43:48.3228417Z * [new tag] ciflow/trunk/161123 -> ciflow/trunk/161123 2025-08-26T19:43:48.3229112Z * [new tag] ciflow/trunk/161124 -> ciflow/trunk/161124 2025-08-26T19:43:48.3229771Z * [new tag] ciflow/trunk/161125 -> ciflow/trunk/161125 2025-08-26T19:43:48.3230472Z * [new tag] ciflow/trunk/161126 -> ciflow/trunk/161126 2025-08-26T19:43:48.3231250Z * [new tag] ciflow/trunk/161131 -> ciflow/trunk/161131 2025-08-26T19:43:48.3232203Z * [new tag] ciflow/trunk/161143 -> ciflow/trunk/161143 2025-08-26T19:43:48.3232862Z * [new tag] ciflow/trunk/161144 -> ciflow/trunk/161144 2025-08-26T19:43:48.3233522Z * [new tag] ciflow/trunk/161164 -> ciflow/trunk/161164 2025-08-26T19:43:48.3234185Z * [new tag] ciflow/trunk/161180 -> ciflow/trunk/161180 2025-08-26T19:43:48.3234866Z * [new tag] ciflow/trunk/161214 -> ciflow/trunk/161214 2025-08-26T19:43:48.3235552Z * [new tag] ciflow/trunk/161217 -> ciflow/trunk/161217 2025-08-26T19:43:48.3236329Z * [new tag] ciflow/trunk/161225 -> ciflow/trunk/161225 2025-08-26T19:43:48.3237643Z * [new tag] ciflow/trunk/161236 -> ciflow/trunk/161236 2025-08-26T19:43:48.3242753Z * [new tag] ciflow/trunk/161237 -> ciflow/trunk/161237 2025-08-26T19:43:48.3243368Z * [new tag] ciflow/trunk/161241 -> ciflow/trunk/161241 2025-08-26T19:43:48.3244299Z * [new tag] ciflow/trunk/161262 -> ciflow/trunk/161262 2025-08-26T19:43:48.3245546Z * [new tag] ciflow/trunk/161263 -> ciflow/trunk/161263 2025-08-26T19:43:48.3246101Z * [new tag] ciflow/trunk/161279 -> ciflow/trunk/161279 2025-08-26T19:43:48.3247086Z * [new tag] ciflow/trunk/161306 -> ciflow/trunk/161306 2025-08-26T19:43:48.3247767Z * [new tag] ciflow/trunk/161311 -> ciflow/trunk/161311 2025-08-26T19:43:48.3248432Z * [new tag] ciflow/trunk/161354 -> ciflow/trunk/161354 2025-08-26T19:43:48.3249192Z * [new tag] ciflow/trunk/161355 -> ciflow/trunk/161355 2025-08-26T19:43:48.3249947Z * [new tag] ciflow/trunk/161362 -> ciflow/trunk/161362 2025-08-26T19:43:48.3250630Z * [new tag] ciflow/trunk/161363 -> ciflow/trunk/161363 2025-08-26T19:43:48.3251536Z * [new tag] ciflow/trunk/161370 -> ciflow/trunk/161370 2025-08-26T19:43:48.3252127Z * [new tag] ciflow/trunk/161383 -> ciflow/trunk/161383 2025-08-26T19:43:48.3252791Z * [new tag] ciflow/trunk/161385 -> ciflow/trunk/161385 2025-08-26T19:43:48.3253720Z * [new tag] ciflow/trunk/161389 -> ciflow/trunk/161389 2025-08-26T19:43:48.3254298Z * [new tag] ciflow/trunk/161392 -> ciflow/trunk/161392 2025-08-26T19:43:48.3254943Z * [new tag] ciflow/trunk/161395 -> ciflow/trunk/161395 2025-08-26T19:43:48.3255625Z * [new tag] ciflow/trunk/161396 -> ciflow/trunk/161396 2025-08-26T19:43:48.3256306Z * [new tag] ciflow/trunk/161409 -> ciflow/trunk/161409 2025-08-26T19:43:48.3257107Z * [new tag] ciflow/trunk/161410 -> ciflow/trunk/161410 2025-08-26T19:43:48.3257724Z * [new tag] ciflow/trunk/161435 -> ciflow/trunk/161435 2025-08-26T19:43:48.3258635Z * [new tag] ciflow/trunk/161437 -> ciflow/trunk/161437 2025-08-26T19:43:48.3259356Z * [new tag] ciflow/trunk/161451 -> ciflow/trunk/161451 2025-08-26T19:43:48.3260023Z * [new tag] ciflow/trunk/161453 -> ciflow/trunk/161453 2025-08-26T19:43:48.3260897Z * [new tag] ciflow/trunk/161454 -> ciflow/trunk/161454 2025-08-26T19:43:48.3261632Z * [new tag] ciflow/trunk/161489 -> ciflow/trunk/161489 2025-08-26T19:43:48.3262603Z * [new tag] ciflow/trunk/161517 -> ciflow/trunk/161517 2025-08-26T19:43:48.3263594Z * [new tag] ciflow/unstable/123 -> ciflow/unstable/123 2025-08-26T19:43:48.3264527Z * [new tag] ciflow/win-arm64/158104 -> ciflow/win-arm64/158104 2025-08-26T19:43:48.3265169Z * [new tag] ciflow/win-arm64/159562 -> ciflow/win-arm64/159562 2025-08-26T19:43:48.3265743Z * [new tag] ciflow/win-arm64/160258 -> ciflow/win-arm64/160258 2025-08-26T19:43:48.3266709Z * [new tag] ciflow/win-arm64/161504 -> ciflow/win-arm64/161504 2025-08-26T19:43:48.3267512Z * [new tag] ciflow/xpu/143553 -> ciflow/xpu/143553 2025-08-26T19:43:48.3268169Z * [new tag] ciflow/xpu/158733 -> ciflow/xpu/158733 2025-08-26T19:43:48.3268758Z * [new tag] ciflow/xpu/159473 -> ciflow/xpu/159473 2025-08-26T19:43:48.3269422Z * [new tag] ciflow/xpu/159944 -> ciflow/xpu/159944 2025-08-26T19:43:48.3270058Z * [new tag] ciflow/xpu/160067 -> ciflow/xpu/160067 2025-08-26T19:43:48.3270970Z * [new tag] ciflow/xpu/160158 -> ciflow/xpu/160158 2025-08-26T19:43:48.3271625Z * [new tag] ciflow/xpu/160940 -> ciflow/xpu/160940 2025-08-26T19:43:48.3272403Z * [new tag] ciflow/xpu/161041 -> ciflow/xpu/161041 2025-08-26T19:43:48.3273128Z * [new tag] ciflow/xpu/161045 -> ciflow/xpu/161045 2025-08-26T19:43:48.3273817Z * [new tag] ciflow/xpu/161142 -> ciflow/xpu/161142 2025-08-26T19:43:48.3274721Z * [new tag] ciflow/xpu/161152 -> ciflow/xpu/161152 2025-08-26T19:43:48.3275648Z * [new tag] ciflow/xpu/161246 -> ciflow/xpu/161246 2025-08-26T19:43:48.3276557Z * [new tag] ciflow/xpu/161389 -> ciflow/xpu/161389 2025-08-26T19:43:48.3277424Z * [new tag] ciflow/xpu/161392 -> ciflow/xpu/161392 2025-08-26T19:43:48.3277975Z * [new tag] ciflow/xpu/161397 -> ciflow/xpu/161397 2025-08-26T19:43:48.3278749Z * [new tag] ciflow/xpu/161477 -> ciflow/xpu/161477 2025-08-26T19:43:48.3279387Z * [new tag] ciflow/xpu/161489 -> ciflow/xpu/161489 2025-08-26T19:43:48.3280320Z * [new tag] cslpull75 -> cslpull75 2025-08-26T19:43:48.3281002Z * [new tag] cslpull76 -> cslpull76 2025-08-26T19:43:48.3281725Z * [new tag] cslpull77 -> cslpull77 2025-08-26T19:43:48.3282574Z * [new tag] cslpull78 -> cslpull78 2025-08-26T19:43:48.3283582Z * [new tag] cslpull79 -> cslpull79 2025-08-26T19:43:48.3284622Z * [new tag] cslpull80 -> cslpull80 2025-08-26T19:43:48.3285376Z * [new tag] cslpull81 -> cslpull81 2025-08-26T19:43:48.3286234Z * [new tag] cslpull82 -> cslpull82 2025-08-26T19:43:48.3287027Z * [new tag] cslpull83 -> cslpull83 2025-08-26T19:43:48.3287739Z * [new tag] cslpull84 -> cslpull84 2025-08-26T19:43:48.3288656Z * [new tag] cslpull85 -> cslpull85 2025-08-26T19:43:48.3289604Z * [new tag] cslpull86 -> cslpull86 2025-08-26T19:43:48.3290463Z * [new tag] cslpull87 -> cslpull87 2025-08-26T19:43:48.3291195Z * [new tag] cslpull88 -> cslpull88 2025-08-26T19:43:48.3292077Z * [new tag] cslpull89 -> cslpull89 2025-08-26T19:43:48.3292569Z * [new tag] cslpull90 -> cslpull90 2025-08-26T19:43:48.3293920Z * [new tag] cslpull91 -> cslpull91 2025-08-26T19:43:48.3294562Z * [new tag] cslpull92 -> cslpull92 2025-08-26T19:43:48.3295421Z * [new tag] flight_5 -> flight_5 2025-08-26T19:43:48.3296309Z * [new tag] flight_5.1 -> flight_5.1 2025-08-26T19:43:48.3297151Z * [new tag] flight_5.2 -> flight_5.2 2025-08-26T19:43:48.3297782Z * [new tag] flight_5.3 -> flight_5.3 2025-08-26T19:43:48.3298665Z * [new tag] forpull1 -> forpull1 2025-08-26T19:43:48.3299705Z * [new tag] malfet/tag-2ef5611 -> malfet/tag-2ef5611 2025-08-26T19:43:48.3300456Z * [new tag] malfet/tag-317b1a0 -> malfet/tag-317b1a0 2025-08-26T19:43:48.3301254Z * [new tag] malfet/tag-ec6f767 -> malfet/tag-ec6f767 2025-08-26T19:43:48.3302160Z * [new tag] nightly-binary -> nightly-binary 2025-08-26T19:43:48.3302707Z * [new tag] sqzhang_flight4_plus -> sqzhang_flight4_plus 2025-08-26T19:43:48.3303728Z * [new tag] sqzhang_flight_3 -> sqzhang_flight_3 2025-08-26T19:43:48.3304933Z * [new tag] trunk/00efeabc295e072fb9d6e68b008a31fb04201fd1 -> trunk/00efeabc295e072fb9d6e68b008a31fb04201fd1 2025-08-26T19:43:48.3305626Z * [new tag] trunk/037c43d3b24d4db733011cb904c385eaa6e11bcf -> trunk/037c43d3b24d4db733011cb904c385eaa6e11bcf 2025-08-26T19:43:48.3306915Z * [new tag] trunk/0533ff2ccba7e77622ac3c6758f1032bdc10feff -> trunk/0533ff2ccba7e77622ac3c6758f1032bdc10feff 2025-08-26T19:43:48.3307786Z * [new tag] trunk/05e8fac4f374c4dbf0cd0e85e925e9112cf234a2 -> trunk/05e8fac4f374c4dbf0cd0e85e925e9112cf234a2 2025-08-26T19:43:48.3308788Z * [new tag] trunk/089ad1d88bf31ddab769a4f87750b474ed1214c8 -> trunk/089ad1d88bf31ddab769a4f87750b474ed1214c8 2025-08-26T19:43:48.3309615Z * [new tag] trunk/0924304e728b9507a54eced28c812fbd5b13c397 -> trunk/0924304e728b9507a54eced28c812fbd5b13c397 2025-08-26T19:43:48.3311018Z * [new tag] trunk/0a5ab612dd2b9fc5bb2e1281ec7ca8730c5c3c89 -> trunk/0a5ab612dd2b9fc5bb2e1281ec7ca8730c5c3c89 2025-08-26T19:43:48.3311756Z * [new tag] trunk/0d19541284c38212235f78db24e3ac3ae4787e45 -> trunk/0d19541284c38212235f78db24e3ac3ae4787e45 2025-08-26T19:43:48.3312571Z * [new tag] trunk/0d9da384ef76e3ce2e7eaf951252ae9edb922863 -> trunk/0d9da384ef76e3ce2e7eaf951252ae9edb922863 2025-08-26T19:43:48.3313259Z * [new tag] trunk/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 -> trunk/0dea191ff7b844352dc2cd5e3b5ef5ea13a76756 2025-08-26T19:43:48.3314045Z * [new tag] trunk/0f801a510f5f185543388717241adb7237c3d46a -> trunk/0f801a510f5f185543388717241adb7237c3d46a 2025-08-26T19:43:48.3314831Z * [new tag] trunk/10e67f5ec3834da93fc2022caa7ac69cf97c01f0 -> trunk/10e67f5ec3834da93fc2022caa7ac69cf97c01f0 2025-08-26T19:43:48.3315678Z * [new tag] trunk/1113e7de30da95973c1eac7921601f9a0e94f2db -> trunk/1113e7de30da95973c1eac7921601f9a0e94f2db 2025-08-26T19:43:48.3316579Z * [new tag] trunk/117f11adb4b41a5485b570c4337c22ecc8e00aeb -> trunk/117f11adb4b41a5485b570c4337c22ecc8e00aeb 2025-08-26T19:43:48.3317359Z * [new tag] trunk/1471b20cb3fc502931ef12b1420414e32facd5b0 -> trunk/1471b20cb3fc502931ef12b1420414e32facd5b0 2025-08-26T19:43:48.3318622Z * [new tag] trunk/16e811e0b5073c7b42fe76f650ca2b79e339e053 -> trunk/16e811e0b5073c7b42fe76f650ca2b79e339e053 2025-08-26T19:43:48.3319495Z * [new tag] trunk/17b0263e86aec8aed068bb8b6744b129233e8084 -> trunk/17b0263e86aec8aed068bb8b6744b129233e8084 2025-08-26T19:43:48.3320203Z * [new tag] trunk/18271148d32da3d48897e9e7515de45066fce5bc -> trunk/18271148d32da3d48897e9e7515de45066fce5bc 2025-08-26T19:43:48.3321064Z * [new tag] trunk/19c70c2f3dc345a6555318f5f8b46cd55c42d0b4 -> trunk/19c70c2f3dc345a6555318f5f8b46cd55c42d0b4 2025-08-26T19:43:48.3321869Z * [new tag] trunk/1a566c4909ccf16ace1fbf1f65d90c995b362712 -> trunk/1a566c4909ccf16ace1fbf1f65d90c995b362712 2025-08-26T19:43:48.3322685Z * [new tag] trunk/1d458e294755ff2bfa314c67ddc5cb1dacc2aee8 -> trunk/1d458e294755ff2bfa314c67ddc5cb1dacc2aee8 2025-08-26T19:43:48.3323508Z * [new tag] trunk/1d46aa736fc8870dc88015c729a8c64470fa985c -> trunk/1d46aa736fc8870dc88015c729a8c64470fa985c 2025-08-26T19:43:48.3324414Z * [new tag] trunk/1de4540449ad6b9df8f452ab72da30ce8908af60 -> trunk/1de4540449ad6b9df8f452ab72da30ce8908af60 2025-08-26T19:43:48.3325199Z * [new tag] trunk/1e3fe78a104776cd708f150116348540346dae25 -> trunk/1e3fe78a104776cd708f150116348540346dae25 2025-08-26T19:43:48.3326025Z * [new tag] trunk/1ea918caf990c84bcb4e4ee5eee90f1102815b0a -> trunk/1ea918caf990c84bcb4e4ee5eee90f1102815b0a 2025-08-26T19:43:48.3326857Z * [new tag] trunk/1eccfb157ab9855b3f81872a23502fb15f455e0a -> trunk/1eccfb157ab9855b3f81872a23502fb15f455e0a 2025-08-26T19:43:48.3327651Z * [new tag] trunk/1fbe230b0d82251c6de8b5ae86c4da456b1db05c -> trunk/1fbe230b0d82251c6de8b5ae86c4da456b1db05c 2025-08-26T19:43:48.3328572Z * [new tag] trunk/209143ddeb99b0b075d16525088cee4893be7492 -> trunk/209143ddeb99b0b075d16525088cee4893be7492 2025-08-26T19:43:48.3329509Z * [new tag] trunk/22df59efc0a845b3ff37019029efd07c5a25c456 -> trunk/22df59efc0a845b3ff37019029efd07c5a25c456 2025-08-26T19:43:48.3330314Z * [new tag] trunk/23b033452fb1d4b404216279bbf5b6d06d8570c3 -> trunk/23b033452fb1d4b404216279bbf5b6d06d8570c3 2025-08-26T19:43:48.3331207Z * [new tag] trunk/24e7f3c21c9452c81d72bbd4b0c6b1f96f33536a -> trunk/24e7f3c21c9452c81d72bbd4b0c6b1f96f33536a 2025-08-26T19:43:48.3332063Z * [new tag] trunk/25df65afd8b5e2fffbcaf2b7ed63ef7a1e37ecb9 -> trunk/25df65afd8b5e2fffbcaf2b7ed63ef7a1e37ecb9 2025-08-26T19:43:48.3332848Z * [new tag] trunk/262640fd220236042fbf4443cc163c8838c84c3d -> trunk/262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:43:48.3333704Z * [new tag] trunk/266784ec6ae82f823abe406582e7a91f2ebb564a -> trunk/266784ec6ae82f823abe406582e7a91f2ebb564a 2025-08-26T19:43:48.3334396Z * [new tag] trunk/2835cc5e91eda8cbc4ac59de2ca990fa17107409 -> trunk/2835cc5e91eda8cbc4ac59de2ca990fa17107409 2025-08-26T19:43:48.3335164Z * [new tag] trunk/284b7190054686e68d9cc683b6ce43e45dd22338 -> trunk/284b7190054686e68d9cc683b6ce43e45dd22338 2025-08-26T19:43:48.3335995Z * [new tag] trunk/29afde20203ee6773641b4e3552942a37315316f -> trunk/29afde20203ee6773641b4e3552942a37315316f 2025-08-26T19:43:48.3336852Z * [new tag] trunk/2a7a7ad7116d930fde86cda02f668e624d26ec3e -> trunk/2a7a7ad7116d930fde86cda02f668e624d26ec3e 2025-08-26T19:43:48.3337921Z * [new tag] trunk/2b62ef74208792c7c4bf923f872e54b5f384efc8 -> trunk/2b62ef74208792c7c4bf923f872e54b5f384efc8 2025-08-26T19:43:48.3338912Z * [new tag] trunk/2beffb3311a41589021c121dac543994a7cbdff2 -> trunk/2beffb3311a41589021c121dac543994a7cbdff2 2025-08-26T19:43:48.3339667Z * [new tag] trunk/2c0650a00a0a0dd2bbf25ed22780fdd881bcda54 -> trunk/2c0650a00a0a0dd2bbf25ed22780fdd881bcda54 2025-08-26T19:43:48.3340508Z * [new tag] trunk/2cf69fe0e1bdb1413fe9e802c4b84d8958708421 -> trunk/2cf69fe0e1bdb1413fe9e802c4b84d8958708421 2025-08-26T19:43:48.3341350Z * [new tag] trunk/2cf7ac2fb7ab4067e17cc5ca71034b1c61a4fb10 -> trunk/2cf7ac2fb7ab4067e17cc5ca71034b1c61a4fb10 2025-08-26T19:43:48.3342282Z * [new tag] trunk/2f0cba934de7094a66c6ce68f5e937254f23142a -> trunk/2f0cba934de7094a66c6ce68f5e937254f23142a 2025-08-26T19:43:48.3342972Z * [new tag] trunk/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 -> trunk/2f0de0ff9361ca4f2b1e6f9edbc600b5fb6abcd6 2025-08-26T19:43:48.3343810Z * [new tag] trunk/2f50ae7d2022cb096c4156f5a207c291e36ddecf -> trunk/2f50ae7d2022cb096c4156f5a207c291e36ddecf 2025-08-26T19:43:48.3344677Z * [new tag] trunk/2fdd4f918cdc5fc8070e4c9c0d87b9045d316c06 -> trunk/2fdd4f918cdc5fc8070e4c9c0d87b9045d316c06 2025-08-26T19:43:48.3345519Z * [new tag] trunk/30384abcb1d181e774c0ac21b580aa34336a96c6 -> trunk/30384abcb1d181e774c0ac21b580aa34336a96c6 2025-08-26T19:43:48.3346643Z * [new tag] trunk/31a41daff49f2cde941d8b9e35cb2eaeeb606c0d -> trunk/31a41daff49f2cde941d8b9e35cb2eaeeb606c0d 2025-08-26T19:43:48.3347441Z * [new tag] trunk/332fa5b388521c05a19217649745c6edfdc2836d -> trunk/332fa5b388521c05a19217649745c6edfdc2836d 2025-08-26T19:43:48.3348419Z * [new tag] trunk/33346b58148c55592994a43385c321ae8c8808f2 -> trunk/33346b58148c55592994a43385c321ae8c8808f2 2025-08-26T19:43:48.3349324Z * [new tag] trunk/3373b074f5ea5277974fa6e945544fdfb16bb446 -> trunk/3373b074f5ea5277974fa6e945544fdfb16bb446 2025-08-26T19:43:48.3350148Z * [new tag] trunk/33c3794533844236a6e30ba377e0a6802b279fc8 -> trunk/33c3794533844236a6e30ba377e0a6802b279fc8 2025-08-26T19:43:48.3350959Z * [new tag] trunk/35e4d97e047bff8b38fee1dcf6ef6503f0fc9208 -> trunk/35e4d97e047bff8b38fee1dcf6ef6503f0fc9208 2025-08-26T19:43:48.3351797Z * [new tag] trunk/36ac916929ca67b533cc45932970297e9824324e -> trunk/36ac916929ca67b533cc45932970297e9824324e 2025-08-26T19:43:48.3352688Z * [new tag] trunk/371909cfd10e0da1bab1e12fb54a2403c37c5f76 -> trunk/371909cfd10e0da1bab1e12fb54a2403c37c5f76 2025-08-26T19:43:48.3353507Z * [new tag] trunk/373e25c2eb9f882356a9c7a2f18020935ff1d78b -> trunk/373e25c2eb9f882356a9c7a2f18020935ff1d78b 2025-08-26T19:43:48.3354314Z * [new tag] trunk/37a34022b59a6ff2757e5cec0fdc72278418f339 -> trunk/37a34022b59a6ff2757e5cec0fdc72278418f339 2025-08-26T19:43:48.3355126Z * [new tag] trunk/38a492d40d7ebb2856cb120df337c6cdac244528 -> trunk/38a492d40d7ebb2856cb120df337c6cdac244528 2025-08-26T19:43:48.3356056Z * [new tag] trunk/394728bab2de21e8002fc6a47aa4d3acb2d7a728 -> trunk/394728bab2de21e8002fc6a47aa4d3acb2d7a728 2025-08-26T19:43:48.3356865Z * [new tag] trunk/39862acb2e320783245d2a03acfd1b14cae28038 -> trunk/39862acb2e320783245d2a03acfd1b14cae28038 2025-08-26T19:43:48.3357755Z * [new tag] trunk/3a4140bf8e783db3f0094d2a2ce1d8534066432f -> trunk/3a4140bf8e783db3f0094d2a2ce1d8534066432f 2025-08-26T19:43:48.3358571Z * [new tag] trunk/3caddd4daa5b1a167663c07219e065e86247ad76 -> trunk/3caddd4daa5b1a167663c07219e065e86247ad76 2025-08-26T19:43:48.3359426Z * [new tag] trunk/3dacaf0e1eb3286e70bf8d572000ecebf2c1f4c9 -> trunk/3dacaf0e1eb3286e70bf8d572000ecebf2c1f4c9 2025-08-26T19:43:48.3360222Z * [new tag] trunk/3e210f90c2cbd5817aa23d430da10cad200a3ffa -> trunk/3e210f90c2cbd5817aa23d430da10cad200a3ffa 2025-08-26T19:43:48.3361027Z * [new tag] trunk/3e3e83418d0f6b1495f79380f3a3dbc8b2d23062 -> trunk/3e3e83418d0f6b1495f79380f3a3dbc8b2d23062 2025-08-26T19:43:48.3361598Z * [new tag] trunk/3e5b021f217a42ae55dc690083f67a28126808ed -> trunk/3e5b021f217a42ae55dc690083f67a28126808ed 2025-08-26T19:43:48.3362435Z * [new tag] trunk/3ea6cc8c2d443d6104159d50e8328c144f6caa39 -> trunk/3ea6cc8c2d443d6104159d50e8328c144f6caa39 2025-08-26T19:43:48.3363364Z * [new tag] trunk/3f1a97a99cad4cc682b20b43c1178ed9e1b81f24 -> trunk/3f1a97a99cad4cc682b20b43c1178ed9e1b81f24 2025-08-26T19:43:48.3364195Z * [new tag] trunk/3f5a8e2003f2234ca8be19fdc307ba7b995f9be3 -> trunk/3f5a8e2003f2234ca8be19fdc307ba7b995f9be3 2025-08-26T19:43:48.3365545Z * [new tag] trunk/40c0e700a488191cd8f541b30d8e3b9f2c0bc759 -> trunk/40c0e700a488191cd8f541b30d8e3b9f2c0bc759 2025-08-26T19:43:48.3366304Z * [new tag] trunk/419a2dbf5f69cee52382090200b532a81da92c69 -> trunk/419a2dbf5f69cee52382090200b532a81da92c69 2025-08-26T19:43:48.3367173Z * [new tag] trunk/431846a6323c6f1d02da49e311ac694324f386f4 -> trunk/431846a6323c6f1d02da49e311ac694324f386f4 2025-08-26T19:43:48.3368011Z * [new tag] trunk/44549c7146bd6c4166f97e856037babe1b7f4f49 -> trunk/44549c7146bd6c4166f97e856037babe1b7f4f49 2025-08-26T19:43:48.3369020Z * [new tag] trunk/447d34b5f80fb7350f79decd855cb599cab39083 -> trunk/447d34b5f80fb7350f79decd855cb599cab39083 2025-08-26T19:43:48.3370001Z * [new tag] trunk/46429be72323c1807a785234164bd91011f68d08 -> trunk/46429be72323c1807a785234164bd91011f68d08 2025-08-26T19:43:48.3370680Z * [new tag] trunk/4651aaac47ff855e08a74e2fdbfa605bc53afba8 -> trunk/4651aaac47ff855e08a74e2fdbfa605bc53afba8 2025-08-26T19:43:48.3371523Z * [new tag] trunk/47d267364cad407b5612bf4a5faa160d2f4a7121 -> trunk/47d267364cad407b5612bf4a5faa160d2f4a7121 2025-08-26T19:43:48.3372437Z * [new tag] trunk/49ff884b1edc3b872eeb2387ec60ef230cae7f24 -> trunk/49ff884b1edc3b872eeb2387ec60ef230cae7f24 2025-08-26T19:43:48.3373264Z * [new tag] trunk/4a1aca11c20cfa29a1513b9f289d75bfe32d05d4 -> trunk/4a1aca11c20cfa29a1513b9f289d75bfe32d05d4 2025-08-26T19:43:48.3374086Z * [new tag] trunk/4acdbb8311f760513556e2e4fdd7bfd88c225e52 -> trunk/4acdbb8311f760513556e2e4fdd7bfd88c225e52 2025-08-26T19:43:48.3374879Z * [new tag] trunk/4c36c8a99463c898190a462300ba7f05b5b3384e -> trunk/4c36c8a99463c898190a462300ba7f05b5b3384e 2025-08-26T19:43:48.3375706Z * [new tag] trunk/4e19c1906a830714c1d9d71361357ce616a034d6 -> trunk/4e19c1906a830714c1d9d71361357ce616a034d6 2025-08-26T19:43:48.3376538Z * [new tag] trunk/4ed3184dee1bf4f775839bfd1448a7a34fe5a898 -> trunk/4ed3184dee1bf4f775839bfd1448a7a34fe5a898 2025-08-26T19:43:48.3377385Z * [new tag] trunk/50cfe76231768ee2c784f68a1eba03369f386019 -> trunk/50cfe76231768ee2c784f68a1eba03369f386019 2025-08-26T19:43:48.3378233Z * [new tag] trunk/510825e5fed8b56eb5e9352c12f0df1feeadb810 -> trunk/510825e5fed8b56eb5e9352c12f0df1feeadb810 2025-08-26T19:43:48.3379074Z * [new tag] trunk/512fc768e94c937df350911aaa4ebce757d1f9df -> trunk/512fc768e94c937df350911aaa4ebce757d1f9df 2025-08-26T19:43:48.3380399Z * [new tag] trunk/517d38d3406abbba35d0694bff259a698cad3ec9 -> trunk/517d38d3406abbba35d0694bff259a698cad3ec9 2025-08-26T19:43:48.3381192Z * [new tag] trunk/5255e65c01bf48bbcd916ecf16ed81cf28d3c6e2 -> trunk/5255e65c01bf48bbcd916ecf16ed81cf28d3c6e2 2025-08-26T19:43:48.3382064Z * [new tag] trunk/543896fcf3312f2053018edf9ee74c0fbb1d28ed -> trunk/543896fcf3312f2053018edf9ee74c0fbb1d28ed 2025-08-26T19:43:48.3382951Z * [new tag] trunk/54c2b66592d168e4a7525f7a58f8ca020517a9cb -> trunk/54c2b66592d168e4a7525f7a58f8ca020517a9cb 2025-08-26T19:43:48.3383621Z * [new tag] trunk/54cc63b467f24242cf0d6538d3e1df39e553daf1 -> trunk/54cc63b467f24242cf0d6538d3e1df39e553daf1 2025-08-26T19:43:48.3384514Z * [new tag] trunk/56ebed627a23eea36190e1ced5024a18ffcedbd7 -> trunk/56ebed627a23eea36190e1ced5024a18ffcedbd7 2025-08-26T19:43:48.3385429Z * [new tag] trunk/576a0e64ed2470abd2c430205d1984a11951ce05 -> trunk/576a0e64ed2470abd2c430205d1984a11951ce05 2025-08-26T19:43:48.3386220Z * [new tag] trunk/5805c4210b477f0a7315d6038078dc4a8be1c8fa -> trunk/5805c4210b477f0a7315d6038078dc4a8be1c8fa 2025-08-26T19:43:48.3387125Z * [new tag] trunk/58f9a3dd6391397e439c5f5075837e8f983735aa -> trunk/58f9a3dd6391397e439c5f5075837e8f983735aa 2025-08-26T19:43:48.3387939Z * [new tag] trunk/595987d28d4c8aee68de83734af919c7710ad58b -> trunk/595987d28d4c8aee68de83734af919c7710ad58b 2025-08-26T19:43:48.3388821Z * [new tag] trunk/599f639ddb8bb45abb2dc305542f38288427183d -> trunk/599f639ddb8bb45abb2dc305542f38288427183d 2025-08-26T19:43:48.3389690Z * [new tag] trunk/5afa4187dfe1e99278f8e372ec09102d5b937572 -> trunk/5afa4187dfe1e99278f8e372ec09102d5b937572 2025-08-26T19:43:48.3390532Z * [new tag] trunk/5d9653d90ee003173dd03f93e09fed236500ef06 -> trunk/5d9653d90ee003173dd03f93e09fed236500ef06 2025-08-26T19:43:48.3391383Z * [new tag] trunk/5dad5b4f57ade4001c0f421dbdad2e418304870e -> trunk/5dad5b4f57ade4001c0f421dbdad2e418304870e 2025-08-26T19:43:48.3392353Z * [new tag] trunk/5ee464db5c4293ac09521f9069fa7d2106680a7f -> trunk/5ee464db5c4293ac09521f9069fa7d2106680a7f 2025-08-26T19:43:48.3393145Z * [new tag] trunk/6096d277c543f5dd40351431ef9a8d556134c74d -> trunk/6096d277c543f5dd40351431ef9a8d556134c74d 2025-08-26T19:43:48.3393971Z * [new tag] trunk/62db8ec39116544ae247f876b3e06753178db49b -> trunk/62db8ec39116544ae247f876b3e06753178db49b 2025-08-26T19:43:48.3394777Z * [new tag] trunk/639b8cc51ddebf10361f3840a6b0a244eb6092a1 -> trunk/639b8cc51ddebf10361f3840a6b0a244eb6092a1 2025-08-26T19:43:48.3395656Z * [new tag] trunk/6443ea337df843681bc558d99efa84a3e5559b7f -> trunk/6443ea337df843681bc558d99efa84a3e5559b7f 2025-08-26T19:43:48.3396565Z * [new tag] trunk/6598f00c18dfcc4fc50427305b6b5724e617246f -> trunk/6598f00c18dfcc4fc50427305b6b5724e617246f 2025-08-26T19:43:48.3397473Z * [new tag] trunk/65d21dae18a34e8bd1b2f0e5aec7144b9dd33611 -> trunk/65d21dae18a34e8bd1b2f0e5aec7144b9dd33611 2025-08-26T19:43:48.3398302Z * [new tag] trunk/660b5656a436dcccb0275ea5421d3eb4f1157b43 -> trunk/660b5656a436dcccb0275ea5421d3eb4f1157b43 2025-08-26T19:43:48.3399233Z * [new tag] trunk/66166cf1e7696bf25f6f7bb815a93df367db48dc -> trunk/66166cf1e7696bf25f6f7bb815a93df367db48dc 2025-08-26T19:43:48.3400077Z * [new tag] trunk/667245dc60242a35ae0a6b0072628eb8e15a6d03 -> trunk/667245dc60242a35ae0a6b0072628eb8e15a6d03 2025-08-26T19:43:48.3400877Z * [new tag] trunk/67b98da1b262317f9c0375d64a4b467c82712548 -> trunk/67b98da1b262317f9c0375d64a4b467c82712548 2025-08-26T19:43:48.3401736Z * [new tag] trunk/67d31f6b281d3b15b205756fc7ebc450cdde1dab -> trunk/67d31f6b281d3b15b205756fc7ebc450cdde1dab 2025-08-26T19:43:48.3402588Z * [new tag] trunk/67fc16c7447f4fc04e7d28bfe201a4a0c78f3ea4 -> trunk/67fc16c7447f4fc04e7d28bfe201a4a0c78f3ea4 2025-08-26T19:43:48.3403498Z * [new tag] trunk/6aef9f3a6906c011a57541c1de7a246222bc9ac9 -> trunk/6aef9f3a6906c011a57541c1de7a246222bc9ac9 2025-08-26T19:43:48.3404182Z * [new tag] trunk/6ea4be1e2eca952ea66090182bd2eede89799a45 -> trunk/6ea4be1e2eca952ea66090182bd2eede89799a45 2025-08-26T19:43:48.3405021Z * [new tag] trunk/7006fd0c8874cb0228d3f2bfd83a989bde4b7021 -> trunk/7006fd0c8874cb0228d3f2bfd83a989bde4b7021 2025-08-26T19:43:48.3405824Z * [new tag] trunk/710514a2a51facaba445d2c188541d778f9fdb59 -> trunk/710514a2a51facaba445d2c188541d778f9fdb59 2025-08-26T19:43:48.3406771Z * [new tag] trunk/7131bfab89c46ffe31b61ea4937a8727e9cf33c1 -> trunk/7131bfab89c46ffe31b61ea4937a8727e9cf33c1 2025-08-26T19:43:48.3407560Z * [new tag] trunk/726dce3c944cbda16e54d3b15cdb4b6ced05af72 -> trunk/726dce3c944cbda16e54d3b15cdb4b6ced05af72 2025-08-26T19:43:48.3408346Z * [new tag] trunk/72e4786d1635681b8d053d0168c7d16b980e5124 -> trunk/72e4786d1635681b8d053d0168c7d16b980e5124 2025-08-26T19:43:48.3409257Z * [new tag] trunk/7376111d59f3170c2814d565c09d09435189692a -> trunk/7376111d59f3170c2814d565c09d09435189692a 2025-08-26T19:43:48.3410274Z * [new tag] trunk/74124d1b46774f2a73aa1aadc2b0874cb523b1c1 -> trunk/74124d1b46774f2a73aa1aadc2b0874cb523b1c1 2025-08-26T19:43:48.3411786Z * [new tag] trunk/74280d091321343b47a2975e17584b973d7c22c4 -> trunk/74280d091321343b47a2975e17584b973d7c22c4 2025-08-26T19:43:48.3412544Z * [new tag] trunk/74c4c758afa8c28162f00a456c185552e1159fd3 -> trunk/74c4c758afa8c28162f00a456c185552e1159fd3 2025-08-26T19:43:48.3413279Z * [new tag] trunk/763053dc536341997641e920d8887b3010901b3b -> trunk/763053dc536341997641e920d8887b3010901b3b 2025-08-26T19:43:48.3414119Z * [new tag] trunk/774b4befa18741b3115802cae71000168a40c384 -> trunk/774b4befa18741b3115802cae71000168a40c384 2025-08-26T19:43:48.3414827Z * [new tag] trunk/77bc959fe122bfd131e339ca36cab445a1860806 -> trunk/77bc959fe122bfd131e339ca36cab445a1860806 2025-08-26T19:43:48.3415679Z * [new tag] trunk/78a8e6a671c5631bc0e89b0e674790a424540547 -> trunk/78a8e6a671c5631bc0e89b0e674790a424540547 2025-08-26T19:43:48.3416517Z * [new tag] trunk/7e4bfa74eafab994b01f8b5501d4d061cbf64808 -> trunk/7e4bfa74eafab994b01f8b5501d4d061cbf64808 2025-08-26T19:43:48.3417430Z * [new tag] trunk/7e6ce41555d595e3fa0d91059491f21cee3eb5ea -> trunk/7e6ce41555d595e3fa0d91059491f21cee3eb5ea 2025-08-26T19:43:48.3418256Z * [new tag] trunk/7f201baf414301b3312576893b7f6f2698acd9ba -> trunk/7f201baf414301b3312576893b7f6f2698acd9ba 2025-08-26T19:43:48.3419147Z * [new tag] trunk/7fcdd8d6afeda6a4c8630816e12bf7cca44b8f8a -> trunk/7fcdd8d6afeda6a4c8630816e12bf7cca44b8f8a 2025-08-26T19:43:48.3420064Z * [new tag] trunk/801851086d09506d081800108c9e214edb3f5b7d -> trunk/801851086d09506d081800108c9e214edb3f5b7d 2025-08-26T19:43:48.3421476Z * [new tag] trunk/8047cde0f3a27f3afa218792b8464d5e0c9d942f -> trunk/8047cde0f3a27f3afa218792b8464d5e0c9d942f 2025-08-26T19:43:48.3422248Z * [new tag] trunk/80df27a612be3433516d7e6dfc8d8be058425d3e -> trunk/80df27a612be3433516d7e6dfc8d8be058425d3e 2025-08-26T19:43:48.3423240Z * [new tag] trunk/818ba434c7de4cd604184b2857d544e0ad95735f -> trunk/818ba434c7de4cd604184b2857d544e0ad95735f 2025-08-26T19:43:48.3424067Z * [new tag] trunk/83283ce7f5a7847b4e561e22be9b0f4530b05527 -> trunk/83283ce7f5a7847b4e561e22be9b0f4530b05527 2025-08-26T19:43:48.3424927Z * [new tag] trunk/85adf80cf15538a7e010fa235036fe8e06f8bede -> trunk/85adf80cf15538a7e010fa235036fe8e06f8bede 2025-08-26T19:43:48.3425940Z * [new tag] trunk/8aad3a60ce16a4acab17a8e46e5df339db2ff740 -> trunk/8aad3a60ce16a4acab17a8e46e5df339db2ff740 2025-08-26T19:43:48.3427078Z * [new tag] trunk/8c442e4fd3310e15f57770944f883ac1d73e77e2 -> trunk/8c442e4fd3310e15f57770944f883ac1d73e77e2 2025-08-26T19:43:48.3427814Z * [new tag] trunk/8c506e6310b9b5295151fb725be479d0f80ce5e8 -> trunk/8c506e6310b9b5295151fb725be479d0f80ce5e8 2025-08-26T19:43:48.3428979Z * [new tag] trunk/8cfc119491f533c4edded4263a78eb0af782a2d5 -> trunk/8cfc119491f533c4edded4263a78eb0af782a2d5 2025-08-26T19:43:48.3429892Z * [new tag] trunk/8dbe7f99bd707ee28ae12ecb9cab54e1785bf13e -> trunk/8dbe7f99bd707ee28ae12ecb9cab54e1785bf13e 2025-08-26T19:43:48.3430692Z * [new tag] trunk/8e1770905565cd67d6c3a91c7afa462f4ef6e6aa -> trunk/8e1770905565cd67d6c3a91c7afa462f4ef6e6aa 2025-08-26T19:43:48.3431626Z * [new tag] trunk/8f31aa97a3e1e17bed29b6cedf9884f0c6b145e9 -> trunk/8f31aa97a3e1e17bed29b6cedf9884f0c6b145e9 2025-08-26T19:43:48.3432323Z * [new tag] trunk/8f766d68397736053883aa281cae0eb46bb233bb -> trunk/8f766d68397736053883aa281cae0eb46bb233bb 2025-08-26T19:43:48.3433198Z * [new tag] trunk/908b0ccb1f70ed2cfa830484e05ee32af13b1836 -> trunk/908b0ccb1f70ed2cfa830484e05ee32af13b1836 2025-08-26T19:43:48.3434102Z * [new tag] trunk/90ea9ccefe3e2d9a9e4840016d1af10c1814d48b -> trunk/90ea9ccefe3e2d9a9e4840016d1af10c1814d48b 2025-08-26T19:43:48.3434954Z * [new tag] trunk/9225c6199412f8a2ee99b7c29f533fb98b9ff62e -> trunk/9225c6199412f8a2ee99b7c29f533fb98b9ff62e 2025-08-26T19:43:48.3435812Z * [new tag] trunk/923bc46122d173a7964c646311a3bea3cd8dd561 -> trunk/923bc46122d173a7964c646311a3bea3cd8dd561 2025-08-26T19:43:48.3436796Z * [new tag] trunk/92ab18482459a63e97f1374e27e8411964da9762 -> trunk/92ab18482459a63e97f1374e27e8411964da9762 2025-08-26T19:43:48.3439504Z * [new tag] trunk/94b9569c4a86e12b944ca66e3125357a14d0eb9e -> trunk/94b9569c4a86e12b944ca66e3125357a14d0eb9e 2025-08-26T19:43:48.3439919Z * [new tag] trunk/957b170d8efe2a51147e0cdb7515acc345ba81da -> trunk/957b170d8efe2a51147e0cdb7515acc345ba81da 2025-08-26T19:43:48.3440331Z * [new tag] trunk/958f9ca88e9a1580de7c94a5a2ca8a750b1335ae -> trunk/958f9ca88e9a1580de7c94a5a2ca8a750b1335ae 2025-08-26T19:43:48.3440733Z * [new tag] trunk/96682103026b5ea27f19e6db9303e17572095b0e -> trunk/96682103026b5ea27f19e6db9303e17572095b0e 2025-08-26T19:43:48.3441379Z * [new tag] trunk/97200c971110d54030feaad999698c7341f8acc7 -> trunk/97200c971110d54030feaad999698c7341f8acc7 2025-08-26T19:43:48.3442019Z * [new tag] trunk/981ac533c6e69a77538aaa7a9747c3d840dfa8be -> trunk/981ac533c6e69a77538aaa7a9747c3d840dfa8be 2025-08-26T19:43:48.3442949Z * [new tag] trunk/995397d47a0e27394ee1010f158e181eb304100a -> trunk/995397d47a0e27394ee1010f158e181eb304100a 2025-08-26T19:43:48.3443898Z * [new tag] trunk/9a41570199155eee92ebd28452a556075e34e1b4 -> trunk/9a41570199155eee92ebd28452a556075e34e1b4 2025-08-26T19:43:48.3444866Z * [new tag] trunk/9b3ebd25acfd2ff4e9b7428079ba364d6f8a14da -> trunk/9b3ebd25acfd2ff4e9b7428079ba364d6f8a14da 2025-08-26T19:43:48.3445729Z * [new tag] trunk/9b4adc4db7494dbc4dbbac5dd85ccbf5babaef44 -> trunk/9b4adc4db7494dbc4dbbac5dd85ccbf5babaef44 2025-08-26T19:43:48.3447077Z * [new tag] trunk/9d18bf01b1661d227f6af41ac07a1e9ef20a9e1a -> trunk/9d18bf01b1661d227f6af41ac07a1e9ef20a9e1a 2025-08-26T19:43:48.3447889Z * [new tag] trunk/9d7cecdd6c44c5421d341bcc359be4097ea9a2f5 -> trunk/9d7cecdd6c44c5421d341bcc359be4097ea9a2f5 2025-08-26T19:43:48.3448851Z * [new tag] trunk/9d882fd9ffc6ad2a292fee548740aabfea745002 -> trunk/9d882fd9ffc6ad2a292fee548740aabfea745002 2025-08-26T19:43:48.3449860Z * [new tag] trunk/9d9cc9897ac44a1a8df38211b03d8342a8af48c3 -> trunk/9d9cc9897ac44a1a8df38211b03d8342a8af48c3 2025-08-26T19:43:48.3450707Z * [new tag] trunk/9e1c9541344b2aa1c946edb779d275072f3b8f4a -> trunk/9e1c9541344b2aa1c946edb779d275072f3b8f4a 2025-08-26T19:43:48.3451553Z * [new tag] trunk/9e491f753ee521a70e6a7e7dbb36f96c9350f5ea -> trunk/9e491f753ee521a70e6a7e7dbb36f96c9350f5ea 2025-08-26T19:43:48.3452401Z * [new tag] trunk/a03cc53e6f6e2fe67316cb8c74c25f5b953f445b -> trunk/a03cc53e6f6e2fe67316cb8c74c25f5b953f445b 2025-08-26T19:43:48.3453235Z * [new tag] trunk/a154c2093c0f2646346f032e1f30012779b3c51d -> trunk/a154c2093c0f2646346f032e1f30012779b3c51d 2025-08-26T19:43:48.3454157Z * [new tag] trunk/a391fa1c42dd32e32a2e5b1cb196bac56daaca88 -> trunk/a391fa1c42dd32e32a2e5b1cb196bac56daaca88 2025-08-26T19:43:48.3455425Z * [new tag] trunk/a3a82e3da85a53afc4bbf3d75bd3d3dcc2e06645 -> trunk/a3a82e3da85a53afc4bbf3d75bd3d3dcc2e06645 2025-08-26T19:43:48.3456065Z * [new tag] trunk/a3fe1ced409d186628ff2975f05ba529a86fae84 -> trunk/a3fe1ced409d186628ff2975f05ba529a86fae84 2025-08-26T19:43:48.3456909Z * [new tag] trunk/a43480d19cdd68e544163b1a07c328a9c54723b8 -> trunk/a43480d19cdd68e544163b1a07c328a9c54723b8 2025-08-26T19:43:48.3457740Z * [new tag] trunk/a445b41e4f11daa82a53a21ec413c15d5079ae77 -> trunk/a445b41e4f11daa82a53a21ec413c15d5079ae77 2025-08-26T19:43:48.3458644Z * [new tag] trunk/a44a0d3671b4ccf2fe915896a8a5204fe79b1e7b -> trunk/a44a0d3671b4ccf2fe915896a8a5204fe79b1e7b 2025-08-26T19:43:48.3459476Z * [new tag] trunk/a6401cb5aa51622045c3f9a03b2cebef236e4182 -> trunk/a6401cb5aa51622045c3f9a03b2cebef236e4182 2025-08-26T19:43:48.3460373Z * [new tag] trunk/a68f63e33161b4665e0f4c399bf8072135a35a57 -> trunk/a68f63e33161b4665e0f4c399bf8072135a35a57 2025-08-26T19:43:48.3461230Z * [new tag] trunk/a72803f1e3c69c780b7d7bcdd9b35360fd98148b -> trunk/a72803f1e3c69c780b7d7bcdd9b35360fd98148b 2025-08-26T19:43:48.3462130Z * [new tag] trunk/a7b5955ea8851d73e35f50a0de5bb0626bae24cb -> trunk/a7b5955ea8851d73e35f50a0de5bb0626bae24cb 2025-08-26T19:43:48.3462967Z * [new tag] trunk/a818fa77e3a72271f144514ef349c5a666313205 -> trunk/a818fa77e3a72271f144514ef349c5a666313205 2025-08-26T19:43:48.3463893Z * [new tag] trunk/a825557ed53507e85ac613862311a81eb88710a4 -> trunk/a825557ed53507e85ac613862311a81eb88710a4 2025-08-26T19:43:48.3464624Z * [new tag] trunk/a85711d565f37b0095af9f7dafa77f392c9aa31e -> trunk/a85711d565f37b0095af9f7dafa77f392c9aa31e 2025-08-26T19:43:48.3465573Z * [new tag] trunk/a941d7ffe54b5f256c1fbd3959ddbf608b7eea88 -> trunk/a941d7ffe54b5f256c1fbd3959ddbf608b7eea88 2025-08-26T19:43:48.3466452Z * [new tag] trunk/a9fabeb012a4b804836a2b8d4b3742b92c9a6b58 -> trunk/a9fabeb012a4b804836a2b8d4b3742b92c9a6b58 2025-08-26T19:43:48.3467303Z * [new tag] trunk/ab7787fb82dd777b2f777ef58bc20dbb7bd8289b -> trunk/ab7787fb82dd777b2f777ef58bc20dbb7bd8289b 2025-08-26T19:43:48.3468159Z * [new tag] trunk/ab8d60f4c86ca19ed00d6e79ae8e6939266f28e6 -> trunk/ab8d60f4c86ca19ed00d6e79ae8e6939266f28e6 2025-08-26T19:43:48.3468937Z * [new tag] trunk/ac8d9418aee4543fa193c86ae0bc3e63707bcd3b -> trunk/ac8d9418aee4543fa193c86ae0bc3e63707bcd3b 2025-08-26T19:43:48.3469843Z * [new tag] trunk/acb00d3ccf5f2d566225f07ed66bd579d5d3e44e -> trunk/acb00d3ccf5f2d566225f07ed66bd579d5d3e44e 2025-08-26T19:43:48.3470686Z * [new tag] trunk/adecb0c9e89e0dfe18d944d292c98c97b686fc83 -> trunk/adecb0c9e89e0dfe18d944d292c98c97b686fc83 2025-08-26T19:43:48.3471626Z * [new tag] trunk/ae8d319fd4a0b0fa7b1372aa07690a36ce823abc -> trunk/ae8d319fd4a0b0fa7b1372aa07690a36ce823abc 2025-08-26T19:43:48.3472514Z * [new tag] trunk/af3265d20f763e5366bfa37e3d4a6307036d0c18 -> trunk/af3265d20f763e5366bfa37e3d4a6307036d0c18 2025-08-26T19:43:48.3473448Z * [new tag] trunk/b0420d24386263f2727fd5714b63cfa6bc89f3e6 -> trunk/b0420d24386263f2727fd5714b63cfa6bc89f3e6 2025-08-26T19:43:48.3474303Z * [new tag] trunk/b1380f434da2fa2de0e5ff6fd70f73082dc08687 -> trunk/b1380f434da2fa2de0e5ff6fd70f73082dc08687 2025-08-26T19:43:48.3475181Z * [new tag] trunk/b2632e79828300302fd11e093d765196c3c0db58 -> trunk/b2632e79828300302fd11e093d765196c3c0db58 2025-08-26T19:43:48.3476088Z * [new tag] trunk/b2e06e0194c3fa8f7578a1b48751cc027394fb67 -> trunk/b2e06e0194c3fa8f7578a1b48751cc027394fb67 2025-08-26T19:43:48.3476941Z * [new tag] trunk/b3e215b864e6ca43b2c4e50ce666673f80feee27 -> trunk/b3e215b864e6ca43b2c4e50ce666673f80feee27 2025-08-26T19:43:48.3477784Z * [new tag] trunk/b708966201811b31ee765ec57715ac21d06ef652 -> trunk/b708966201811b31ee765ec57715ac21d06ef652 2025-08-26T19:43:48.3479101Z * [new tag] trunk/b9e9e92817fd7d1a778f074105603efb07e05004 -> trunk/b9e9e92817fd7d1a778f074105603efb07e05004 2025-08-26T19:43:48.3479704Z * [new tag] trunk/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 -> trunk/bc7eaa0d8a1f5ca8ec0eaac461d1df500dcaea84 2025-08-26T19:43:48.3480527Z * [new tag] trunk/bcfe1b2d714cbb2716495e09ae010e7c34daf045 -> trunk/bcfe1b2d714cbb2716495e09ae010e7c34daf045 2025-08-26T19:43:48.3481406Z * [new tag] trunk/bd5857a1d6d5455d4f0057c182dff5e8ad2a4c8a -> trunk/bd5857a1d6d5455d4f0057c182dff5e8ad2a4c8a 2025-08-26T19:43:48.3482334Z * [new tag] trunk/be2e6b3158552405acc13ef7829a0217826fb271 -> trunk/be2e6b3158552405acc13ef7829a0217826fb271 2025-08-26T19:43:48.3483289Z * [new tag] trunk/be87f22dfba4488963fcc854699829e2782ee0f2 -> trunk/be87f22dfba4488963fcc854699829e2782ee0f2 2025-08-26T19:43:48.3484154Z * [new tag] trunk/becd6cd744bdf950578519437652a0d1f4b48781 -> trunk/becd6cd744bdf950578519437652a0d1f4b48781 2025-08-26T19:43:48.3485359Z * [new tag] trunk/bf8431ba062efa9ff0cdd5032a3ddf2e007a3216 -> trunk/bf8431ba062efa9ff0cdd5032a3ddf2e007a3216 2025-08-26T19:43:48.3486103Z * [new tag] trunk/c02e26bf31eb3da301158a061aa68527dbfb4d32 -> trunk/c02e26bf31eb3da301158a061aa68527dbfb4d32 2025-08-26T19:43:48.3486993Z * [new tag] trunk/c081481bbebdb568d07ee19cfe2cd3125de6cba7 -> trunk/c081481bbebdb568d07ee19cfe2cd3125de6cba7 2025-08-26T19:43:48.3487846Z * [new tag] trunk/c2390087c34c964ef648addf43efb8c6a34e30c2 -> trunk/c2390087c34c964ef648addf43efb8c6a34e30c2 2025-08-26T19:43:48.3488736Z * [new tag] trunk/c4670e40c9b741d50a79b714e3830149833be908 -> trunk/c4670e40c9b741d50a79b714e3830149833be908 2025-08-26T19:43:48.3489698Z * [new tag] trunk/c5cb255625deb4cdbc5780e6911b73498e17ed5a -> trunk/c5cb255625deb4cdbc5780e6911b73498e17ed5a 2025-08-26T19:43:48.3490614Z * [new tag] trunk/c60dea5261d9648d1da51528a07731966bb6823e -> trunk/c60dea5261d9648d1da51528a07731966bb6823e 2025-08-26T19:43:48.3491472Z * [new tag] trunk/c74e5f60611b7eac4321f53a9e4a15b077fb1bcc -> trunk/c74e5f60611b7eac4321f53a9e4a15b077fb1bcc 2025-08-26T19:43:48.3492235Z * [new tag] trunk/c7a77470c54b28e555319e34048af14d1d66198a -> trunk/c7a77470c54b28e555319e34048af14d1d66198a 2025-08-26T19:43:48.3493076Z * [new tag] trunk/c7fb031706330684fc3a2d8d169bebea874d4e95 -> trunk/c7fb031706330684fc3a2d8d169bebea874d4e95 2025-08-26T19:43:48.3493960Z * [new tag] trunk/c8bb0e4720ddddf3cd1b0b48b336978f763c71ca -> trunk/c8bb0e4720ddddf3cd1b0b48b336978f763c71ca 2025-08-26T19:43:48.3494854Z * [new tag] trunk/ca9fe0107e165a4a4147325ff6d34235ebde447f -> trunk/ca9fe0107e165a4a4147325ff6d34235ebde447f 2025-08-26T19:43:48.3495670Z * [new tag] trunk/cb579532150c9e87e7c143adcb020fb7de7cc6b1 -> trunk/cb579532150c9e87e7c143adcb020fb7de7cc6b1 2025-08-26T19:43:48.3496414Z * [new tag] trunk/cc2b65a91ae7773d4ecf9a600dda48fc3e69aa8f -> trunk/cc2b65a91ae7773d4ecf9a600dda48fc3e69aa8f 2025-08-26T19:43:48.3497299Z * [new tag] trunk/cc791d5857f4aa06b8d4e567b1fb2852e3ae963d -> trunk/cc791d5857f4aa06b8d4e567b1fb2852e3ae963d 2025-08-26T19:43:48.3498232Z * [new tag] trunk/cd31be28ec5cd0c4d9cdb6742efe151eee1406ec -> trunk/cd31be28ec5cd0c4d9cdb6742efe151eee1406ec 2025-08-26T19:43:48.3499077Z * [new tag] trunk/cd87f3029582cedb3b88747a3bd7d200b05c1138 -> trunk/cd87f3029582cedb3b88747a3bd7d200b05c1138 2025-08-26T19:43:48.3500037Z * [new tag] trunk/ce048de608180fa88335e5821070472539968b54 -> trunk/ce048de608180fa88335e5821070472539968b54 2025-08-26T19:43:48.3500925Z * [new tag] trunk/ce467df5d1d763d1648aee51c93ce3e9a4699936 -> trunk/ce467df5d1d763d1648aee51c93ce3e9a4699936 2025-08-26T19:43:48.3501876Z * [new tag] trunk/cee72119b2dec7776bc2550dd39a9b1349772751 -> trunk/cee72119b2dec7776bc2550dd39a9b1349772751 2025-08-26T19:43:48.3502858Z * [new tag] trunk/cf94cadbeee31a4d1d46a57f11bce7c9fd1cebc0 -> trunk/cf94cadbeee31a4d1d46a57f11bce7c9fd1cebc0 2025-08-26T19:43:48.3503802Z * [new tag] trunk/cfdaaaaa26d7f34427ba941569eca46f02f79f3e -> trunk/cfdaaaaa26d7f34427ba941569eca46f02f79f3e 2025-08-26T19:43:48.3504936Z * [new tag] trunk/d1faf2ef0476eb60b42c057baee9af0f48ae849a -> trunk/d1faf2ef0476eb60b42c057baee9af0f48ae849a 2025-08-26T19:43:48.3505760Z * [new tag] trunk/d228a776e90368bb693837ae23285ad8fc33def5 -> trunk/d228a776e90368bb693837ae23285ad8fc33def5 2025-08-26T19:43:48.3506599Z * [new tag] trunk/d2b8c0d431e00ad57354c5247e46c1bea0b8cd31 -> trunk/d2b8c0d431e00ad57354c5247e46c1bea0b8cd31 2025-08-26T19:43:48.3507462Z * [new tag] trunk/d2bd55d8de784df439b38378f161271dc43b744c -> trunk/d2bd55d8de784df439b38378f161271dc43b744c 2025-08-26T19:43:48.3508394Z * [new tag] trunk/d4703fb91c3510460d71f648da113177edf593c8 -> trunk/d4703fb91c3510460d71f648da113177edf593c8 2025-08-26T19:43:48.3509291Z * [new tag] trunk/d875d3ca1e5099636c766c9df70ac5888c25215a -> trunk/d875d3ca1e5099636c766c9df70ac5888c25215a 2025-08-26T19:43:48.3510190Z * [new tag] trunk/d8fcb2a4acb506f9c72a1f44fc8b857158bda892 -> trunk/d8fcb2a4acb506f9c72a1f44fc8b857158bda892 2025-08-26T19:43:48.3511044Z * [new tag] trunk/daeb3a6094c62d1881ea68091fcadb02d1dc687e -> trunk/daeb3a6094c62d1881ea68091fcadb02d1dc687e 2025-08-26T19:43:48.3511997Z * [new tag] trunk/db38c44ad639e7ada3e9df2ba026a2cb5e40feb0 -> trunk/db38c44ad639e7ada3e9df2ba026a2cb5e40feb0 2025-08-26T19:43:48.3513384Z * [new tag] trunk/db44de4c0d3e9f1fe5334ff4cc261fb8fe4390c8 -> trunk/db44de4c0d3e9f1fe5334ff4cc261fb8fe4390c8 2025-08-26T19:43:48.3514235Z * [new tag] trunk/dbef6066311a1ce6e60e1f2b6084249d1ad45769 -> trunk/dbef6066311a1ce6e60e1f2b6084249d1ad45769 2025-08-26T19:43:48.3515127Z * [new tag] trunk/df571ae7ad7dacf77ce42c00189cf369d7993387 -> trunk/df571ae7ad7dacf77ce42c00189cf369d7993387 2025-08-26T19:43:48.3515982Z * [new tag] trunk/df6073641079c781e66a905e4f15ee49ac257eb2 -> trunk/df6073641079c781e66a905e4f15ee49ac257eb2 2025-08-26T19:43:48.3516993Z * [new tag] trunk/e1a64b75ff3dc834774a9174c2e7b1c46dea35ec -> trunk/e1a64b75ff3dc834774a9174c2e7b1c46dea35ec 2025-08-26T19:43:48.3517810Z * [new tag] trunk/e20f6d798606f3245686e950c43635bbe526232d -> trunk/e20f6d798606f3245686e950c43635bbe526232d 2025-08-26T19:43:48.3518562Z * [new tag] trunk/e25ee0290ef16503f178e04890c15717f6e9ea44 -> trunk/e25ee0290ef16503f178e04890c15717f6e9ea44 2025-08-26T19:43:48.3519434Z * [new tag] trunk/e34b6a01039df5d8940acdccd8d8989f3cd827aa -> trunk/e34b6a01039df5d8940acdccd8d8989f3cd827aa 2025-08-26T19:43:48.3520388Z * [new tag] trunk/e3d68dfae2dee15e74d3b95beaed7149b6afb94a -> trunk/e3d68dfae2dee15e74d3b95beaed7149b6afb94a 2025-08-26T19:43:48.3521247Z * [new tag] trunk/e3ebf364e6d2fb8008da113a596d3cc426ba9c79 -> trunk/e3ebf364e6d2fb8008da113a596d3cc426ba9c79 2025-08-26T19:43:48.3521946Z * [new tag] trunk/e4839470470168648dee5997f57347bb8541ea2b -> trunk/e4839470470168648dee5997f57347bb8541ea2b 2025-08-26T19:43:48.3522911Z * [new tag] trunk/e63155751825ba026ced3a1fc89563231bc85ccc -> trunk/e63155751825ba026ced3a1fc89563231bc85ccc 2025-08-26T19:43:48.3523750Z * [new tag] trunk/e6aa7287f8c8cac76d792097f20ba1dae6dc8717 -> trunk/e6aa7287f8c8cac76d792097f20ba1dae6dc8717 2025-08-26T19:43:48.3524619Z * [new tag] trunk/e6e45e6ae8452f0bc5e3e258027c42eb9a1394fb -> trunk/e6e45e6ae8452f0bc5e3e258027c42eb9a1394fb 2025-08-26T19:43:48.3525538Z * [new tag] trunk/e795450a35bca909902e12de99245e1c0e7e2872 -> trunk/e795450a35bca909902e12de99245e1c0e7e2872 2025-08-26T19:43:48.3526364Z * [new tag] trunk/e7e270a33a3f368c3ef0c3339950a47fdbfadd71 -> trunk/e7e270a33a3f368c3ef0c3339950a47fdbfadd71 2025-08-26T19:43:48.3527206Z * [new tag] trunk/e836323a23f5750e800abe04ef8ca386b3066b58 -> trunk/e836323a23f5750e800abe04ef8ca386b3066b58 2025-08-26T19:43:48.3528111Z * [new tag] trunk/e83825f91cb2901567fedbf31ba7cc434a897271 -> trunk/e83825f91cb2901567fedbf31ba7cc434a897271 2025-08-26T19:43:48.3529436Z * [new tag] trunk/e9d42b3880dcdbd823bbdc9370c8b0b3af0ba2e3 -> trunk/e9d42b3880dcdbd823bbdc9370c8b0b3af0ba2e3 2025-08-26T19:43:48.3530297Z * [new tag] trunk/eb5549a43164cdf8689cd7d177c03b2508c699f4 -> trunk/eb5549a43164cdf8689cd7d177c03b2508c699f4 2025-08-26T19:43:48.3531215Z * [new tag] trunk/eba1ad09e47b66478f973e03cece7f314ac3b412 -> trunk/eba1ad09e47b66478f973e03cece7f314ac3b412 2025-08-26T19:43:48.3532088Z * [new tag] trunk/eba20d2d748cb17dce9aa26e5513e4567bfd8282 -> trunk/eba20d2d748cb17dce9aa26e5513e4567bfd8282 2025-08-26T19:43:48.3532942Z * [new tag] trunk/ec21cafd85d491d2d220e4e54080fe340a37c4c2 -> trunk/ec21cafd85d491d2d220e4e54080fe340a37c4c2 2025-08-26T19:43:48.3533834Z * [new tag] trunk/ed8bcccf31e1ba01a35e818a4afbb74c333e8dc3 -> trunk/ed8bcccf31e1ba01a35e818a4afbb74c333e8dc3 2025-08-26T19:43:48.3534701Z * [new tag] trunk/eddaaa6c2a66a84e17b17bf8af5131852067b259 -> trunk/eddaaa6c2a66a84e17b17bf8af5131852067b259 2025-08-26T19:43:48.3535547Z * [new tag] trunk/ef761c43538abae5bccc0c4b6ebaf42ff676db7a -> trunk/ef761c43538abae5bccc0c4b6ebaf42ff676db7a 2025-08-26T19:43:48.3536997Z * [new tag] trunk/f085f299584b06a2a7d8855eda2a411313e782ad -> trunk/f085f299584b06a2a7d8855eda2a411313e782ad 2025-08-26T19:43:48.3537893Z * [new tag] trunk/f09458c2e16b4fe7063d73d80fd3e7e354bad3f8 -> trunk/f09458c2e16b4fe7063d73d80fd3e7e354bad3f8 2025-08-26T19:43:48.3538811Z * [new tag] trunk/f0e0a6897ee5cb31ccee10ee8e2d3c01140ff999 -> trunk/f0e0a6897ee5cb31ccee10ee8e2d3c01140ff999 2025-08-26T19:43:48.3539713Z * [new tag] trunk/f30501937738a2440f90988d1d46920529309ba8 -> trunk/f30501937738a2440f90988d1d46920529309ba8 2025-08-26T19:43:48.3540594Z * [new tag] trunk/f391afe9bf8c542fdbb822423d2a1e454b3d9744 -> trunk/f391afe9bf8c542fdbb822423d2a1e454b3d9744 2025-08-26T19:43:48.3541420Z * [new tag] trunk/f521e82a4e80df502fa57e5852af14d8779dcbd1 -> trunk/f521e82a4e80df502fa57e5852af14d8779dcbd1 2025-08-26T19:43:48.3542180Z * [new tag] trunk/f5bf5147ad18994c9a6e0f565d7831362bf5a18a -> trunk/f5bf5147ad18994c9a6e0f565d7831362bf5a18a 2025-08-26T19:43:48.3543020Z * [new tag] trunk/f795e92802c55608ad4f4f198726d250056d0232 -> trunk/f795e92802c55608ad4f4f198726d250056d0232 2025-08-26T19:43:48.3544218Z * [new tag] trunk/f8bd85827d465a8a2a610c27ed9e62a4c27ac07d -> trunk/f8bd85827d465a8a2a610c27ed9e62a4c27ac07d 2025-08-26T19:43:48.3545004Z * [new tag] trunk/f90ccad1651b5a1698b2232acc3e92e2829b7935 -> trunk/f90ccad1651b5a1698b2232acc3e92e2829b7935 2025-08-26T19:43:48.3545735Z * [new tag] trunk/f912c93344caa74e24c8164a2e25fe84a8203073 -> trunk/f912c93344caa74e24c8164a2e25fe84a8203073 2025-08-26T19:43:48.3546659Z * [new tag] trunk/f9875166a953a51bbd454d963ee03d41818a27e8 -> trunk/f9875166a953a51bbd454d963ee03d41818a27e8 2025-08-26T19:43:48.3547555Z * [new tag] trunk/f9df4ec2af0ac19b42f658ae87acf12067e67b36 -> trunk/f9df4ec2af0ac19b42f658ae87acf12067e67b36 2025-08-26T19:43:48.3548464Z * [new tag] trunk/fab5dac734344105ae107e85c08151758a4a9b4d -> trunk/fab5dac734344105ae107e85c08151758a4a9b4d 2025-08-26T19:43:48.3549393Z * [new tag] trunk/fb241d0a448f1dd88471098ac149418124a7c4aa -> trunk/fb241d0a448f1dd88471098ac149418124a7c4aa 2025-08-26T19:43:48.3550348Z * [new tag] trunk/fc0683b1e75fdf3182e0855b3f79e80fe0124ef1 -> trunk/fc0683b1e75fdf3182e0855b3f79e80fe0124ef1 2025-08-26T19:43:48.3553019Z * [new tag] trunk/fc69c2bc67672c3b2d0c62c1821895f09288f1c0 -> trunk/fc69c2bc67672c3b2d0c62c1821895f09288f1c0 2025-08-26T19:43:48.3553823Z * [new tag] trunk/febfc3ec03004116dfd6d504e6853ff02a1dd6e0 -> trunk/febfc3ec03004116dfd6d504e6853ff02a1dd6e0 2025-08-26T19:43:48.3554773Z * [new tag] trunk/fecc5f600110209aaaedead11770a445b3c879e6 -> trunk/fecc5f600110209aaaedead11770a445b3c879e6 2025-08-26T19:43:48.3555677Z * [new tag] trunk/ff4f5dd8ed8e2aaee903c7d30cd4f8bd04d883c8 -> trunk/ff4f5dd8ed8e2aaee903c7d30cd4f8bd04d883c8 2025-08-26T19:43:48.3556410Z * [new tag] trunk/ffa1ce7650766c2ae6eaa96415dfc29e9eb0b3ec -> trunk/ffa1ce7650766c2ae6eaa96415dfc29e9eb0b3ec 2025-08-26T19:43:48.3556980Z * [new tag] v0.1.1 -> v0.1.1 2025-08-26T19:43:48.3557930Z * [new tag] v0.1.10 -> v0.1.10 2025-08-26T19:43:48.3558685Z * [new tag] v0.1.11 -> v0.1.11 2025-08-26T19:43:48.3559404Z * [new tag] v0.1.12 -> v0.1.12 2025-08-26T19:43:48.3560288Z * [new tag] v0.1.2 -> v0.1.2 2025-08-26T19:43:48.3561011Z * [new tag] v0.1.3 -> v0.1.3 2025-08-26T19:43:48.3561780Z * [new tag] v0.1.4 -> v0.1.4 2025-08-26T19:43:48.3562504Z * [new tag] v0.1.5 -> v0.1.5 2025-08-26T19:43:48.3563377Z * [new tag] v0.1.6 -> v0.1.6 2025-08-26T19:43:48.3564021Z * [new tag] v0.1.7 -> v0.1.7 2025-08-26T19:43:48.3564886Z * [new tag] v0.1.8 -> v0.1.8 2025-08-26T19:43:48.3566034Z * [new tag] v0.1.9 -> v0.1.9 2025-08-26T19:43:48.3566757Z * [new tag] v0.2.0 -> v0.2.0 2025-08-26T19:43:48.3567704Z * [new tag] v0.3.0 -> v0.3.0 2025-08-26T19:43:48.3568568Z * [new tag] v0.3.1 -> v0.3.1 2025-08-26T19:43:48.3569411Z * [new tag] v0.4.0 -> v0.4.0 2025-08-26T19:43:48.3570322Z * [new tag] v0.4.1 -> v0.4.1 2025-08-26T19:43:48.3571063Z * [new tag] v1.0.0 -> v1.0.0 2025-08-26T19:43:48.3571996Z * [new tag] v1.0.0a0 -> v1.0.0a0 2025-08-26T19:43:48.3572660Z * [new tag] v1.0.1 -> v1.0.1 2025-08-26T19:43:48.3573577Z * [new tag] v1.0rc0 -> v1.0rc0 2025-08-26T19:43:48.3574093Z * [new tag] v1.0rc1 -> v1.0rc1 2025-08-26T19:43:48.3575072Z * [new tag] v1.1.0 -> v1.1.0 2025-08-26T19:43:48.3575753Z * [new tag] v1.1.0a0 -> v1.1.0a0 2025-08-26T19:43:48.3576834Z * [new tag] v1.10.0 -> v1.10.0 2025-08-26T19:43:48.3577739Z * [new tag] v1.10.0-rc1 -> v1.10.0-rc1 2025-08-26T19:43:48.3578506Z * [new tag] v1.10.0-rc2 -> v1.10.0-rc2 2025-08-26T19:43:48.3579096Z * [new tag] v1.10.0-rc3 -> v1.10.0-rc3 2025-08-26T19:43:48.3580061Z * [new tag] v1.10.1 -> v1.10.1 2025-08-26T19:43:48.3580705Z * [new tag] v1.10.1-rc1 -> v1.10.1-rc1 2025-08-26T19:43:48.3581302Z * [new tag] v1.10.2 -> v1.10.2 2025-08-26T19:43:48.3581939Z * [new tag] v1.10.2-rc1 -> v1.10.2-rc1 2025-08-26T19:43:48.3582809Z * [new tag] v1.11.0 -> v1.11.0 2025-08-26T19:43:48.3583789Z * [new tag] v1.11.0-rc1 -> v1.11.0-rc1 2025-08-26T19:43:48.3584804Z * [new tag] v1.11.0-rc2 -> v1.11.0-rc2 2025-08-26T19:43:48.3585708Z * [new tag] v1.11.0-rc3 -> v1.11.0-rc3 2025-08-26T19:43:48.3586459Z * [new tag] v1.11.0-rc4 -> v1.11.0-rc4 2025-08-26T19:43:48.3587411Z * [new tag] v1.11.0-rc5 -> v1.11.0-rc5 2025-08-26T19:43:48.3587961Z * [new tag] v1.11.0-rc6 -> v1.11.0-rc6 2025-08-26T19:43:48.3588558Z * [new tag] v1.11.0-rc7 -> v1.11.0-rc7 2025-08-26T19:43:48.3589484Z * [new tag] v1.12.0 -> v1.12.0 2025-08-26T19:43:48.3590194Z * [new tag] v1.12.0-rc1 -> v1.12.0-rc1 2025-08-26T19:43:48.3591179Z * [new tag] v1.12.0-rc2 -> v1.12.0-rc2 2025-08-26T19:43:48.3591949Z * [new tag] v1.12.0-rc3 -> v1.12.0-rc3 2025-08-26T19:43:48.3592923Z * [new tag] v1.12.0-rc4 -> v1.12.0-rc4 2025-08-26T19:43:48.3593623Z * [new tag] v1.12.0-rc5 -> v1.12.0-rc5 2025-08-26T19:43:48.3594693Z * [new tag] v1.12.0-rc6 -> v1.12.0-rc6 2025-08-26T19:43:48.3595163Z * [new tag] v1.12.0-rc7 -> v1.12.0-rc7 2025-08-26T19:43:48.3596018Z * [new tag] v1.12.0-rc8 -> v1.12.0-rc8 2025-08-26T19:43:48.3596594Z * [new tag] v1.12.1 -> v1.12.1 2025-08-26T19:43:48.3597594Z * [new tag] v1.12.1-rc1 -> v1.12.1-rc1 2025-08-26T19:43:48.3598347Z * [new tag] v1.12.1-rc2 -> v1.12.1-rc2 2025-08-26T19:43:48.3599328Z * [new tag] v1.12.1-rc3 -> v1.12.1-rc3 2025-08-26T19:43:48.3600205Z * [new tag] v1.12.1-rc4 -> v1.12.1-rc4 2025-08-26T19:43:48.3600820Z * [new tag] v1.12.1-rc5 -> v1.12.1-rc5 2025-08-26T19:43:48.3601724Z * [new tag] v1.13.0 -> v1.13.0 2025-08-26T19:43:48.3602646Z * [new tag] v1.13.0-rc1 -> v1.13.0-rc1 2025-08-26T19:43:48.3603376Z * [new tag] v1.13.0-rc2 -> v1.13.0-rc2 2025-08-26T19:43:48.3604290Z * [new tag] v1.13.0-rc3 -> v1.13.0-rc3 2025-08-26T19:43:48.3605205Z * [new tag] v1.13.0-rc4 -> v1.13.0-rc4 2025-08-26T19:43:48.3605712Z * [new tag] v1.13.0-rc5 -> v1.13.0-rc5 2025-08-26T19:43:48.3606369Z * [new tag] v1.13.0-rc6 -> v1.13.0-rc6 2025-08-26T19:43:48.3607357Z * [new tag] v1.13.1 -> v1.13.1 2025-08-26T19:43:48.3607874Z * [new tag] v1.13.1-rc1 -> v1.13.1-rc1 2025-08-26T19:43:48.3608839Z * [new tag] v1.2.0 -> v1.2.0 2025-08-26T19:43:48.3609706Z * [new tag] v1.2.0a0 -> v1.2.0a0 2025-08-26T19:43:48.3610448Z * [new tag] v1.3.0 -> v1.3.0 2025-08-26T19:43:48.3611355Z * [new tag] v1.3.0a0 -> v1.3.0a0 2025-08-26T19:43:48.3611943Z * [new tag] v1.3.1 -> v1.3.1 2025-08-26T19:43:48.3612811Z * [new tag] v1.4.0 -> v1.4.0 2025-08-26T19:43:48.3613544Z * [new tag] v1.4.0a0 -> v1.4.0a0 2025-08-26T19:43:48.3614199Z * [new tag] v1.4.1 -> v1.4.1 2025-08-26T19:43:48.3615114Z * [new tag] v1.5.0 -> v1.5.0 2025-08-26T19:43:48.3616011Z * [new tag] v1.5.0-rc1 -> v1.5.0-rc1 2025-08-26T19:43:48.3616943Z * [new tag] v1.5.0-rc2 -> v1.5.0-rc2 2025-08-26T19:43:48.3618179Z * [new tag] v1.5.0-rc3 -> v1.5.0-rc3 2025-08-26T19:43:48.3618830Z * [new tag] v1.5.0-rc4 -> v1.5.0-rc4 2025-08-26T19:43:48.3619432Z * [new tag] v1.5.0-rc5 -> v1.5.0-rc5 2025-08-26T19:43:48.3620466Z * [new tag] v1.5.1 -> v1.5.1 2025-08-26T19:43:48.3620962Z * [new tag] v1.5.1-rc1 -> v1.5.1-rc1 2025-08-26T19:43:48.3621806Z * [new tag] v1.6.0 -> v1.6.0 2025-08-26T19:43:48.3622707Z * [new tag] v1.6.0-rc1 -> v1.6.0-rc1 2025-08-26T19:43:48.3623604Z * [new tag] v1.6.0-rc2 -> v1.6.0-rc2 2025-08-26T19:43:48.3624329Z * [new tag] v1.6.0-rc3 -> v1.6.0-rc3 2025-08-26T19:43:48.3625253Z * [new tag] v1.6.0-rc4 -> v1.6.0-rc4 2025-08-26T19:43:48.3626212Z * [new tag] v1.6.0-rc5 -> v1.6.0-rc5 2025-08-26T19:43:48.3626801Z * [new tag] v1.6.0-rc6 -> v1.6.0-rc6 2025-08-26T19:43:48.3627516Z * [new tag] v1.6.0-rc7 -> v1.6.0-rc7 2025-08-26T19:43:48.3628424Z * [new tag] v1.7.0 -> v1.7.0 2025-08-26T19:43:48.3629196Z * [new tag] v1.7.0-rc1 -> v1.7.0-rc1 2025-08-26T19:43:48.3630226Z * [new tag] v1.7.0-rc2 -> v1.7.0-rc2 2025-08-26T19:43:48.3630928Z * [new tag] v1.7.0-rc3 -> v1.7.0-rc3 2025-08-26T19:43:48.3631554Z * [new tag] v1.7.0-rc4 -> v1.7.0-rc4 2025-08-26T19:43:48.3632495Z * [new tag] v1.7.1 -> v1.7.1 2025-08-26T19:43:48.3633539Z * [new tag] v1.7.1-rc1 -> v1.7.1-rc1 2025-08-26T19:43:48.3634376Z * [new tag] v1.7.1-rc2 -> v1.7.1-rc2 2025-08-26T19:43:48.3635055Z * [new tag] v1.7.1-rc3 -> v1.7.1-rc3 2025-08-26T19:43:48.3635937Z * [new tag] v1.8.0 -> v1.8.0 2025-08-26T19:43:48.3636536Z * [new tag] v1.8.0-rc1 -> v1.8.0-rc1 2025-08-26T19:43:48.3637579Z * [new tag] v1.8.0-rc2 -> v1.8.0-rc2 2025-08-26T19:43:48.3638505Z * [new tag] v1.8.0-rc3 -> v1.8.0-rc3 2025-08-26T19:43:48.3639195Z * [new tag] v1.8.0-rc4 -> v1.8.0-rc4 2025-08-26T19:43:48.3639842Z * [new tag] v1.8.0-rc5 -> v1.8.0-rc5 2025-08-26T19:43:48.3640689Z * [new tag] v1.8.1 -> v1.8.1 2025-08-26T19:43:48.3641359Z * [new tag] v1.8.1-rc1 -> v1.8.1-rc1 2025-08-26T19:43:48.3641959Z * [new tag] v1.8.1-rc2 -> v1.8.1-rc2 2025-08-26T19:43:48.3642633Z * [new tag] v1.8.1-rc3 -> v1.8.1-rc3 2025-08-26T19:43:48.3644065Z * [new tag] v1.8.2 -> v1.8.2 2025-08-26T19:43:48.3644664Z * [new tag] v1.8.2-rc1 -> v1.8.2-rc1 2025-08-26T19:43:48.3645541Z * [new tag] v1.9.0 -> v1.9.0 2025-08-26T19:43:48.3646400Z * [new tag] v1.9.0-rc1 -> v1.9.0-rc1 2025-08-26T19:43:48.3647292Z * [new tag] v1.9.0-rc2 -> v1.9.0-rc2 2025-08-26T19:43:48.3648261Z * [new tag] v1.9.0-rc3 -> v1.9.0-rc3 2025-08-26T19:43:48.3648864Z * [new tag] v1.9.0-rc4 -> v1.9.0-rc4 2025-08-26T19:43:48.3649909Z * [new tag] v1.9.1 -> v1.9.1 2025-08-26T19:43:48.3651031Z * [new tag] v1.9.1-rc1 -> v1.9.1-rc1 2025-08-26T19:43:48.3651410Z * [new tag] v1.9.1-rc2 -> v1.9.1-rc2 2025-08-26T19:43:48.3652431Z * [new tag] v2.0.0 -> v2.0.0 2025-08-26T19:43:48.3653114Z * [new tag] v2.0.0-rc1 -> v2.0.0-rc1 2025-08-26T19:43:48.3654092Z * [new tag] v2.0.0-rc2 -> v2.0.0-rc2 2025-08-26T19:43:48.3654843Z * [new tag] v2.0.0-rc3 -> v2.0.0-rc3 2025-08-26T19:43:48.3655786Z * [new tag] v2.0.0-rc4 -> v2.0.0-rc4 2025-08-26T19:43:48.3656491Z * [new tag] v2.0.0-rc5 -> v2.0.0-rc5 2025-08-26T19:43:48.3657090Z * [new tag] v2.0.0-rc6 -> v2.0.0-rc6 2025-08-26T19:43:48.3658140Z * [new tag] v2.0.1 -> v2.0.1 2025-08-26T19:43:48.3659019Z * [new tag] v2.0.1-rc1 -> v2.0.1-rc1 2025-08-26T19:43:48.3659622Z * [new tag] v2.0.1-rc2 -> v2.0.1-rc2 2025-08-26T19:43:48.3660369Z * [new tag] v2.0.1-rc3 -> v2.0.1-rc3 2025-08-26T19:43:48.3660977Z * [new tag] v2.0.1-rc4 -> v2.0.1-rc4 2025-08-26T19:43:48.3662493Z * [new tag] v2.1.0 -> v2.1.0 2025-08-26T19:43:48.3663224Z * [new tag] v2.1.0-rc1 -> v2.1.0-rc1 2025-08-26T19:43:48.3664127Z * [new tag] v2.1.0-rc2 -> v2.1.0-rc2 2025-08-26T19:43:48.3665063Z * [new tag] v2.1.0-rc3 -> v2.1.0-rc3 2025-08-26T19:43:48.3665960Z * [new tag] v2.1.0-rc4 -> v2.1.0-rc4 2025-08-26T19:43:48.3666690Z * [new tag] v2.1.0-rc5 -> v2.1.0-rc5 2025-08-26T19:43:48.3667372Z * [new tag] v2.1.0-rc6 -> v2.1.0-rc6 2025-08-26T19:43:48.3668267Z * [new tag] v2.1.1 -> v2.1.1 2025-08-26T19:43:48.3669204Z * [new tag] v2.1.1-rc1 -> v2.1.1-rc1 2025-08-26T19:43:48.3669906Z * [new tag] v2.1.1-rc2 -> v2.1.1-rc2 2025-08-26T19:43:48.3671319Z * [new tag] v2.1.1-rc3 -> v2.1.1-rc3 2025-08-26T19:43:48.3672098Z * [new tag] v2.1.1-rc4 -> v2.1.1-rc4 2025-08-26T19:43:48.3672998Z * [new tag] v2.1.1-rc5 -> v2.1.1-rc5 2025-08-26T19:43:48.3673597Z * [new tag] v2.1.1-rc6 -> v2.1.1-rc6 2025-08-26T19:43:48.3674423Z * [new tag] v2.1.2 -> v2.1.2 2025-08-26T19:43:48.3675446Z * [new tag] v2.1.2-rc1 -> v2.1.2-rc1 2025-08-26T19:43:48.3676275Z * [new tag] v2.1.2-rc2 -> v2.1.2-rc2 2025-08-26T19:43:48.3676920Z * [new tag] v2.1.2-rc3 -> v2.1.2-rc3 2025-08-26T19:43:48.3677861Z * [new tag] v2.2.0 -> v2.2.0 2025-08-26T19:43:48.3678807Z * [new tag] v2.2.0-rc1 -> v2.2.0-rc1 2025-08-26T19:43:48.3679413Z * [new tag] v2.2.0-rc2 -> v2.2.0-rc2 2025-08-26T19:43:48.3680361Z * [new tag] v2.2.0-rc3 -> v2.2.0-rc3 2025-08-26T19:43:48.3681064Z * [new tag] v2.2.0-rc4 -> v2.2.0-rc4 2025-08-26T19:43:48.3682000Z * [new tag] v2.2.0-rc5 -> v2.2.0-rc5 2025-08-26T19:43:48.3682744Z * [new tag] v2.2.0-rc6 -> v2.2.0-rc6 2025-08-26T19:43:48.3683406Z * [new tag] v2.2.0-rc7 -> v2.2.0-rc7 2025-08-26T19:43:48.3684090Z * [new tag] v2.2.0-rc8 -> v2.2.0-rc8 2025-08-26T19:43:48.3685186Z * [new tag] v2.2.1 -> v2.2.1 2025-08-26T19:43:48.3685893Z * [new tag] v2.2.1-rc1 -> v2.2.1-rc1 2025-08-26T19:43:48.3686548Z * [new tag] v2.2.1-rc2 -> v2.2.1-rc2 2025-08-26T19:43:48.3687177Z * [new tag] v2.2.1-rc3 -> v2.2.1-rc3 2025-08-26T19:43:48.3687799Z * [new tag] v2.2.2 -> v2.2.2 2025-08-26T19:43:48.3688884Z * [new tag] v2.2.2-rc1 -> v2.2.2-rc1 2025-08-26T19:43:48.3689464Z * [new tag] v2.2.2-rc2 -> v2.2.2-rc2 2025-08-26T19:43:48.3690172Z * [new tag] v2.2.2-rc3 -> v2.2.2-rc3 2025-08-26T19:43:48.3691106Z * [new tag] v2.3.0 -> v2.3.0 2025-08-26T19:43:48.3691867Z * [new tag] v2.3.0-rc1 -> v2.3.0-rc1 2025-08-26T19:43:48.3692905Z * [new tag] v2.3.0-rc10 -> v2.3.0-rc10 2025-08-26T19:43:48.3693891Z * [new tag] v2.3.0-rc11 -> v2.3.0-rc11 2025-08-26T19:43:48.3694393Z * [new tag] v2.3.0-rc12 -> v2.3.0-rc12 2025-08-26T19:43:48.3695367Z * [new tag] v2.3.0-rc2 -> v2.3.0-rc2 2025-08-26T19:43:48.3696269Z * [new tag] v2.3.0-rc3 -> v2.3.0-rc3 2025-08-26T19:43:48.3697026Z * [new tag] v2.3.0-rc4 -> v2.3.0-rc4 2025-08-26T19:43:48.3697985Z * [new tag] v2.3.0-rc5 -> v2.3.0-rc5 2025-08-26T19:43:48.3698583Z * [new tag] v2.3.0-rc6 -> v2.3.0-rc6 2025-08-26T19:43:48.3699480Z * [new tag] v2.3.0-rc7 -> v2.3.0-rc7 2025-08-26T19:43:48.3700234Z * [new tag] v2.3.0-rc8 -> v2.3.0-rc8 2025-08-26T19:43:48.3700985Z * [new tag] v2.3.0-rc9 -> v2.3.0-rc9 2025-08-26T19:43:48.3701623Z * [new tag] v2.3.1 -> v2.3.1 2025-08-26T19:43:48.3702542Z * [new tag] v2.3.1-rc1 -> v2.3.1-rc1 2025-08-26T19:43:48.3703274Z * [new tag] v2.3.1-rc2 -> v2.3.1-rc2 2025-08-26T19:43:48.3704286Z * [new tag] v2.3.1-rc3 -> v2.3.1-rc3 2025-08-26T19:43:48.3705061Z * [new tag] v2.4.0 -> v2.4.0 2025-08-26T19:43:48.3705998Z * [new tag] v2.4.0-rc1 -> v2.4.0-rc1 2025-08-26T19:43:48.3706864Z * [new tag] v2.4.0-rc2 -> v2.4.0-rc2 2025-08-26T19:43:48.3707607Z * [new tag] v2.4.0-rc3 -> v2.4.0-rc3 2025-08-26T19:43:48.3708526Z * [new tag] v2.4.0-rc4 -> v2.4.0-rc4 2025-08-26T19:43:48.3709441Z * [new tag] v2.4.0-rc5 -> v2.4.0-rc5 2025-08-26T19:43:48.3710293Z * [new tag] v2.4.0-rc6 -> v2.4.0-rc6 2025-08-26T19:43:48.3711204Z * [new tag] v2.4.0-rc7 -> v2.4.0-rc7 2025-08-26T19:43:48.3711932Z * [new tag] v2.4.0-rc8 -> v2.4.0-rc8 2025-08-26T19:43:48.3712891Z * [new tag] v2.4.0-rc9 -> v2.4.0-rc9 2025-08-26T19:43:48.3713433Z * [new tag] v2.4.1 -> v2.4.1 2025-08-26T19:43:48.3714498Z * [new tag] v2.4.1-rc1 -> v2.4.1-rc1 2025-08-26T19:43:48.3715329Z * [new tag] v2.4.1-rc2 -> v2.4.1-rc2 2025-08-26T19:43:48.3716313Z * [new tag] v2.4.1-rc3 -> v2.4.1-rc3 2025-08-26T19:43:48.3717038Z * [new tag] v2.5.0 -> v2.5.0 2025-08-26T19:43:48.3717972Z * [new tag] v2.5.0-rc1 -> v2.5.0-rc1 2025-08-26T19:43:48.3718645Z * [new tag] v2.5.0-rc10 -> v2.5.0-rc10 2025-08-26T19:43:48.3719412Z * [new tag] v2.5.0-rc2 -> v2.5.0-rc2 2025-08-26T19:43:48.3720303Z * [new tag] v2.5.0-rc3 -> v2.5.0-rc3 2025-08-26T19:43:48.3721064Z * [new tag] v2.5.0-rc4 -> v2.5.0-rc4 2025-08-26T19:43:48.3722033Z * [new tag] v2.5.0-rc5 -> v2.5.0-rc5 2025-08-26T19:43:48.3722962Z * [new tag] v2.5.0-rc6 -> v2.5.0-rc6 2025-08-26T19:43:48.3724275Z * [new tag] v2.5.0-rc7 -> v2.5.0-rc7 2025-08-26T19:43:48.3725156Z * [new tag] v2.5.0-rc8 -> v2.5.0-rc8 2025-08-26T19:43:48.3726008Z * [new tag] v2.5.0-rc9 -> v2.5.0-rc9 2025-08-26T19:43:48.3726606Z * [new tag] v2.5.1 -> v2.5.1 2025-08-26T19:43:48.3727247Z * [new tag] v2.5.1-rc1 -> v2.5.1-rc1 2025-08-26T19:43:48.3727951Z * [new tag] v2.6.0 -> v2.6.0 2025-08-26T19:43:48.3729054Z * [new tag] v2.6.0-rc1 -> v2.6.0-rc1 2025-08-26T19:43:48.3730089Z * [new tag] v2.6.0-rc2 -> v2.6.0-rc2 2025-08-26T19:43:48.3730967Z * [new tag] v2.6.0-rc3 -> v2.6.0-rc3 2025-08-26T19:43:48.3731721Z * [new tag] v2.6.0-rc4 -> v2.6.0-rc4 2025-08-26T19:43:48.3732868Z * [new tag] v2.6.0-rc5 -> v2.6.0-rc5 2025-08-26T19:43:48.3733902Z * [new tag] v2.6.0-rc6 -> v2.6.0-rc6 2025-08-26T19:43:48.3734738Z * [new tag] v2.6.0-rc7 -> v2.6.0-rc7 2025-08-26T19:43:48.3735756Z * [new tag] v2.6.0-rc8 -> v2.6.0-rc8 2025-08-26T19:43:48.3736622Z * [new tag] v2.6.0-rc9 -> v2.6.0-rc9 2025-08-26T19:43:48.3737792Z * [new tag] v2.7.0 -> v2.7.0 2025-08-26T19:43:48.3742877Z * [new tag] v2.7.0-rc1 -> v2.7.0-rc1 2025-08-26T19:43:48.3743444Z * [new tag] v2.7.0-rc10 -> v2.7.0-rc10 2025-08-26T19:43:48.3744517Z * [new tag] v2.7.0-rc2 -> v2.7.0-rc2 2025-08-26T19:43:48.3745369Z * [new tag] v2.7.0-rc3 -> v2.7.0-rc3 2025-08-26T19:43:48.3746347Z * [new tag] v2.7.0-rc4 -> v2.7.0-rc4 2025-08-26T19:43:48.3747078Z * [new tag] v2.7.0-rc5 -> v2.7.0-rc5 2025-08-26T19:43:48.3748094Z * [new tag] v2.7.0-rc6 -> v2.7.0-rc6 2025-08-26T19:43:48.3748966Z * [new tag] v2.7.0-rc7 -> v2.7.0-rc7 2025-08-26T19:43:48.3749935Z * [new tag] v2.7.0-rc8 -> v2.7.0-rc8 2025-08-26T19:43:48.3750845Z * [new tag] v2.7.0-rc9 -> v2.7.0-rc9 2025-08-26T19:43:48.3751450Z * [new tag] v2.7.1 -> v2.7.1 2025-08-26T19:43:48.3752415Z * [new tag] v2.7.1-rc1 -> v2.7.1-rc1 2025-08-26T19:43:48.3753326Z * [new tag] v2.7.1-rc2 -> v2.7.1-rc2 2025-08-26T19:43:48.3754278Z * [new tag] v2.7.1-rc3 -> v2.7.1-rc3 2025-08-26T19:43:48.3755196Z * [new tag] v2.7.1-rc4 -> v2.7.1-rc4 2025-08-26T19:43:48.3755943Z * [new tag] v2.7.1-rc5 -> v2.7.1-rc5 2025-08-26T19:43:48.3756635Z * [new tag] v2.8.0 -> v2.8.0 2025-08-26T19:43:48.3757608Z * [new tag] v2.8.0-rc1 -> v2.8.0-rc1 2025-08-26T19:43:48.3758379Z * [new tag] v2.8.0-rc2 -> v2.8.0-rc2 2025-08-26T19:43:48.3759435Z * [new tag] v2.8.0-rc3 -> v2.8.0-rc3 2025-08-26T19:43:48.3760437Z * [new tag] v2.8.0-rc4 -> v2.8.0-rc4 2025-08-26T19:43:48.3761367Z * [new tag] v2.8.0-rc5 -> v2.8.0-rc5 2025-08-26T19:43:48.3762295Z * [new tag] v2.8.0-rc6 -> v2.8.0-rc6 2025-08-26T19:43:48.3763027Z * [new tag] v2.8.0-rc7 -> v2.8.0-rc7 2025-08-26T19:43:48.3764008Z * [new tag] v2.8.0-rc8 -> v2.8.0-rc8 2025-08-26T19:43:48.3764723Z * [new tag] whc_flight_1 -> whc_flight_1 2025-08-26T19:43:48.3765645Z * [new tag] whc_flight_2 -> whc_flight_2 2025-08-26T19:43:48.3766316Z * [new tag] whc_flight_4 -> whc_flight_4 2025-08-26T19:43:48.4339381Z [command]/usr/bin/git rev-parse --verify --quiet 262640fd220236042fbf4443cc163c8838c84c3d^{object} 2025-08-26T19:43:48.4360881Z 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:43:48.4364157Z ##[endgroup] 2025-08-26T19:43:48.4364454Z ##[group]Determining the checkout info 2025-08-26T19:43:48.4365518Z ##[endgroup] 2025-08-26T19:43:48.4369277Z [command]/usr/bin/git sparse-checkout disable 2025-08-26T19:43:48.4398933Z [command]/usr/bin/git config --local --unset-all extensions.worktreeConfig 2025-08-26T19:43:48.4420686Z ##[group]Checking out the ref 2025-08-26T19:43:48.4427444Z [command]/usr/bin/git checkout --progress --force 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:43:49.4725829Z Updating files: 87% (16918/19395) 2025-08-26T19:43:49.4833631Z Updating files: 88% (17068/19395) 2025-08-26T19:43:49.4951246Z Updating files: 89% (17262/19395) 2025-08-26T19:43:49.5107986Z Updating files: 90% (17456/19395) 2025-08-26T19:43:49.5227199Z Updating files: 91% (17650/19395) 2025-08-26T19:43:49.5348711Z Updating files: 92% (17844/19395) 2025-08-26T19:43:49.5522203Z Updating files: 93% (18038/19395) 2025-08-26T19:43:49.5705652Z Updating files: 94% (18232/19395) 2025-08-26T19:43:49.5875659Z Updating files: 95% (18426/19395) 2025-08-26T19:43:49.6016740Z Updating files: 96% (18620/19395) 2025-08-26T19:43:49.6192652Z Updating files: 97% (18814/19395) 2025-08-26T19:43:49.6430752Z Updating files: 98% (19008/19395) 2025-08-26T19:43:49.6574341Z Updating files: 99% (19202/19395) 2025-08-26T19:43:49.6574858Z Updating files: 100% (19395/19395) 2025-08-26T19:43:49.6575576Z Updating files: 100% (19395/19395), done. 2025-08-26T19:43:49.6839247Z Note: switching to '262640fd220236042fbf4443cc163c8838c84c3d'. 2025-08-26T19:43:49.6839912Z 2025-08-26T19:43:49.6840343Z You are in 'detached HEAD' state. You can look around, make experimental 2025-08-26T19:43:49.6841377Z changes and commit them, and you can discard any commits you make in this 2025-08-26T19:43:49.6842414Z state without impacting any branches by switching back to a branch. 2025-08-26T19:43:49.6842932Z 2025-08-26T19:43:49.6843274Z If you want to create a new branch to retain commits you create, you may 2025-08-26T19:43:49.6844115Z do so (now or later) by using -c with the switch command. Example: 2025-08-26T19:43:49.6844592Z 2025-08-26T19:43:49.6844761Z git switch -c 2025-08-26T19:43:49.6845219Z 2025-08-26T19:43:49.6845384Z Or undo this operation with: 2025-08-26T19:43:49.6845662Z 2025-08-26T19:43:49.6845826Z git switch - 2025-08-26T19:43:49.6846069Z 2025-08-26T19:43:49.6846519Z Turn off this advice by setting config variable advice.detachedHead to false 2025-08-26T19:43:49.6847206Z 2025-08-26T19:43:49.6847628Z HEAD is now at 262640fd220 [ROCm][CI] restore test_flex_attention tests (#161519) 2025-08-26T19:43:49.6908524Z ##[endgroup] 2025-08-26T19:43:49.6908991Z ##[group]Setting up auth for fetching submodules 2025-08-26T19:43:49.6914696Z [command]/usr/bin/git config --global http.https://github.com/.extraheader AUTHORIZATION: basic *** 2025-08-26T19:43:49.6958066Z [command]/usr/bin/git config --global --unset-all url.https://github.com/.insteadOf 2025-08-26T19:43:49.6982229Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf git@github.com: 2025-08-26T19:43:49.7006999Z [command]/usr/bin/git config --global --add url.https://github.com/.insteadOf org-21003710@github.com: 2025-08-26T19:43:49.7027212Z ##[endgroup] 2025-08-26T19:43:49.7027625Z ##[group]Fetching submodules 2025-08-26T19:43:49.7030717Z [command]/usr/bin/git submodule sync --recursive 2025-08-26T19:43:49.7314350Z [command]/usr/bin/git -c protocol.version=2 submodule update --init --force --recursive 2025-08-26T19:43:49.7589897Z Submodule 'android/libs/fbjni' (https://github.com/facebookincubator/fbjni.git) registered for path 'android/libs/fbjni' 2025-08-26T19:43:49.7591811Z Submodule 'third_party/NNPACK_deps/FP16' (https://github.com/Maratyszcza/FP16.git) registered for path 'third_party/FP16' 2025-08-26T19:43:49.7594671Z Submodule 'third_party/NNPACK_deps/FXdiv' (https://github.com/Maratyszcza/FXdiv.git) registered for path 'third_party/FXdiv' 2025-08-26T19:43:49.7955525Z Submodule 'third_party/NNPACK' (https://github.com/Maratyszcza/NNPACK.git) registered for path 'third_party/NNPACK' 2025-08-26T19:43:49.7958210Z Submodule 'third_party/NVTX' (https://github.com/NVIDIA/NVTX.git) registered for path 'third_party/NVTX' 2025-08-26T19:43:49.7961930Z Submodule 'third_party/VulkanMemoryAllocator' (https://github.com/GPUOpen-LibrariesAndSDKs/VulkanMemoryAllocator.git) registered for path 'third_party/VulkanMemoryAllocator' 2025-08-26T19:43:49.7968939Z Submodule 'third_party/XNNPACK' (https://github.com/google/XNNPACK.git) registered for path 'third_party/XNNPACK' 2025-08-26T19:43:49.7969857Z Submodule 'third_party/aiter' (https://github.com/ROCm/aiter.git) registered for path 'third_party/aiter' 2025-08-26T19:43:49.7972096Z Submodule 'third_party/benchmark' (https://github.com/google/benchmark.git) registered for path 'third_party/benchmark' 2025-08-26T19:43:49.7975526Z Submodule 'third_party/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/composable_kernel' 2025-08-26T19:43:49.7979035Z Submodule 'third_party/cpp-httplib' (https://github.com/yhirose/cpp-httplib.git) registered for path 'third_party/cpp-httplib' 2025-08-26T19:43:49.7994119Z Submodule 'third_party/cpuinfo' (https://github.com/pytorch/cpuinfo.git) registered for path 'third_party/cpuinfo' 2025-08-26T19:43:49.7998043Z Submodule 'third_party/cudnn_frontend' (https://github.com/NVIDIA/cudnn-frontend.git) registered for path 'third_party/cudnn_frontend' 2025-08-26T19:43:49.8001767Z Submodule 'third_party/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/cutlass' 2025-08-26T19:43:49.8005604Z Submodule 'third_party/fbgemm' (https://github.com/pytorch/fbgemm) registered for path 'third_party/fbgemm' 2025-08-26T19:43:49.8010882Z Submodule 'third_party/flash-attention' (https://github.com/Dao-AILab/flash-attention.git) registered for path 'third_party/flash-attention' 2025-08-26T19:43:49.8015252Z Submodule 'third_party/flatbuffers' (https://github.com/google/flatbuffers.git) registered for path 'third_party/flatbuffers' 2025-08-26T19:43:49.8019625Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/fmt' 2025-08-26T19:43:49.8024181Z Submodule 'third_party/gemmlowp/gemmlowp' (https://github.com/google/gemmlowp.git) registered for path 'third_party/gemmlowp/gemmlowp' 2025-08-26T19:43:49.8039509Z Submodule 'third_party/gloo' (https://github.com/pytorch/gloo) registered for path 'third_party/gloo' 2025-08-26T19:43:49.8045666Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/googletest' 2025-08-26T19:43:49.8050330Z Submodule 'third_party/ideep' (https://github.com/intel/ideep) registered for path 'third_party/ideep' 2025-08-26T19:43:49.8054939Z Submodule 'third_party/ittapi' (https://github.com/intel/ittapi.git) registered for path 'third_party/ittapi' 2025-08-26T19:43:49.8059654Z Submodule 'third_party/kineto' (https://github.com/pytorch/kineto) registered for path 'third_party/kineto' 2025-08-26T19:43:49.8064662Z Submodule 'third_party/kleidiai' (https://github.com/ARM-software/kleidiai.git) registered for path 'third_party/kleidiai' 2025-08-26T19:43:49.8069639Z Submodule 'third_party/mimalloc' (https://github.com/microsoft/mimalloc.git) registered for path 'third_party/mimalloc' 2025-08-26T19:43:49.8074711Z Submodule 'third_party/nlohmann' (https://github.com/nlohmann/json.git) registered for path 'third_party/nlohmann' 2025-08-26T19:43:49.8091500Z Submodule 'third_party/onnx' (https://github.com/onnx/onnx.git) registered for path 'third_party/onnx' 2025-08-26T19:43:49.8096944Z Submodule 'third_party/opentelemetry-cpp' (https://github.com/open-telemetry/opentelemetry-cpp.git) registered for path 'third_party/opentelemetry-cpp' 2025-08-26T19:43:49.8102017Z Submodule 'third_party/pocketfft' (https://github.com/mreineck/pocketfft) registered for path 'third_party/pocketfft' 2025-08-26T19:43:49.8107364Z Submodule 'third_party/protobuf' (https://github.com/protocolbuffers/protobuf.git) registered for path 'third_party/protobuf' 2025-08-26T19:43:49.8112932Z Submodule 'third_party/NNPACK_deps/psimd' (https://github.com/Maratyszcza/psimd.git) registered for path 'third_party/psimd' 2025-08-26T19:43:49.8118756Z Submodule 'third_party/NNPACK_deps/pthreadpool' (https://github.com/Maratyszcza/pthreadpool.git) registered for path 'third_party/pthreadpool' 2025-08-26T19:43:49.8124429Z Submodule 'third_party/pybind11' (https://github.com/pybind/pybind11.git) registered for path 'third_party/pybind11' 2025-08-26T19:43:49.8130502Z Submodule 'third_party/python-peachpy' (https://github.com/malfet/PeachPy.git) registered for path 'third_party/python-peachpy' 2025-08-26T19:43:49.8147395Z Submodule 'third_party/sleef' (https://github.com/shibatch/sleef) registered for path 'third_party/sleef' 2025-08-26T19:43:49.8153329Z Submodule 'third_party/tensorpipe' (https://github.com/pytorch/tensorpipe.git) registered for path 'third_party/tensorpipe' 2025-08-26T19:43:49.8181669Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/android/libs/fbjni'... 2025-08-26T19:43:50.0733564Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FXdiv'... 2025-08-26T19:43:50.0734465Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/FP16'... 2025-08-26T19:43:50.0735201Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NNPACK'... 2025-08-26T19:43:50.0759007Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fmt'... 2025-08-26T19:43:53.3930741Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/benchmark'... 2025-08-26T19:43:53.3932572Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/NVTX'... 2025-08-26T19:43:53.3934289Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention'... 2025-08-26T19:43:53.3935946Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gloo'... 2025-08-26T19:43:53.3937724Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpuinfo'... 2025-08-26T19:43:53.3939430Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep'... 2025-08-26T19:43:53.3941120Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cpp-httplib'... 2025-08-26T19:43:53.3942803Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ittapi'... 2025-08-26T19:43:53.3944459Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kleidiai'... 2025-08-26T19:43:53.3946185Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/gemmlowp/gemmlowp'... 2025-08-26T19:43:53.3947959Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pocketfft'... 2025-08-26T19:43:53.3949616Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cudnn_frontend'... 2025-08-26T19:43:53.3951556Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/googletest'... 2025-08-26T19:43:53.3953213Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/psimd'... 2025-08-26T19:43:53.3954787Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/mimalloc'... 2025-08-26T19:43:53.3956470Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pthreadpool'... 2025-08-26T19:43:53.3958283Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/VulkanMemoryAllocator'... 2025-08-26T19:43:53.3960031Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flatbuffers'... 2025-08-26T19:43:53.4931904Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/protobuf'... 2025-08-26T19:44:10.1345982Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/python-peachpy'... 2025-08-26T19:44:10.1347546Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto'... 2025-08-26T19:44:10.1349071Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/tensorpipe'... 2025-08-26T19:44:10.1350561Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/sleef'... 2025-08-26T19:44:10.1352033Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/pybind11'... 2025-08-26T19:44:10.1353535Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/cutlass'... 2025-08-26T19:44:10.1354980Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm'... 2025-08-26T19:44:10.1356538Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/composable_kernel'... 2025-08-26T19:44:10.1358080Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/onnx'... 2025-08-26T19:44:10.1359492Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter'... 2025-08-26T19:44:10.1360955Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/nlohmann'... 2025-08-26T19:44:10.1362525Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp'... 2025-08-26T19:44:10.2347024Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/XNNPACK'... 2025-08-26T19:44:12.5472444Z Submodule path 'android/libs/fbjni': checked out '7e1e1fe3858c63c251c637ae41a20de425dde96f' 2025-08-26T19:44:12.5589777Z Submodule path 'third_party/FP16': checked out '4dfe081cf6bcd15db339cf2680b9281b8451eeb3' 2025-08-26T19:44:12.5678350Z Submodule path 'third_party/FXdiv': checked out 'b408327ac2a15ec3e43352421954f5b1967701d1' 2025-08-26T19:44:12.5919632Z Submodule path 'third_party/NNPACK': checked out 'c07e3a0400713d546e0dea2d5466dd22ea389c73' 2025-08-26T19:44:12.6682499Z Submodule path 'third_party/NVTX': checked out '2942f167cc30c5e3a44a2aecd5b0d9c07ff61a07' 2025-08-26T19:44:12.7242320Z Submodule path 'third_party/VulkanMemoryAllocator': checked out '1d8f600fd424278486eade7ed3e877c99f0846b1' 2025-08-26T19:44:13.4442961Z Submodule path 'third_party/XNNPACK': checked out '51a0103656eff6fc9bfd39a4597923c4b542c883' 2025-08-26T19:44:13.5993499Z Submodule path 'third_party/aiter': checked out '01aae101b9e5e94d6c16a9514c9fb8df99c93150' 2025-08-26T19:44:13.6012577Z Submodule '3rdparty/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/aiter/3rdparty/composable_kernel' 2025-08-26T19:44:13.6037092Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/aiter/3rdparty/composable_kernel'... 2025-08-26T19:44:17.3015268Z Submodule path 'third_party/aiter/3rdparty/composable_kernel': checked out 'cffe8fa2a442ac8e80dd236a1a5d24fe3d7e0cbf' 2025-08-26T19:44:17.3244368Z Submodule path 'third_party/benchmark': checked out '299e5928955cc62af9968370293b916f5130916f' 2025-08-26T19:44:17.6421208Z Submodule path 'third_party/composable_kernel': checked out '7fe50dc3da2069d6645d9deb8c017a876472a977' 2025-08-26T19:44:17.6967133Z Submodule path 'third_party/cpp-httplib': checked out '3af7f2c16147f3fbc6e4d717032daf505dc1652c' 2025-08-26T19:44:17.7949358Z Submodule path 'third_party/cpuinfo': checked out '5e3d2445e6a84d9599bee2bf78edbb4d80865e1d' 2025-08-26T19:44:17.8383508Z Submodule path 'third_party/cudnn_frontend': checked out 'f937055efc6d414d11f4c6577e3977fe74f35fb6' 2025-08-26T19:44:18.4622202Z Submodule path 'third_party/cutlass': checked out 'e51efbfe18fe4f4cbb66ab814c55bf4aa0185491' 2025-08-26T19:44:18.6017239Z Submodule path 'third_party/fbgemm': checked out '21c7d30c526c0f1ad873ecc632dca6cfa8a69067' 2025-08-26T19:44:18.6038276Z Submodule 'external/asmjit' (https://github.com/asmjit/asmjit.git) registered for path 'third_party/fbgemm/external/asmjit' 2025-08-26T19:44:18.6040901Z Submodule 'external/composable_kernel' (https://github.com/jwfromm/composable_kernel.git) registered for path 'third_party/fbgemm/external/composable_kernel' 2025-08-26T19:44:18.6043297Z Submodule 'external/cpuinfo' (https://github.com/pytorch/cpuinfo) registered for path 'third_party/fbgemm/external/cpuinfo' 2025-08-26T19:44:18.6045872Z Submodule 'external/cutlass' (https://github.com/jwfromm/cutlass) registered for path 'third_party/fbgemm/external/cutlass' 2025-08-26T19:44:18.6048538Z Submodule 'external/googletest' (https://github.com/google/googletest) registered for path 'third_party/fbgemm/external/googletest' 2025-08-26T19:44:18.6051524Z Submodule 'external/hipify_torch' (https://github.com/ROCmSoftwarePlatform/hipify_torch.git) registered for path 'third_party/fbgemm/external/hipify_torch' 2025-08-26T19:44:18.6054083Z Submodule 'external/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/fbgemm/external/json' 2025-08-26T19:44:18.6080837Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/asmjit'... 2025-08-26T19:44:19.9382345Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/hipify_torch'... 2025-08-26T19:44:19.9383949Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cpuinfo'... 2025-08-26T19:44:19.9385425Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/googletest'... 2025-08-26T19:44:19.9937344Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/composable_kernel'... 2025-08-26T19:44:20.0938593Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/cutlass'... 2025-08-26T19:44:20.9884362Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/fbgemm/external/json'... 2025-08-26T19:44:25.8618283Z Submodule path 'third_party/fbgemm/external/asmjit': checked out 'a3199e8857792cd10b7589ff5d58343d2c9008ea' 2025-08-26T19:44:26.1165770Z Submodule path 'third_party/fbgemm/external/composable_kernel': checked out 'b1281b8b08d973a7064f864f47eeb30f3e2596e9' 2025-08-26T19:44:26.2160666Z Submodule path 'third_party/fbgemm/external/cpuinfo': checked out '6543fec09b2f04ac4a666882998b534afc9c1349' 2025-08-26T19:44:26.8242878Z Submodule path 'third_party/fbgemm/external/cutlass': checked out 'b40777404c174b9694a870bff5c13ce6b7f656ad' 2025-08-26T19:44:26.8706795Z Submodule path 'third_party/fbgemm/external/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-08-26T19:44:26.8820848Z Submodule path 'third_party/fbgemm/external/hipify_torch': checked out 'a4337c69fe0e2552a7b7b0669178926beeed828c' 2025-08-26T19:44:26.9832372Z Submodule path 'third_party/fbgemm/external/json': checked out '9cca280a4d0ccf0c08f47a99aa71d1b0e52f8d03' 2025-08-26T19:44:27.0511081Z Submodule path 'third_party/flash-attention': checked out '979702c87a8713a8e0a5e9fee122b90d2ef13be5' 2025-08-26T19:44:27.0528954Z Submodule 'csrc/composable_kernel' (https://github.com/ROCm/composable_kernel.git) registered for path 'third_party/flash-attention/csrc/composable_kernel' 2025-08-26T19:44:27.0531490Z Submodule 'csrc/cutlass' (https://github.com/NVIDIA/cutlass.git) registered for path 'third_party/flash-attention/csrc/cutlass' 2025-08-26T19:44:27.0555921Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/composable_kernel'... 2025-08-26T19:44:30.4430565Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/flash-attention/csrc/cutlass'... 2025-08-26T19:44:30.6794980Z Submodule path 'third_party/flash-attention/csrc/composable_kernel': checked out '888317e698e9803c62bd38568abc9e05d7709f33' 2025-08-26T19:44:31.2393758Z Submodule path 'third_party/flash-attention/csrc/cutlass': checked out 'c506e16788cb08416a4a57e11a9067beeee29420' 2025-08-26T19:44:31.3769250Z Submodule path 'third_party/flatbuffers': checked out 'a2cd1ea3b6d3fee220106b5fed3f7ce8da9eb757' 2025-08-26T19:44:31.4107130Z Submodule path 'third_party/fmt': checked out '40626af88bd7df9a5fb80be7b25ac85b122d6c21' 2025-08-26T19:44:31.4494939Z Submodule path 'third_party/gemmlowp/gemmlowp': checked out '3fb5c176c17c765a3492cd2f0321b0dab712f350' 2025-08-26T19:44:31.4736836Z Submodule path 'third_party/gloo': checked out 'c7b7b022c124d9643957d9bd55f57ac59fce8fa2' 2025-08-26T19:44:31.5183818Z Submodule path 'third_party/googletest': checked out '52eb8108c5bdec04579160ae17225d66034bd723' 2025-08-26T19:44:31.5306037Z Submodule path 'third_party/ideep': checked out '719d8e6cd7f7a0e01b155657526d693acf97c2b3' 2025-08-26T19:44:31.5320970Z Submodule 'mkl-dnn' (https://github.com/intel/mkl-dnn.git) registered for path 'third_party/ideep/mkl-dnn' 2025-08-26T19:44:31.5344106Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/ideep/mkl-dnn'... 2025-08-26T19:44:43.2804118Z Submodule path 'third_party/ideep/mkl-dnn': checked out '8d263e693366ef8db40acc569cc7d8edf644556d' 2025-08-26T19:44:43.3003885Z Submodule path 'third_party/ittapi': checked out 'dec1d23ca65ab069d225dfe40dea14f455170959' 2025-08-26T19:44:43.3890315Z Submodule path 'third_party/kineto': checked out '5e7501833f1021ce6f618572d3baf657b6319658' 2025-08-26T19:44:43.3907987Z Submodule 'libkineto/third_party/dynolog' (https://github.com/facebookincubator/dynolog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T19:44:43.3910192Z Submodule 'libkineto/third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/fmt' 2025-08-26T19:44:43.3912776Z Submodule 'libkineto/third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/googletest' 2025-08-26T19:44:43.3939403Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog'... 2025-08-26T19:44:44.4008849Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/fmt'... 2025-08-26T19:44:44.8116269Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/googletest'... 2025-08-26T19:44:44.8941399Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog': checked out '7d04a0053a845370ae06ce317a22a48e9edcc74e' 2025-08-26T19:44:44.8957615Z Submodule 'third_party/DCGM' (https://github.com/NVIDIA/DCGM.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T19:44:44.8960087Z Submodule 'third_party/cpr' (https://github.com/libcpr/cpr.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T19:44:44.8962583Z Submodule 'third_party/fmt' (https://github.com/fmtlib/fmt.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-08-26T19:44:44.8965176Z Submodule 'third_party/gflags' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-08-26T19:44:44.8967815Z Submodule 'third_party/glog' (https://github.com/google/glog.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-08-26T19:44:44.8971334Z Submodule 'third_party/googletest' (https://github.com/google/googletest.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-08-26T19:44:44.8973699Z Submodule 'third_party/json' (https://github.com/nlohmann/json.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-08-26T19:44:44.8976601Z Submodule 'third_party/pfs' (https://github.com/dtrugman/pfs.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-08-26T19:44:44.9004372Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM'... 2025-08-26T19:44:46.4369554Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/pfs'... 2025-08-26T19:44:46.4370844Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags'... 2025-08-26T19:44:46.4372093Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/cpr'... 2025-08-26T19:44:46.4373291Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/glog'... 2025-08-26T19:44:46.4374540Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/googletest'... 2025-08-26T19:44:46.4375755Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/fmt'... 2025-08-26T19:44:46.5370046Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/json'... 2025-08-26T19:44:53.0478915Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM': checked out 'ffde4e54bc7249a6039a5e6b45b395141e1217f9' 2025-08-26T19:44:53.0651956Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr': checked out '871ed52d350214a034f6ef8a3b8f51c5ce1bd400' 2025-08-26T19:44:53.1012920Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt': checked out 'cd4af11efc9c622896a3e4cb599fa28668ca3d05' 2025-08-26T19:44:53.1144058Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags': checked out 'e171aa2d15ed9eb17054558e0b3a6a413bb01067' 2025-08-26T19:44:53.1158900Z Submodule 'doc' (https://github.com/gflags/gflags.git) registered for path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-08-26T19:44:53.1182105Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc'... 2025-08-26T19:44:53.4222158Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc': checked out '8411df715cf522606e3b1aca386ddfc0b63d34b4' 2025-08-26T19:44:53.4404784Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog': checked out 'b33e3bad4c46c8a6345525fd822af355e5ef9446' 2025-08-26T19:44:53.4801495Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest': checked out '58d77fa8070e8cec2dc1ed015d66b454c8d78850' 2025-08-26T19:44:53.5786917Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/json': checked out '4f8fba14066156b73f1189a2b8bd568bde5284c5' 2025-08-26T19:44:53.5950724Z Submodule path 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs': checked out 'f68a2fa8ea36c783bdd760371411fcb495aa3150' 2025-08-26T19:44:53.6339191Z Submodule path 'third_party/kineto/libkineto/third_party/fmt': checked out '0041a40c1350ba702d475b9c4ad62da77caea164' 2025-08-26T19:44:53.6918624Z Submodule path 'third_party/kineto/libkineto/third_party/googletest': checked out '7aca84427f224eeed3144123d5230d5871e93347' 2025-08-26T19:44:53.7338886Z Submodule path 'third_party/kleidiai': checked out 'cca02c2f69dd18e1f12647c1c0bdc8cf90e680c7' 2025-08-26T19:44:53.7718989Z Submodule path 'third_party/mimalloc': 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2025-08-26T19:44:55.2958848Z Submodule 'third_party/prometheus-cpp' (https://github.com/jupp0r/prometheus-cpp) registered for path 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T19:44:55.2961641Z Submodule 'tools/vcpkg' (https://github.com/Microsoft/vcpkg) registered for path 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T19:44:55.2988028Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/benchmark'... 2025-08-26T19:44:55.7121717Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentracing-cpp'... 2025-08-26T19:44:55.7122933Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/opentelemetry-proto'... 2025-08-26T19:44:55.7124093Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/prometheus-cpp'... 2025-08-26T19:44:55.7125200Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/ms-gsl'... 2025-08-26T19:44:55.8123247Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/googletest'... 2025-08-26T19:44:56.4784692Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/third_party/nlohmann-json'... 2025-08-26T19:45:04.7999305Z Cloning into '/home/ec2-user/actions-runner/_work/pytorch/pytorch/third_party/opentelemetry-cpp/tools/vcpkg'... 2025-08-26T19:45:04.8185448Z Submodule path 'third_party/opentelemetry-cpp/third_party/benchmark': checked out 'd572f4777349d43653b21d6c2fc63020ab326db2' 2025-08-26T19:45:04.8585873Z Submodule path 'third_party/opentelemetry-cpp/third_party/googletest': checked out 'b796f7d44681514f58a683a3a71ff17c94edb0c1' 2025-08-26T19:45:04.8752026Z Submodule path 'third_party/opentelemetry-cpp/third_party/ms-gsl': checked out 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2025-08-26T19:45:11.4704799Z [command]/usr/bin/git submodule foreach --recursive sh -c "git config --local 'http.https://github.com/.extraheader' 'AUTHORIZATION: basic ***' && git config --local --show-origin --name-only --get-regexp remote.origin.url" 2025-08-26T19:45:11.4984306Z Entering 'android/libs/fbjni' 2025-08-26T19:45:11.5032341Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/android/libs/fbjni/config remote.origin.url 2025-08-26T19:45:11.5047887Z Entering 'third_party/FP16' 2025-08-26T19:45:11.5095525Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FP16/config remote.origin.url 2025-08-26T19:45:11.5110515Z Entering 'third_party/FXdiv' 2025-08-26T19:45:11.5158888Z file:/home/ec2-user/actions-runner/_work/pytorch/pytorch/.git/modules/third_party/NNPACK_deps/FXdiv/config remote.origin.url 2025-08-26T19:45:11.5173268Z Entering 'third_party/NNPACK' 2025-08-26T19:45:11.5219964Z 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2025-08-26T19:45:12.2880026Z Entering 'third_party/mimalloc' 2025-08-26T19:45:12.2919047Z Entering 'third_party/nlohmann' 2025-08-26T19:45:12.2959528Z Entering 'third_party/onnx' 2025-08-26T19:45:12.3016556Z Entering 'third_party/onnx/third_party/pybind11' 2025-08-26T19:45:12.3057602Z Entering 'third_party/opentelemetry-cpp' 2025-08-26T19:45:12.3098221Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-08-26T19:45:12.3136510Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-08-26T19:45:12.3174450Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-08-26T19:45:12.3211766Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-08-26T19:45:12.3252221Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-08-26T19:45:12.3288987Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-08-26T19:45:12.3326418Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T19:45:12.3364139Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-08-26T19:45:12.3402831Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-08-26T19:45:12.3442519Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T19:45:12.3499307Z Entering 'third_party/pocketfft' 2025-08-26T19:45:12.3539460Z Entering 'third_party/protobuf' 2025-08-26T19:45:12.3581650Z Entering 'third_party/protobuf/third_party/benchmark' 2025-08-26T19:45:12.3618878Z Entering 'third_party/protobuf/third_party/googletest' 2025-08-26T19:45:12.3667908Z Entering 'third_party/psimd' 2025-08-26T19:45:12.3699278Z Entering 'third_party/pthreadpool' 2025-08-26T19:45:12.3738205Z Entering 'third_party/pybind11' 2025-08-26T19:45:12.3777643Z Entering 'third_party/python-peachpy' 2025-08-26T19:45:12.3816300Z Entering 'third_party/sleef' 2025-08-26T19:45:12.3855589Z Entering 'third_party/tensorpipe' 2025-08-26T19:45:12.3894424Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-08-26T19:45:12.3931953Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-08-26T19:45:12.3969378Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-08-26T19:45:12.4006501Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-08-26T19:45:12.4043914Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-08-26T19:45:12.4097492Z [command]/usr/bin/git submodule foreach --recursive git config --local --add 'url.https://github.com/.insteadOf' 'org-21003710@github.com:' 2025-08-26T19:45:12.4376995Z Entering 'android/libs/fbjni' 2025-08-26T19:45:12.4415365Z Entering 'third_party/FP16' 2025-08-26T19:45:12.4455717Z Entering 'third_party/FXdiv' 2025-08-26T19:45:12.4494872Z Entering 'third_party/NNPACK' 2025-08-26T19:45:12.4534633Z Entering 'third_party/NVTX' 2025-08-26T19:45:12.4574153Z Entering 'third_party/VulkanMemoryAllocator' 2025-08-26T19:45:12.4614391Z Entering 'third_party/XNNPACK' 2025-08-26T19:45:12.4668309Z Entering 'third_party/aiter' 2025-08-26T19:45:12.4708552Z Entering 'third_party/aiter/3rdparty/composable_kernel' 2025-08-26T19:45:12.4756448Z Entering 'third_party/benchmark' 2025-08-26T19:45:12.4795087Z Entering 'third_party/composable_kernel' 2025-08-26T19:45:12.4843687Z Entering 'third_party/cpp-httplib' 2025-08-26T19:45:12.4881693Z Entering 'third_party/cpuinfo' 2025-08-26T19:45:12.4921080Z Entering 'third_party/cudnn_frontend' 2025-08-26T19:45:12.4960367Z Entering 'third_party/cutlass' 2025-08-26T19:45:12.5008495Z Entering 'third_party/fbgemm' 2025-08-26T19:45:12.5051165Z Entering 'third_party/fbgemm/external/asmjit' 2025-08-26T19:45:12.5088293Z Entering 'third_party/fbgemm/external/composable_kernel' 2025-08-26T19:45:12.5132992Z Entering 'third_party/fbgemm/external/cpuinfo' 2025-08-26T19:45:12.5171365Z Entering 'third_party/fbgemm/external/cutlass' 2025-08-26T19:45:12.5216859Z Entering 'third_party/fbgemm/external/googletest' 2025-08-26T19:45:12.5254227Z Entering 'third_party/fbgemm/external/hipify_torch' 2025-08-26T19:45:12.5291578Z Entering 'third_party/fbgemm/external/json' 2025-08-26T19:45:12.5332647Z Entering 'third_party/flash-attention' 2025-08-26T19:45:12.5372682Z Entering 'third_party/flash-attention/csrc/composable_kernel' 2025-08-26T19:45:12.5416644Z Entering 'third_party/flash-attention/csrc/cutlass' 2025-08-26T19:45:12.5463958Z Entering 'third_party/flatbuffers' 2025-08-26T19:45:12.5505183Z Entering 'third_party/fmt' 2025-08-26T19:45:12.5545575Z Entering 'third_party/gemmlowp/gemmlowp' 2025-08-26T19:45:12.5584266Z Entering 'third_party/gloo' 2025-08-26T19:45:12.5623235Z Entering 'third_party/googletest' 2025-08-26T19:45:12.5662452Z Entering 'third_party/ideep' 2025-08-26T19:45:12.5700556Z Entering 'third_party/ideep/mkl-dnn' 2025-08-26T19:45:12.5746213Z Entering 'third_party/ittapi' 2025-08-26T19:45:12.5784975Z Entering 'third_party/kineto' 2025-08-26T19:45:12.5851832Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T19:45:12.5889730Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T19:45:12.5930821Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T19:45:12.5970416Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-08-26T19:45:12.6008454Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-08-26T19:45:12.6046120Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-08-26T19:45:12.6085884Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-08-26T19:45:12.6123903Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-08-26T19:45:12.6162340Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-08-26T19:45:12.6201683Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-08-26T19:45:12.6241587Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-08-26T19:45:12.6279345Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-08-26T19:45:12.6318717Z Entering 'third_party/kleidiai' 2025-08-26T19:45:12.6359516Z Entering 'third_party/mimalloc' 2025-08-26T19:45:12.6398966Z Entering 'third_party/nlohmann' 2025-08-26T19:45:12.6439191Z Entering 'third_party/onnx' 2025-08-26T19:45:12.6496824Z Entering 'third_party/onnx/third_party/pybind11' 2025-08-26T19:45:12.6537317Z Entering 'third_party/opentelemetry-cpp' 2025-08-26T19:45:12.6578386Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-08-26T19:45:12.6615544Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-08-26T19:45:12.6652942Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-08-26T19:45:12.6689690Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-08-26T19:45:12.6728465Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-08-26T19:45:12.6765552Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-08-26T19:45:12.6803442Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T19:45:12.6841060Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-08-26T19:45:12.6880646Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-08-26T19:45:12.6920189Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T19:45:12.6978262Z Entering 'third_party/pocketfft' 2025-08-26T19:45:12.7017254Z Entering 'third_party/protobuf' 2025-08-26T19:45:12.7060317Z Entering 'third_party/protobuf/third_party/benchmark' 2025-08-26T19:45:12.7097496Z Entering 'third_party/protobuf/third_party/googletest' 2025-08-26T19:45:12.7138606Z Entering 'third_party/psimd' 2025-08-26T19:45:12.7177049Z Entering 'third_party/pthreadpool' 2025-08-26T19:45:12.7215811Z Entering 'third_party/pybind11' 2025-08-26T19:45:12.7257134Z Entering 'third_party/python-peachpy' 2025-08-26T19:45:12.7296239Z Entering 'third_party/sleef' 2025-08-26T19:45:12.7335634Z Entering 'third_party/tensorpipe' 2025-08-26T19:45:12.7375284Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-08-26T19:45:12.7412711Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-08-26T19:45:12.7451455Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-08-26T19:45:12.7489096Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-08-26T19:45:12.7527061Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-08-26T19:45:12.7577702Z ##[endgroup] 2025-08-26T19:45:12.7611253Z [command]/usr/bin/git log -1 --format=%H 2025-08-26T19:45:12.7631399Z 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:45:12.7824053Z Prepare all required actions 2025-08-26T19:45:12.7824643Z Getting action download info 2025-08-26T19:45:12.9773895Z ##[group]Run ./.github/actions/setup-linux 2025-08-26T19:45:12.9774252Z env: 2025-08-26T19:45:12.9774488Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:12.9774752Z ##[endgroup] 2025-08-26T19:45:12.9822425Z ##[group]Run set -euo pipefail 2025-08-26T19:45:12.9822792Z set -euo pipefail 2025-08-26T19:45:12.9823110Z function get_ec2_metadata() { 2025-08-26T19:45:12.9823500Z  # Pulled from instance metadata endpoint for EC2 2025-08-26T19:45:12.9824164Z  # see https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/instancedata-data-retrieval.html 2025-08-26T19:45:12.9824755Z  category=$1 2025-08-26T19:45:12.9825139Z  # If it is GCP runner (runner name contains gcp), do not run this 2025-08-26T19:45:12.9825590Z  runner_name_str=i-04da9546f7741a2d4 2025-08-26T19:45:12.9826157Z  if [[ -f /.inarc ]]; then 2025-08-26T19:45:12.9826526Z  echo "ARC Runner, no info on ec2 metadata" 2025-08-26T19:45:12.9826929Z  elif [[ $runner_name_str == *"gcp"* ]]; then 2025-08-26T19:45:12.9827430Z  echo "Runner is from Google Cloud Platform, No info on ec2 metadata" 2025-08-26T19:45:12.9827883Z  else 2025-08-26T19:45:12.9828797Z  curl -H "X-aws-ec2-metadata-token: $(curl -s -X PUT "http://169.254.169.254/latest/api/token" -H "X-aws-ec2-metadata-token-ttl-seconds: 30")" -fsSL "http://169.254.169.254/latest/meta-data/${category}" 2025-08-26T19:45:12.9829765Z  fi 2025-08-26T19:45:12.9829980Z } 2025-08-26T19:45:12.9830258Z echo "ami-id: $(get_ec2_metadata ami-id)" 2025-08-26T19:45:12.9830711Z echo "instance-id: $(get_ec2_metadata instance-id)" 2025-08-26T19:45:12.9831214Z echo "instance-type: $(get_ec2_metadata instance-type)" 2025-08-26T19:45:12.9831646Z echo "system info $(uname -a)" 2025-08-26T19:45:12.9839891Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:12.9840302Z env: 2025-08-26T19:45:12.9840530Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:12.9840795Z ##[endgroup] 2025-08-26T19:45:12.9987788Z ami-id: ami-05ffe3c48a9991133 2025-08-26T19:45:13.0084449Z instance-id: i-04da9546f7741a2d4 2025-08-26T19:45:13.0180357Z instance-type: c5.4xlarge 2025-08-26T19:45:13.0190265Z system info Linux ip-10-0-28-8.ec2.internal 6.1.141-155.222.amzn2023.x86_64 #1 SMP PREEMPT_DYNAMIC Tue Jun 17 10:29:47 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux 2025-08-26T19:45:13.0221315Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T19:45:13.0222306Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T19:45:13.0228294Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:13.0228718Z env: 2025-08-26T19:45:13.0228937Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:13.0229214Z ##[endgroup] 2025-08-26T19:45:13.0286923Z ##[group]Run if systemctl is-active --quiet docker; then 2025-08-26T19:45:13.0287421Z if systemctl is-active --quiet docker; then 2025-08-26T19:45:13.0287837Z  echo "Docker daemon is running..."; 2025-08-26T19:45:13.0288228Z else 2025-08-26T19:45:13.0288592Z  echo "Starting docker daemon..." && sudo systemctl start docker; 2025-08-26T19:45:13.0289148Z fi 2025-08-26T19:45:13.0294621Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:13.0295026Z env: 2025-08-26T19:45:13.0295253Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:13.0295533Z ##[endgroup] 2025-08-26T19:45:13.0368569Z Docker daemon is running... 2025-08-26T19:45:13.0415492Z ##[group]Run nick-fields/retry@v3.0.0 2025-08-26T19:45:13.0415814Z with: 2025-08-26T19:45:13.0416029Z shell: bash 2025-08-26T19:45:13.0416427Z timeout_minutes: 5 2025-08-26T19:45:13.0416689Z max_attempts: 3 2025-08-26T19:45:13.0416940Z retry_wait_seconds: 30 2025-08-26T19:45:13.0419346Z command: AWS_ACCOUNT_ID=$(aws sts get-caller-identity|grep Account|cut -f4 -d\") aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" # For LF Runners we need to make sure we also login to Meta's ECR docker registry too. META_AWS_ACCOUNT_ID=308535385114 if [ "$AWS_ACCOUNT_ID" != "$META_AWS_ACCOUNT_ID" ] ; then aws ecr get-login-password --region "$AWS_DEFAULT_REGION" | docker login --username AWS \ --password-stdin "$META_AWS_ACCOUNT_ID.dkr.ecr.$AWS_DEFAULT_REGION.amazonaws.com" fi 2025-08-26T19:45:13.0421797Z polling_interval_seconds: 1 2025-08-26T19:45:13.0422099Z warning_on_retry: true 2025-08-26T19:45:13.0422376Z continue_on_error: false 2025-08-26T19:45:13.0422741Z env: 2025-08-26T19:45:13.0422968Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:13.0423251Z AWS_RETRY_MODE: standard 2025-08-26T19:45:13.0423527Z AWS_MAX_ATTEMPTS: 5 2025-08-26T19:45:13.0423785Z AWS_DEFAULT_REGION: us-east-1 2025-08-26T19:45:13.0424075Z ##[endgroup] 2025-08-26T19:45:14.1724574Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-08-26T19:45:14.1725666Z Configure a credential helper to remove this warning. See 2025-08-26T19:45:14.1726273Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-08-26T19:45:14.1726712Z 2025-08-26T19:45:14.1726807Z Login Succeeded 2025-08-26T19:45:14.6906018Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-08-26T19:45:14.6906814Z Configure a credential helper to remove this warning. See 2025-08-26T19:45:14.6907477Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-08-26T19:45:14.6907883Z 2025-08-26T19:45:14.6908022Z Login Succeeded 2025-08-26T19:45:15.1241890Z Command completed after 1 attempt(s). 2025-08-26T19:45:15.1300285Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-08-26T19:45:15.1300855Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-08-26T19:45:15.1301348Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-08-26T19:45:15.1308034Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:15.1308441Z env: 2025-08-26T19:45:15.1308662Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:15.1308946Z ##[endgroup] 2025-08-26T19:45:15.1400407Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T19:45:15.1401005Z # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T19:45:15.1401448Z # shellcheck disable=SC2046 2025-08-26T19:45:15.1401801Z docker stop $(docker ps -q) || true 2025-08-26T19:45:15.1402164Z # Prune all of the docker images 2025-08-26T19:45:15.1402540Z docker system prune -af 2025-08-26T19:45:15.1407914Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:15.1408311Z env: 2025-08-26T19:45:15.1408541Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:15.1408929Z ##[endgroup] 2025-08-26T19:45:15.1640635Z "docker stop" requires at least 1 argument. 2025-08-26T19:45:15.1641275Z See 'docker stop --help'. 2025-08-26T19:45:15.1641583Z 2025-08-26T19:45:15.1641906Z Usage: docker stop [OPTIONS] CONTAINER [CONTAINER...] 2025-08-26T19:45:15.1642471Z 2025-08-26T19:45:15.1642686Z Stop one or more running containers 2025-08-26T19:45:15.1812944Z Total reclaimed space: 0B 2025-08-26T19:45:15.1851091Z ##[group]Run set +e 2025-08-26T19:45:15.1851387Z set +e 2025-08-26T19:45:15.1851634Z set -x 2025-08-26T19:45:15.1851878Z  2025-08-26T19:45:15.1852135Z PT_DOMAIN=download.pytorch.org 2025-08-26T19:45:15.1852737Z # TODO: Flaky access to download.pytorch.org https://github.com/pytorch/pytorch/issues/100400, 2025-08-26T19:45:15.1853765Z # cleaning this up once the issue is fixed. There are more than one resolved IP here, the last 2025-08-26T19:45:15.1854390Z # one is returned at random 2025-08-26T19:45:15.1854814Z RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" | tail -n1) 2025-08-26T19:45:15.1855217Z  2025-08-26T19:45:15.1855450Z if [ -z "${RESOLVED_IP}" ]; then 2025-08-26T19:45:15.1855907Z  echo "Couldn't resolve ${PT_DOMAIN}, retrying with Google DNS..." 2025-08-26T19:45:15.1856460Z  RESOLVED_IP=$(dig -4 +short "${PT_DOMAIN}" @8.8.8.8 | tail -n1) 2025-08-26T19:45:15.1856877Z  2025-08-26T19:45:15.1857124Z  if [ -z "${RESOLVED_IP}" ]; then 2025-08-26T19:45:15.1857520Z  echo "Couldn't resolve ${PT_DOMAIN}, exiting..." 2025-08-26T19:45:15.1857905Z  exit 1 2025-08-26T19:45:15.1858153Z  fi 2025-08-26T19:45:15.1858380Z fi 2025-08-26T19:45:15.1858677Z  2025-08-26T19:45:15.1858959Z if grep -r "${PT_DOMAIN}" /etc/hosts; then 2025-08-26T19:45:15.1859349Z  # Clean up any old records first 2025-08-26T19:45:15.1859735Z  sudo sed -i "/${PT_DOMAIN}/d" /etc/hosts 2025-08-26T19:45:15.1860068Z fi 2025-08-26T19:45:15.1860294Z  2025-08-26T19:45:15.1860625Z echo "${RESOLVED_IP} ${PT_DOMAIN}" | sudo tee -a /etc/hosts 2025-08-26T19:45:15.1861051Z cat /etc/hosts 2025-08-26T19:45:15.1866987Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:15.1867388Z env: 2025-08-26T19:45:15.1867620Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:15.1867901Z ##[endgroup] 2025-08-26T19:45:15.1890008Z + PT_DOMAIN=download.pytorch.org 2025-08-26T19:45:15.1894822Z ++ dig -4 +short download.pytorch.org 2025-08-26T19:45:15.1895621Z ++ tail -n1 2025-08-26T19:45:15.2317374Z + RESOLVED_IP=18.160.10.36 2025-08-26T19:45:15.2317791Z + '[' -z 18.160.10.36 ']' 2025-08-26T19:45:15.2318134Z + grep -r download.pytorch.org /etc/hosts 2025-08-26T19:45:15.2331920Z + echo '18.160.10.36 download.pytorch.org' 2025-08-26T19:45:15.2332339Z + sudo tee -a /etc/hosts 2025-08-26T19:45:15.5279188Z 18.160.10.36 download.pytorch.org 2025-08-26T19:45:15.5294270Z + cat /etc/hosts 2025-08-26T19:45:15.5302484Z 127.0.0.1 localhost localhost.localdomain localhost4 localhost4.localdomain4 2025-08-26T19:45:15.5307883Z ::1 localhost6 localhost6.localdomain6 2025-08-26T19:45:15.5308305Z 18.160.10.36 download.pytorch.org 2025-08-26T19:45:15.5489273Z ##[group]Run pytorch/test-infra/.github/actions/calculate-docker-image@main 2025-08-26T19:45:15.5489796Z with: 2025-08-26T19:45:15.5490574Z docker-image-name: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5491463Z use-custom-docker-registry: true 2025-08-26T19:45:15.5491785Z docker-build-dir: .ci/docker 2025-08-26T19:45:15.5492120Z docker-build-script: ./build.sh 2025-08-26T19:45:15.5492434Z working-directory: . 2025-08-26T19:45:15.5492808Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:15.5493221Z force-push: false 2025-08-26T19:45:15.5493465Z env: 2025-08-26T19:45:15.5493693Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:15.5493969Z ##[endgroup] 2025-08-26T19:45:15.5521716Z ##[group]Run set -ex 2025-08-26T19:45:15.5522038Z set -ex 2025-08-26T19:45:15.5522276Z  2025-08-26T19:45:15.5522728Z # If the docker build directory or the build script doesn't exist, the action will 2025-08-26T19:45:15.5523439Z # gracefully return the docker image name as it is. Pulling docker image in Linux 2025-08-26T19:45:15.5524035Z # job could then download the pre-built image as usual 2025-08-26T19:45:15.5524768Z if [[ -d "${DOCKER_BUILD_DIR}" ]] && [[ -f "${DOCKER_BUILD_DIR}/${DOCKER_BUILD_SCRIPT}" ]] && [[ "${USE_CUSTOM_DOCKER_REGISTRY}" == "true" ]]; then 2025-08-26T19:45:15.5525466Z  echo "skip=false" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5525816Z else 2025-08-26T19:45:15.5526092Z  echo "skip=true" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5526548Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5526979Z  2025-08-26T19:45:15.5527567Z  echo "Not using custom ECR registry. Either it was not requested or there is no Docker build script in the ${REPO_NAME} repo..." 2025-08-26T19:45:15.5528247Z  exit 0 2025-08-26T19:45:15.5528471Z fi 2025-08-26T19:45:15.5528791Z  2025-08-26T19:45:15.5529161Z if [[ "${DOCKER_IMAGE_NAME}" == *"${DOCKER_REGISTRY}/${REPO_NAME}"* ]]; then 2025-08-26T19:45:15.5529804Z  # The docker image name already includes the ECR prefix and tag, so we can just 2025-08-26T19:45:15.5530374Z  # use it as it is, but first let's extract the tag 2025-08-26T19:45:15.5531009Z  DOCKER_TAG=$(echo "${DOCKER_IMAGE_NAME}" | awk -F '[:,]' '{print $2}') 2025-08-26T19:45:15.5531551Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5532073Z  echo "docker-image=${DOCKER_IMAGE_NAME}" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5532505Z else 2025-08-26T19:45:15.5532785Z  if [[ "${DOCKER_IMAGE_NAME}" == *:* ]]; then 2025-08-26T19:45:15.5533177Z  CUSTOM_TAG_PREFIX=${DOCKER_IMAGE_NAME#*:} 2025-08-26T19:45:15.5533599Z  DOCKER_IMAGE_NAME=${DOCKER_IMAGE_NAME%%:*} 2025-08-26T19:45:15.5533954Z  fi 2025-08-26T19:45:15.5534432Z  DOCKER_TAG=${CUSTOM_TAG_PREFIX:+${CUSTOM_TAG_PREFIX}-}$(git rev-parse HEAD:"${DOCKER_BUILD_DIR}") 2025-08-26T19:45:15.5535062Z  echo "docker-tag=${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5535737Z  echo "docker-image=${DOCKER_REGISTRY}/${REPO_NAME}/${DOCKER_IMAGE_NAME}:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5536490Z  echo "custom-tag-prefix=${CUSTOM_TAG_PREFIX}" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5536946Z fi 2025-08-26T19:45:15.5544704Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:15.5545097Z env: 2025-08-26T19:45:15.5545334Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:15.5545621Z REPO_NAME: pytorch 2025-08-26T19:45:15.5546563Z DOCKER_IMAGE_NAME: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5547438Z DOCKER_BUILD_DIR: .ci/docker 2025-08-26T19:45:15.5547736Z DOCKER_BUILD_SCRIPT: ./build.sh 2025-08-26T19:45:15.5548146Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:15.5548584Z USE_CUSTOM_DOCKER_REGISTRY: true 2025-08-26T19:45:15.5548904Z CUSTOM_TAG_PREFIX: 2025-08-26T19:45:15.5549152Z ##[endgroup] 2025-08-26T19:45:15.5573404Z + [[ -d .ci/docker ]] 2025-08-26T19:45:15.5573719Z + [[ -f .ci/docker/./build.sh ]] 2025-08-26T19:45:15.5574038Z + [[ true == \t\r\u\e ]] 2025-08-26T19:45:15.5574325Z + echo skip=false 2025-08-26T19:45:15.5575407Z + [[ 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 == *\3\0\8\5\3\5\3\8\5\1\1\4\.\d\k\r\.\e\c\r\.\u\s\-\e\a\s\t\-\1\.\a\m\a\z\o\n\a\w\s\.\c\o\m\/\p\y\t\o\r\c\h* ]] 2025-08-26T19:45:15.5579838Z ++ echo 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5580705Z ++ awk -F '[:,]' '{print $2}' 2025-08-26T19:45:15.5599852Z + DOCKER_TAG=pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5600715Z + echo docker-tag=pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5601954Z + echo docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5633220Z ##[group]Run set +e 2025-08-26T19:45:15.5633541Z set +e 2025-08-26T19:45:15.5633784Z set -x 2025-08-26T19:45:15.5634023Z  2025-08-26T19:45:15.5634233Z login() { 2025-08-26T19:45:15.5634739Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-08-26T19:45:15.5635293Z } 2025-08-26T19:45:15.5635518Z  2025-08-26T19:45:15.5635737Z retry () { 2025-08-26T19:45:15.5636030Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-08-26T19:45:15.5636364Z } 2025-08-26T19:45:15.5636582Z  2025-08-26T19:45:15.5636820Z retry login "${DOCKER_REGISTRY}" 2025-08-26T19:45:15.5637147Z  2025-08-26T19:45:15.5637610Z START_TIME=$(date +%s) 2025-08-26T19:45:15.5637955Z # Wait up to 120 minutes 2025-08-26T19:45:15.5638347Z while [[ $(( $(date +%s) - 7200 )) -lt $START_TIME ]]; do 2025-08-26T19:45:15.5639011Z  # Check if image already exists, if it does then skip building it 2025-08-26T19:45:15.5639543Z  if docker manifest inspect "${DOCKER_IMAGE}"; then 2025-08-26T19:45:15.5639936Z  exit 0 2025-08-26T19:45:15.5640189Z  fi 2025-08-26T19:45:15.5640403Z  2025-08-26T19:45:15.5640807Z  # NB: This flag is used by Docker build workflow to push the image to ECR, so we can 2025-08-26T19:45:15.5641517Z  # use this to differentiate between the Docker build and regular build jobs. For the 2025-08-26T19:45:15.5642218Z  # latter, it will wait for the Docker images to become available before continuing 2025-08-26T19:45:15.5642768Z  if [ "${DOCKER_PUSH:-false}" == "true" ]; then 2025-08-26T19:45:15.5643180Z  # It's a Docker build job, let's build the image 2025-08-26T19:45:15.5643548Z  break 2025-08-26T19:45:15.5643795Z  else 2025-08-26T19:45:15.5644159Z  # It's a regular build job, wait for the image to become available 2025-08-26T19:45:15.5644582Z  sleep 300 2025-08-26T19:45:15.5644844Z  fi 2025-08-26T19:45:15.5645073Z done 2025-08-26T19:45:15.5645296Z  2025-08-26T19:45:15.5645654Z # NB: This part requires a full checkout. Otherwise, the merge base will 2025-08-26T19:45:15.5646259Z # be empty. The default action would be to continue rebuild the image 2025-08-26T19:45:15.5646896Z if [[ "$BASE_REVISION" = "$(git rev-parse HEAD)" ]]; then 2025-08-26T19:45:15.5647381Z  # if we're on the base branch then use the parent commit 2025-08-26T19:45:15.5647811Z  MERGE_BASE=$(git rev-parse HEAD~) 2025-08-26T19:45:15.5648131Z else 2025-08-26T19:45:15.5648478Z  # otherwise we're on a PR, so use the most recent base commit 2025-08-26T19:45:15.5649072Z  MERGE_BASE=$(git merge-base HEAD "$BASE_REVISION") 2025-08-26T19:45:15.5649460Z fi 2025-08-26T19:45:15.5649672Z  2025-08-26T19:45:15.5649920Z if [[ -z "${MERGE_BASE}" ]]; then 2025-08-26T19:45:15.5650296Z  echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5650646Z  2025-08-26T19:45:15.5651128Z  echo "Finding merge base only works with full checkout, please set fetch-depth to 0, continuing ..." 2025-08-26T19:45:15.5651713Z  exit 0 2025-08-26T19:45:15.5651958Z fi 2025-08-26T19:45:15.5652188Z  2025-08-26T19:45:15.5652513Z if ! git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}"; then 2025-08-26T19:45:15.5653220Z  echo "Directory '${DOCKER_BUILD_DIR}' not found in commit $MERGE_BASE, you should rebase onto a more recent commit" 2025-08-26T19:45:15.5653840Z  exit 1 2025-08-26T19:45:15.5654078Z fi 2025-08-26T19:45:15.5654297Z  2025-08-26T19:45:15.5654669Z PREVIOUS_DOCKER_TAG=$(git rev-parse "${MERGE_BASE}:${DOCKER_BUILD_DIR}") 2025-08-26T19:45:15.5655371Z # If no image exists but the hash is the same as the previous hash then we should error out here 2025-08-26T19:45:15.5655997Z if [[ "${PREVIOUS_DOCKER_TAG}" == "${DOCKER_TAG}" ]]; then 2025-08-26T19:45:15.5656719Z  echo "WARNING: Something has gone wrong and the previous image isn't available for the merge-base of your branch" 2025-08-26T19:45:15.5657537Z  echo " Will re-build docker image to store in local cache, TTS may be longer" 2025-08-26T19:45:15.5658010Z fi 2025-08-26T19:45:15.5658233Z  2025-08-26T19:45:15.5658512Z echo "rebuild=true" >> "${GITHUB_OUTPUT}" 2025-08-26T19:45:15.5664021Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:15.5664423Z env: 2025-08-26T19:45:15.5664638Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:15.5664930Z DOCKER_BUILD_DIR: .ci/docker 2025-08-26T19:45:15.5665286Z BASE_REVISION: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:45:15.5666273Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5667324Z DOCKER_TAG: pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:15.5667981Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:15.5668394Z DOCKER_PUSH: 2025-08-26T19:45:15.5668633Z ##[endgroup] 2025-08-26T19:45:15.5690153Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:15.5690625Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:15.5692604Z + aws ecr get-login-password --region us-east-1 2025-08-26T19:45:15.5693927Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:16.0942245Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-08-26T19:45:16.0942911Z Configure a credential helper to remove this warning. See 2025-08-26T19:45:16.0943496Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-08-26T19:45:16.0944073Z 2025-08-26T19:45:16.0944228Z Login Succeeded 2025-08-26T19:45:16.0958731Z ++ date +%s 2025-08-26T19:45:16.0967116Z + START_TIME=1756237516 2025-08-26T19:45:16.0970158Z ++ date +%s 2025-08-26T19:45:16.0978552Z + [[ 1756230316 -lt 1756237516 ]] 2025-08-26T19:45:16.0979773Z + docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:16.3030699Z { 2025-08-26T19:45:16.3031033Z "schemaVersion": 2, 2025-08-26T19:45:16.3031538Z "mediaType": "application/vnd.docker.distribution.manifest.v2+json", 2025-08-26T19:45:16.3032007Z "config": { 2025-08-26T19:45:16.3032368Z "mediaType": "application/vnd.docker.container.image.v1+json", 2025-08-26T19:45:16.3032786Z "size": 29883, 2025-08-26T19:45:16.3033257Z "digest": "sha256:bcfee952306a7e44650613e1b9a4dc8a749cc45f82748f17141360b84d5c4b94" 2025-08-26T19:45:16.3033758Z }, 2025-08-26T19:45:16.3033967Z "layers": [ 2025-08-26T19:45:16.3034228Z { 2025-08-26T19:45:16.3034563Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3035014Z "size": 30448173, 2025-08-26T19:45:16.3035469Z "digest": "sha256:660ffc76f83b006444a5731b215acc2e35138d8be5cac8ed1ffd40f947117495" 2025-08-26T19:45:16.3035968Z }, 2025-08-26T19:45:16.3036156Z { 2025-08-26T19:45:16.3036517Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3036957Z "size": 1554, 2025-08-26T19:45:16.3037552Z "digest": "sha256:bc6828dc3a67bd1a0f7dc77dd5b628363201b20ed5e62b20b10984b773009991" 2025-08-26T19:45:16.3038049Z }, 2025-08-26T19:45:16.3038256Z { 2025-08-26T19:45:16.3038607Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3039062Z "size": 344953099, 2025-08-26T19:45:16.3039502Z "digest": "sha256:077c5ccf8634c7f0028234842674c21eb81df6eefca3bc64667b986f7b2d5bf6" 2025-08-26T19:45:16.3040001Z }, 2025-08-26T19:45:16.3040202Z { 2025-08-26T19:45:16.3040542Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3040963Z "size": 791, 2025-08-26T19:45:16.3041395Z "digest": "sha256:c4b66cb3e1458a047d25f65267cd75101a856b69bf7f0e4cf3ab0f5170b80d21" 2025-08-26T19:45:16.3041886Z }, 2025-08-26T19:45:16.3042087Z { 2025-08-26T19:45:16.3042419Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3042855Z "size": 63270193, 2025-08-26T19:45:16.3043298Z "digest": "sha256:be2351a8a9e1090a6c189ac5ab7f9129fcd11333aae23d65624537890b2c5759" 2025-08-26T19:45:16.3043787Z }, 2025-08-26T19:45:16.3043973Z { 2025-08-26T19:45:16.3044312Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3044747Z "size": 704, 2025-08-26T19:45:16.3045172Z "digest": 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"sha256:13792f6142bb7a1ef0a78094cc19143b3302ac9aec9b5b76d8714461dbaec2f7" 2025-08-26T19:45:16.3057731Z }, 2025-08-26T19:45:16.3057935Z { 2025-08-26T19:45:16.3058270Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3058691Z "size": 543, 2025-08-26T19:45:16.3059107Z "digest": "sha256:3926b9c5c75770c2130307a795639924b8f840d9db2c4241e6998a0e61b90cc8" 2025-08-26T19:45:16.3059586Z }, 2025-08-26T19:45:16.3059786Z { 2025-08-26T19:45:16.3060110Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3060546Z "size": 3406041060, 2025-08-26T19:45:16.3060998Z "digest": "sha256:d6ab61cb07e7224b31187c48d8349900f6065a2b9f9cba19bfd0e2cdc24de159" 2025-08-26T19:45:16.3061489Z }, 2025-08-26T19:45:16.3061678Z { 2025-08-26T19:45:16.3062017Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3062448Z "size": 32, 2025-08-26T19:45:16.3062875Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-08-26T19:45:16.3063359Z }, 2025-08-26T19:45:16.3063559Z { 2025-08-26T19:45:16.3063904Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3064339Z "size": 380, 2025-08-26T19:45:16.3064738Z "digest": "sha256:949734882de50eee84240586b92983e08269c7cc3972990206c92cf701576350" 2025-08-26T19:45:16.3065220Z }, 2025-08-26T19:45:16.3065419Z { 2025-08-26T19:45:16.3065758Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3066177Z "size": 104, 2025-08-26T19:45:16.3066615Z "digest": "sha256:ee3cb7b4e1614e673aed386d0cfebfe903646c0116da73af3a1778616d2d919b" 2025-08-26T19:45:16.3067117Z }, 2025-08-26T19:45:16.3067317Z { 2025-08-26T19:45:16.3067648Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3068085Z "size": 230, 2025-08-26T19:45:16.3068520Z "digest": 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"sha256:89159c061439df91ec29e3f3e48866d9e771d319226c7fc35e40b5e31cbef91f" 2025-08-26T19:45:16.3074747Z }, 2025-08-26T19:45:16.3074946Z { 2025-08-26T19:45:16.3075274Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3075712Z "size": 195, 2025-08-26T19:45:16.3076130Z "digest": "sha256:7543369e8f46485c7b09c8798b18ec0d1a6f2ab66828a01876404c2bd5c550c5" 2025-08-26T19:45:16.3076616Z }, 2025-08-26T19:45:16.3076802Z { 2025-08-26T19:45:16.3077139Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3077575Z "size": 608, 2025-08-26T19:45:16.3077990Z "digest": "sha256:f7fc941934c65705930f6f684c120e8423f1520dbec4e2eb6121a48029320408" 2025-08-26T19:45:16.3078460Z }, 2025-08-26T19:45:16.3078731Z { 2025-08-26T19:45:16.3079025Z + exit 0 2025-08-26T19:45:16.3079376Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3079799Z "size": 226, 2025-08-26T19:45:16.3080233Z "digest": 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"sha256:7712da47fe11ebc0505d33e9e9f1cf4fb4e456731ebd6825434a55f52cdb778e" 2025-08-26T19:45:16.3086410Z }, 2025-08-26T19:45:16.3086604Z { 2025-08-26T19:45:16.3086949Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3087394Z "size": 1494, 2025-08-26T19:45:16.3087828Z "digest": "sha256:7e9e15046c34c287b185753510aeb7eec0399b6479246a4042f5ec344eec8374" 2025-08-26T19:45:16.3088308Z }, 2025-08-26T19:45:16.3088514Z { 2025-08-26T19:45:16.3088963Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3089415Z "size": 453959341, 2025-08-26T19:45:16.3089854Z "digest": "sha256:0daf7355ddc950f049f6aa07a0f5e6ca00eb8045f1c543088200a84f7a169f94" 2025-08-26T19:45:16.3090359Z }, 2025-08-26T19:45:16.3090561Z { 2025-08-26T19:45:16.3090913Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3091333Z "size": 163, 2025-08-26T19:45:16.3091756Z "digest": 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"sha256:3bf7eaa748f0e6e09ab53d9562fa3ae9f2a992b8ab4c81bf9fecf2855b08f1df" 2025-08-26T19:45:16.3191924Z }, 2025-08-26T19:45:16.3192120Z { 2025-08-26T19:45:16.3192446Z "mediaType": "application/vnd.docker.image.rootfs.diff.tar.gzip", 2025-08-26T19:45:16.3192878Z "size": 32, 2025-08-26T19:45:16.3193304Z "digest": "sha256:4f4fb700ef54461cfa02571ae0db9a0dc1e0cdb5577484a6d75e68dc38e8acc1" 2025-08-26T19:45:16.3193803Z } 2025-08-26T19:45:16.3193992Z ] 2025-08-26T19:45:16.3194193Z } 2025-08-26T19:45:16.3229367Z ##[group]Run set -eux 2025-08-26T19:45:16.3229654Z set -eux 2025-08-26T19:45:16.3230089Z # It's ok if this steps fails, it would then be an anonymous user like what we used to have 2025-08-26T19:45:16.3231296Z aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token | jq --raw-output '.SecretString' | jq -r .docker_hub_readonly_token | docker login --username pytorchbot --password-stdin || true 2025-08-26T19:45:16.3239710Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:16.3240096Z env: 2025-08-26T19:45:16.3240316Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:16.3240581Z ##[endgroup] 2025-08-26T19:45:16.3267080Z + aws secretsmanager get-secret-value --secret-id docker_hub_readonly_token 2025-08-26T19:45:16.3267623Z + jq --raw-output .SecretString 2025-08-26T19:45:16.3268788Z + jq -r .docker_hub_readonly_token 2025-08-26T19:45:16.3269877Z + docker login --username pytorchbot --password-stdin 2025-08-26T19:45:16.8956074Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-08-26T19:45:16.8956740Z Configure a credential helper to remove this warning. See 2025-08-26T19:45:16.8957592Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-08-26T19:45:16.8958212Z 2025-08-26T19:45:16.8958325Z Login Succeeded 2025-08-26T19:45:16.9045568Z ##[group]Run tag=${ECR_DOCKER_IMAGE##*:} 2025-08-26T19:45:16.9045966Z tag=${ECR_DOCKER_IMAGE##*:} 2025-08-26T19:45:16.9046539Z echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}" 2025-08-26T19:45:16.9053470Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:16.9053876Z env: 2025-08-26T19:45:16.9054107Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:16.9054925Z ECR_DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:16.9055769Z ##[endgroup] 2025-08-26T19:45:16.9080455Z docker pull ghcr.io/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:16.9134067Z ##[group]Run pytorch/test-infra/.github/actions/pull-docker-image@main 2025-08-26T19:45:16.9134518Z with: 2025-08-26T19:45:16.9135270Z docker-image: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:16.9136220Z docker-registry: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:16.9136644Z env: 2025-08-26T19:45:16.9136863Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:16.9137145Z ##[endgroup] 2025-08-26T19:45:16.9161128Z ##[group]Run set -x 2025-08-26T19:45:16.9161410Z set -x 2025-08-26T19:45:16.9161651Z set +e 2025-08-26T19:45:16.9161891Z  2025-08-26T19:45:16.9162098Z login() { 2025-08-26T19:45:16.9162598Z  aws ecr get-login-password --region us-east-1 | docker login -u AWS --password-stdin "$1" 2025-08-26T19:45:16.9163151Z } 2025-08-26T19:45:16.9163368Z  2025-08-26T19:45:16.9163621Z retry () { 2025-08-26T19:45:16.9163907Z  $* || (sleep 1 && $*) || (sleep 2 && $*) 2025-08-26T19:45:16.9164227Z } 2025-08-26T19:45:16.9164443Z  2025-08-26T19:45:16.9164690Z retry login "${DOCKER_REGISTRY}" 2025-08-26T19:45:16.9165014Z  2025-08-26T19:45:16.9165513Z IMAGE_SIZE=$(docker manifest inspect "${DOCKER_IMAGE}" | jq '[.layers[].size, .config.size] | add / 1024 / 1024') 2025-08-26T19:45:16.9166222Z echo "Compressed size of image in MB: ${IMAGE_SIZE}" 2025-08-26T19:45:16.9166617Z  2025-08-26T19:45:16.9166839Z set -e 2025-08-26T19:45:16.9167188Z # ignore output since only exit code is used for conditional 2025-08-26T19:45:16.9167709Z # only pull docker image if it's not available locally 2025-08-26T19:45:16.9168285Z if ! docker inspect --type=image "${DOCKER_IMAGE}" >/dev/null 2>/dev/null; then 2025-08-26T19:45:16.9168945Z  retry docker pull "${DOCKER_IMAGE}" 2025-08-26T19:45:16.9169287Z fi 2025-08-26T19:45:16.9174486Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:45:16.9174886Z env: 2025-08-26T19:45:16.9175116Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:45:16.9175920Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:16.9176860Z DOCKER_REGISTRY: 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:16.9177258Z ##[endgroup] 2025-08-26T19:45:16.9198170Z + set +e 2025-08-26T19:45:16.9198580Z + retry login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:16.9199068Z + login 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:16.9201606Z + aws ecr get-login-password --region us-east-1 2025-08-26T19:45:16.9202845Z + docker login -u AWS --password-stdin 308535385114.dkr.ecr.us-east-1.amazonaws.com 2025-08-26T19:45:17.4346077Z WARNING! Your password will be stored unencrypted in /home/ec2-user/.docker/config.json. 2025-08-26T19:45:17.4346732Z Configure a credential helper to remove this warning. See 2025-08-26T19:45:17.4347341Z https://docs.docker.com/engine/reference/commandline/login/#credentials-store 2025-08-26T19:45:17.4347747Z 2025-08-26T19:45:17.4351955Z Login Succeeded 2025-08-26T19:45:17.4368812Z ++ docker manifest inspect 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:17.4369989Z ++ jq '[.layers[].size, .config.size] | add / 1024 / 1024' 2025-08-26T19:45:17.6373637Z + IMAGE_SIZE=4404.510594367981 2025-08-26T19:45:17.6374070Z + echo 'Compressed size of image in MB: 4404.510594367981' 2025-08-26T19:45:17.6374460Z + set -e 2025-08-26T19:45:17.6374729Z Compressed size of image in MB: 4404.510594367981 2025-08-26T19:45:17.6375944Z + docker inspect --type=image 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:17.6490283Z + retry docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:17.6491675Z + docker pull 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:45:17.9463191Z pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6: Pulling from pytorch/ci-image 2025-08-26T19:45:17.9464400Z 660ffc76f83b: Pulling fs layer 2025-08-26T19:45:17.9464926Z bc6828dc3a67: Pulling fs layer 2025-08-26T19:45:17.9465254Z 077c5ccf8634: Pulling fs layer 2025-08-26T19:45:17.9465679Z c4b66cb3e145: Pulling fs layer 2025-08-26T19:45:17.9466041Z be2351a8a9e1: Pulling fs layer 2025-08-26T19:45:17.9466404Z ac0275b0c502: Pulling fs layer 2025-08-26T19:45:17.9466837Z 12a376ecda84: Pulling fs layer 2025-08-26T19:45:17.9467338Z ab2a2f72897f: Pulling fs layer 2025-08-26T19:45:17.9467892Z 98d248f35952: Pulling fs layer 2025-08-26T19:45:17.9468395Z 03d1105a106a: Pulling fs layer 2025-08-26T19:45:17.9468893Z c6de97442ffc: Pulling fs layer 2025-08-26T19:45:17.9469424Z 13792f6142bb: Pulling fs layer 2025-08-26T19:45:17.9469997Z 3926b9c5c757: Pulling fs layer 2025-08-26T19:45:17.9470477Z d6ab61cb07e7: Pulling fs layer 2025-08-26T19:45:17.9470979Z 4f4fb700ef54: Pulling fs layer 2025-08-26T19:45:17.9471524Z 949734882de5: Pulling fs layer 2025-08-26T19:45:17.9472041Z c4b66cb3e145: Waiting 2025-08-26T19:45:17.9472482Z be2351a8a9e1: Waiting 2025-08-26T19:45:17.9472934Z ee3cb7b4e161: Pulling fs layer 2025-08-26T19:45:17.9473439Z 8e2e9e025db0: Pulling fs layer 2025-08-26T19:45:17.9473819Z f7974c6e740c: Pulling fs layer 2025-08-26T19:45:17.9474105Z ac0275b0c502: Waiting 2025-08-26T19:45:17.9474361Z f69c3f35c384: Pulling fs layer 2025-08-26T19:45:17.9474733Z 03d1105a106a: Waiting 2025-08-26T19:45:17.9475009Z 12a376ecda84: Waiting 2025-08-26T19:45:17.9475395Z c6de97442ffc: Waiting 2025-08-26T19:45:17.9475790Z 98d248f35952: Waiting 2025-08-26T19:45:17.9476254Z 89159c061439: Pulling fs layer 2025-08-26T19:45:17.9476770Z d6ab61cb07e7: Waiting 2025-08-26T19:45:17.9477122Z 949734882de5: Waiting 2025-08-26T19:45:17.9477443Z 7543369e8f46: Pulling fs layer 2025-08-26T19:45:17.9477744Z f7fc941934c6: Pulling fs layer 2025-08-26T19:45:17.9478134Z f655cd3e2552: Pulling fs layer 2025-08-26T19:45:17.9478443Z f69c3f35c384: Waiting 2025-08-26T19:45:17.9478755Z ee3cb7b4e161: Waiting 2025-08-26T19:45:17.9479009Z 8e2e9e025db0: Waiting 2025-08-26T19:45:17.9479269Z 0780d907ae80: Pulling fs layer 2025-08-26T19:45:17.9479555Z f7974c6e740c: Waiting 2025-08-26T19:45:17.9479786Z 89159c061439: Waiting 2025-08-26T19:45:17.9480030Z 7543369e8f46: Waiting 2025-08-26T19:45:17.9480282Z 13792f6142bb: Waiting 2025-08-26T19:45:17.9480542Z 7712da47fe11: Pulling fs layer 2025-08-26T19:45:17.9480813Z 0780d907ae80: Waiting 2025-08-26T19:45:17.9481071Z 7e9e15046c34: Pulling fs layer 2025-08-26T19:45:17.9481354Z f7fc941934c6: Waiting 2025-08-26T19:45:17.9481626Z 0daf7355ddc9: Pulling fs layer 2025-08-26T19:45:17.9481900Z 4f4fb700ef54: Waiting 2025-08-26T19:45:17.9482162Z 0435a6eaf460: Pulling fs layer 2025-08-26T19:45:17.9482443Z 7e9e15046c34: Waiting 2025-08-26T19:45:17.9482698Z f655cd3e2552: Waiting 2025-08-26T19:45:17.9482938Z 0daf7355ddc9: Waiting 2025-08-26T19:45:17.9483204Z e7c2dba69e4c: Pulling fs layer 2025-08-26T19:45:17.9483756Z 7712da47fe11: Waiting 2025-08-26T19:45:17.9483995Z 3926b9c5c757: Waiting 2025-08-26T19:45:17.9484249Z 0435a6eaf460: Waiting 2025-08-26T19:45:17.9484514Z 2b73a19dab76: Pulling fs layer 2025-08-26T19:45:17.9484814Z ed5131773436: Pulling fs layer 2025-08-26T19:45:17.9485097Z d7e9765898f9: Pulling fs layer 2025-08-26T19:45:17.9485385Z 2b73a19dab76: Waiting 2025-08-26T19:45:17.9485642Z e7c2dba69e4c: Waiting 2025-08-26T19:45:17.9485907Z 13c02d1fa95a: Pulling fs layer 2025-08-26T19:45:17.9486179Z d7e9765898f9: Waiting 2025-08-26T19:45:17.9486424Z ed5131773436: Waiting 2025-08-26T19:45:17.9486799Z 13c02d1fa95a: Waiting 2025-08-26T19:45:17.9487068Z c4ac9ebc03ab: Pulling fs layer 2025-08-26T19:45:17.9487350Z c4ac9ebc03ab: Waiting 2025-08-26T19:45:17.9487768Z 0f80df9ec0a8: Pulling fs layer 2025-08-26T19:45:17.9488292Z d773426c510c: Pulling fs layer 2025-08-26T19:45:17.9488924Z bc0360305afd: Pulling fs layer 2025-08-26T19:45:17.9489409Z 0f80df9ec0a8: Waiting 2025-08-26T19:45:17.9489808Z b1b61de995ce: Pulling fs layer 2025-08-26T19:45:17.9490355Z bc0360305afd: Waiting 2025-08-26T19:45:17.9490832Z 69cf1c80c0c4: Pulling fs layer 2025-08-26T19:45:17.9491331Z d773426c510c: Waiting 2025-08-26T19:45:17.9491642Z 69cf1c80c0c4: Waiting 2025-08-26T19:45:17.9492008Z 494516fc2864: Pulling fs layer 2025-08-26T19:45:17.9492366Z b1b61de995ce: Waiting 2025-08-26T19:45:17.9492815Z 73a0967e5609: Pulling fs layer 2025-08-26T19:45:17.9493304Z ec659429b335: Pulling fs layer 2025-08-26T19:45:17.9493771Z 494516fc2864: Waiting 2025-08-26T19:45:17.9494179Z 73a0967e5609: Waiting 2025-08-26T19:45:17.9494572Z ec659429b335: Waiting 2025-08-26T19:45:17.9495024Z 52e8b9613cef: Pulling fs layer 2025-08-26T19:45:17.9495520Z a1435d9de553: Pulling fs layer 2025-08-26T19:45:17.9496018Z 6a8d17e39fba: Pulling fs layer 2025-08-26T19:45:17.9496483Z 52e8b9613cef: Waiting 2025-08-26T19:45:17.9496892Z a1435d9de553: Waiting 2025-08-26T19:45:17.9497156Z 6a8d17e39fba: Waiting 2025-08-26T19:45:17.9497422Z f82de2f9fbbd: Pulling fs layer 2025-08-26T19:45:17.9497721Z c4a1946e885f: Pulling fs layer 2025-08-26T19:45:17.9498005Z f82de2f9fbbd: Waiting 2025-08-26T19:45:17.9498266Z 8150c2b87518: Pulling fs layer 2025-08-26T19:45:17.9498553Z c4a1946e885f: Waiting 2025-08-26T19:45:17.9498965Z b260b8a04e14: Pulling fs layer 2025-08-26T19:45:17.9499455Z 2ba586ae34b9: Pulling fs layer 2025-08-26T19:45:17.9499953Z 1a18b687e3b3: Pulling fs layer 2025-08-26T19:45:17.9500421Z 8150c2b87518: Waiting 2025-08-26T19:45:17.9500808Z b260b8a04e14: Waiting 2025-08-26T19:45:17.9501234Z b627c22edb90: Pulling fs layer 2025-08-26T19:45:17.9501592Z 2ba586ae34b9: Waiting 2025-08-26T19:45:17.9501872Z 434bc8db9244: Pulling fs layer 2025-08-26T19:45:17.9502153Z 19597bcec455: Pulling fs layer 2025-08-26T19:45:17.9502527Z 288706c7e50f: Pulling fs layer 2025-08-26T19:45:17.9502807Z 1a18b687e3b3: Waiting 2025-08-26T19:45:17.9503058Z 434bc8db9244: Waiting 2025-08-26T19:45:17.9503304Z fa5087659588: Pulling fs layer 2025-08-26T19:45:17.9503752Z 288706c7e50f: Waiting 2025-08-26T19:45:17.9504182Z b627c22edb90: Waiting 2025-08-26T19:45:17.9504610Z 5c615319e208: Pulling fs layer 2025-08-26T19:45:17.9505044Z 424f9ce476c8: Pulling fs layer 2025-08-26T19:45:17.9505331Z 19597bcec455: Waiting 2025-08-26T19:45:17.9505595Z d221e08864cf: Pulling fs layer 2025-08-26T19:45:17.9505877Z 424f9ce476c8: Waiting 2025-08-26T19:45:17.9506110Z 5c615319e208: Waiting 2025-08-26T19:45:17.9506353Z fa5087659588: Waiting 2025-08-26T19:45:17.9506615Z 68effbf08d78: Pulling fs layer 2025-08-26T19:45:17.9506899Z d221e08864cf: Waiting 2025-08-26T19:45:17.9507149Z 3bf7eaa748f0: Pulling fs layer 2025-08-26T19:45:17.9507435Z 3bf7eaa748f0: Waiting 2025-08-26T19:45:17.9507698Z 68effbf08d78: Waiting 2025-08-26T19:45:18.0226962Z bc6828dc3a67: Verifying Checksum 2025-08-26T19:45:18.0227335Z bc6828dc3a67: Download complete 2025-08-26T19:45:18.0993782Z c4b66cb3e145: Verifying Checksum 2025-08-26T19:45:18.0994166Z c4b66cb3e145: Download complete 2025-08-26T19:45:18.2880812Z 660ffc76f83b: Verifying Checksum 2025-08-26T19:45:18.2881687Z 660ffc76f83b: Download complete 2025-08-26T19:45:18.3533947Z ac0275b0c502: Download complete 2025-08-26T19:45:18.4326804Z 12a376ecda84: Verifying Checksum 2025-08-26T19:45:18.4327315Z 12a376ecda84: Download complete 2025-08-26T19:45:18.5245516Z ab2a2f72897f: Verifying Checksum 2025-08-26T19:45:18.5246067Z ab2a2f72897f: Download complete 2025-08-26T19:45:18.6043589Z 98d248f35952: Verifying Checksum 2025-08-26T19:45:18.6043997Z 98d248f35952: Download complete 2025-08-26T19:45:18.6774509Z 03d1105a106a: Download complete 2025-08-26T19:45:18.7445345Z c6de97442ffc: Download complete 2025-08-26T19:45:18.7856359Z be2351a8a9e1: Verifying Checksum 2025-08-26T19:45:18.7856980Z be2351a8a9e1: Download complete 2025-08-26T19:45:18.8298392Z 13792f6142bb: Download complete 2025-08-26T19:45:18.8498082Z 3926b9c5c757: Download complete 2025-08-26T19:45:18.8563006Z 4f4fb700ef54: Download complete 2025-08-26T19:45:18.9226955Z 949734882de5: Verifying Checksum 2025-08-26T19:45:18.9227487Z 949734882de5: Download complete 2025-08-26T19:45:18.9978236Z ee3cb7b4e161: Verifying Checksum 2025-08-26T19:45:18.9978632Z ee3cb7b4e161: Download complete 2025-08-26T19:45:19.0721665Z 8e2e9e025db0: Verifying Checksum 2025-08-26T19:45:19.0722065Z 8e2e9e025db0: Download complete 2025-08-26T19:45:19.1227675Z 660ffc76f83b: Pull complete 2025-08-26T19:45:19.1436621Z bc6828dc3a67: Pull complete 2025-08-26T19:45:19.1795168Z f7974c6e740c: Download complete 2025-08-26T19:45:19.2559419Z f69c3f35c384: Verifying Checksum 2025-08-26T19:45:19.3520641Z 89159c061439: Verifying Checksum 2025-08-26T19:45:19.3521031Z 89159c061439: Download complete 2025-08-26T19:45:19.4316967Z 7543369e8f46: Verifying Checksum 2025-08-26T19:45:19.4317534Z 7543369e8f46: Download complete 2025-08-26T19:45:19.4927667Z f7fc941934c6: Verifying Checksum 2025-08-26T19:45:19.4928286Z f7fc941934c6: Download complete 2025-08-26T19:45:19.5914302Z f655cd3e2552: Verifying Checksum 2025-08-26T19:45:19.5914798Z f655cd3e2552: Download complete 2025-08-26T19:45:19.6590307Z 0780d907ae80: Verifying Checksum 2025-08-26T19:45:19.6590762Z 0780d907ae80: Download complete 2025-08-26T19:45:19.7296332Z 7712da47fe11: Download complete 2025-08-26T19:45:19.7954635Z 7e9e15046c34: Download complete 2025-08-26T19:45:21.4384409Z 077c5ccf8634: Verifying Checksum 2025-08-26T19:45:21.4384797Z 077c5ccf8634: Download complete 2025-08-26T19:45:21.6989797Z 0435a6eaf460: Download complete 2025-08-26T19:45:21.7757055Z e7c2dba69e4c: Download complete 2025-08-26T19:45:21.8633025Z 2b73a19dab76: Verifying Checksum 2025-08-26T19:45:21.8633447Z 2b73a19dab76: Download complete 2025-08-26T19:45:21.9796832Z ed5131773436: Verifying Checksum 2025-08-26T19:45:21.9797233Z ed5131773436: Download complete 2025-08-26T19:45:22.2279401Z d7e9765898f9: Download complete 2025-08-26T19:45:22.3134570Z 13c02d1fa95a: Verifying Checksum 2025-08-26T19:45:22.3134974Z 13c02d1fa95a: Download complete 2025-08-26T19:45:22.3687554Z c4ac9ebc03ab: Verifying Checksum 2025-08-26T19:45:22.3687959Z c4ac9ebc03ab: Download complete 2025-08-26T19:45:22.4570635Z 0f80df9ec0a8: Download complete 2025-08-26T19:45:22.5465035Z d773426c510c: Verifying Checksum 2025-08-26T19:45:22.5465427Z d773426c510c: Download complete 2025-08-26T19:45:22.6120000Z bc0360305afd: Download complete 2025-08-26T19:45:22.6911110Z b1b61de995ce: Download complete 2025-08-26T19:45:22.7603575Z 69cf1c80c0c4: Download complete 2025-08-26T19:45:22.8298307Z 494516fc2864: Verifying Checksum 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2025-08-26T19:47:00.4388097Z 68effbf08d78: Pull complete 2025-08-26T19:47:02.1944324Z 3bf7eaa748f0: Pull complete 2025-08-26T19:47:02.4960823Z Digest: sha256:16e8df60cdede606d7a1939b8ee6c9786a6466d17602dc7150706f3392d20293 2025-08-26T19:47:02.5451320Z Status: Downloaded newer image for 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:47:02.5662007Z 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:47:02.5709932Z ##[group]Run echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T19:47:02.5710952Z echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT" 2025-08-26T19:47:02.5718233Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:02.5718637Z env: 2025-08-26T19:47:02.5718871Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:02.5719139Z ##[endgroup] 2025-08-26T19:47:02.5806327Z Prepare all required actions 2025-08-26T19:47:02.5936952Z ##[group]Run ./.github/actions/get-workflow-job-id 2025-08-26T19:47:02.5937330Z with: 2025-08-26T19:47:02.5938203Z github-token: *** 2025-08-26T19:47:02.5938445Z env: 2025-08-26T19:47:02.5938675Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:02.5938954Z ##[endgroup] 2025-08-26T19:47:02.6029061Z ##[group]Run set -eux 2025-08-26T19:47:02.6029362Z set -eux 2025-08-26T19:47:02.6029822Z python3 .github/scripts/get_workflow_job_id.py "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-08-26T19:47:02.6035854Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:02.6036265Z env: 2025-08-26T19:47:02.6036519Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:02.6037019Z GITHUB_TOKEN: *** 2025-08-26T19:47:02.6037261Z ##[endgroup] 2025-08-26T19:47:02.6061173Z + python3 .github/scripts/get_workflow_job_id.py 17248463620 i-04da9546f7741a2d4 2025-08-26T19:47:04.2808003Z Setting output job-id=48944862553 2025-08-26T19:47:04.2808765Z Setting output job-name=linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:04.2935301Z ##[group]Run python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-08-26T19:47:04.2936092Z python3 -m pip install psutil==5.9.8 dataclasses_json==0.6.7 nvidia-ml-py==11.525.84 2025-08-26T19:47:04.2937111Z python3 -m tools.stats.monitor --log-interval "$MONITOR_LOG_INTERVAL" --data-collect-interval "$MONITOR_DATA_COLLECT_INTERVAL" > usage_log.txt 2>&1 & 2025-08-26T19:47:04.2938230Z echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}" 2025-08-26T19:47:04.2944317Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:04.2944861Z env: 2025-08-26T19:47:04.2945090Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:04.2945370Z JOB_ID: 48944862553 2025-08-26T19:47:04.2945774Z JOB_NAME: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:04.2946254Z WORKFLOW_NAME: pull 2025-08-26T19:47:04.2946526Z WORKFLOW_RUN_ID: 17248463620 2025-08-26T19:47:04.2946854Z MONITOR_LOG_INTERVAL: 5 2025-08-26T19:47:04.2947146Z MONITOR_DATA_COLLECT_INTERVAL: 1 2025-08-26T19:47:04.2947454Z ##[endgroup] 2025-08-26T19:47:04.5846547Z Defaulting to user installation because normal site-packages is not writeable 2025-08-26T19:47:04.9383586Z Collecting psutil==5.9.8 2025-08-26T19:47:04.9546134Z Downloading psutil-5.9.8-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (288 kB) 2025-08-26T19:47:05.0302553Z Collecting dataclasses_json==0.6.7 2025-08-26T19:47:05.0339602Z Downloading dataclasses_json-0.6.7-py3-none-any.whl (28 kB) 2025-08-26T19:47:05.0617657Z Collecting nvidia-ml-py==11.525.84 2025-08-26T19:47:05.0655892Z Downloading nvidia_ml_py-11.525.84-py3-none-any.whl (34 kB) 2025-08-26T19:47:05.1871708Z Collecting marshmallow<4.0.0,>=3.18.0 2025-08-26T19:47:05.1907718Z Downloading marshmallow-3.26.1-py3-none-any.whl (50 kB) 2025-08-26T19:47:05.2148171Z Collecting typing-inspect<1,>=0.4.0 2025-08-26T19:47:05.2182419Z Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB) 2025-08-26T19:47:05.2741416Z Collecting packaging>=17.0 2025-08-26T19:47:05.2789439Z Downloading packaging-25.0-py3-none-any.whl (66 kB) 2025-08-26T19:47:05.3323204Z Collecting typing-extensions>=3.7.4 2025-08-26T19:47:05.3355753Z Downloading typing_extensions-4.15.0-py3-none-any.whl (44 kB) 2025-08-26T19:47:05.3555703Z Collecting mypy-extensions>=0.3.0 2025-08-26T19:47:05.3587778Z Downloading mypy_extensions-1.1.0-py3-none-any.whl (5.0 kB) 2025-08-26T19:47:05.4522725Z Installing collected packages: typing-extensions, packaging, mypy-extensions, typing-inspect, marshmallow, psutil, nvidia-ml-py, dataclasses-json 2025-08-26T19:47:05.7334675Z Successfully installed dataclasses-json-0.6.7 marshmallow-3.26.1 mypy-extensions-1.1.0 nvidia-ml-py-11.525.84 packaging-25.0 psutil-5.9.8 typing-extensions-4.15.0 typing-inspect-0.9.0 2025-08-26T19:47:05.9024981Z Prepare all required actions 2025-08-26T19:47:05.9025394Z Getting action download info 2025-08-26T19:47:06.0482129Z Download action repository 'seemethere/download-artifact-s3@v4' (SHA:1da556a7aa0a088e3153970611f6c432d58e80e6) 2025-08-26T19:47:06.3239181Z Download action repository 'actions/download-artifact@v4' (SHA:d3f86a106a0bac45b974a628896c90dbdf5c8093) 2025-08-26T19:47:06.5854235Z ##[group]Run ./.github/actions/download-build-artifacts 2025-08-26T19:47:06.5854651Z with: 2025-08-26T19:47:06.5854900Z name: linux-jammy-py3.13-clang12 2025-08-26T19:47:06.5855210Z s3-bucket: gha-artifacts 2025-08-26T19:47:06.5855482Z env: 2025-08-26T19:47:06.5855703Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:06.5855997Z ##[endgroup] 2025-08-26T19:47:06.5887791Z ##[group]Run seemethere/download-artifact-s3@v4 2025-08-26T19:47:06.5888153Z with: 2025-08-26T19:47:06.5888396Z name: linux-jammy-py3.13-clang12 2025-08-26T19:47:06.5888718Z s3-bucket: gha-artifacts 2025-08-26T19:47:06.5889122Z region: us-east-1 2025-08-26T19:47:06.5889350Z env: 2025-08-26T19:47:06.5889570Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:06.5889844Z ##[endgroup] 2025-08-26T19:47:07.0863756Z (node:42451) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-08-26T19:47:07.0864682Z 2025-08-26T19:47:07.0865033Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-08-26T19:47:07.0866038Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-08-26T19:47:07.0867123Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-08-26T19:47:07.3524247Z Found 1 objects with prefix pytorch/pytorch/17248463620/linux-jammy-py3.13-clang12/ 2025-08-26T19:47:07.3525978Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/artifacts.zip 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GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:18.9791921Z ##[endgroup] 2025-08-26T19:47:19.4310521Z (node:42471) NOTE: We are formalizing our plans to enter AWS SDK for JavaScript (v2) into maintenance mode in 2023. 2025-08-26T19:47:19.4311040Z 2025-08-26T19:47:19.4311318Z Please migrate your code to use AWS SDK for JavaScript (v3). 2025-08-26T19:47:19.4311879Z For more information, check the migration guide at https://a.co/7PzMCcy 2025-08-26T19:47:19.4312464Z (Use `node --trace-warnings ...` to show where the warning was created) 2025-08-26T19:47:19.5470224Z Found 1 objects with prefix pytorch/pytorch/17248463620/td_results/ 2025-08-26T19:47:19.5470881Z Starting download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json 2025-08-26T19:47:19.6115410Z Finished download (1/1): /home/ec2-user/actions-runner/_work/pytorch/pytorch/td_results.json 2025-08-26T19:47:19.6120293Z Artifact download has finished successfully 2025-08-26T19:47:19.6372788Z ##[group]Run mkdir -p .additional_ci_files 2025-08-26T19:47:19.6373197Z mkdir -p .additional_ci_files 2025-08-26T19:47:19.6373662Z mv td_results.json .additional_ci_files/td_results.json || true 2025-08-26T19:47:19.6380411Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:19.6380800Z env: 2025-08-26T19:47:19.6381047Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:19.6381326Z ##[endgroup] 2025-08-26T19:47:19.6526613Z ##[group]Run .github/scripts/parse_ref.py 2025-08-26T19:47:19.6527001Z .github/scripts/parse_ref.py 2025-08-26T19:47:19.6532516Z shell: /usr/bin/bash -e {0} 2025-08-26T19:47:19.6532813Z env: 2025-08-26T19:47:19.6533039Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:19.6533302Z ##[endgroup] 2025-08-26T19:47:19.6738876Z Setting output branch=main 2025-08-26T19:47:19.6868822Z Prepare all required actions 2025-08-26T19:47:19.6869222Z Getting action download info 2025-08-26T19:47:19.8141692Z ##[group]Run ./.github/actions/filter-test-configs 2025-08-26T19:47:19.8142061Z with: 2025-08-26T19:47:19.8142555Z github-token: *** 2025-08-26T19:47:19.8145549Z test-matrix: {"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]} 2025-08-26T19:47:19.8148724Z job-name: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:19.8149327Z env: 2025-08-26T19:47:19.8149539Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:19.8149819Z ##[endgroup] 2025-08-26T19:47:19.8197736Z ##[group]Run nick-fields/retry@v3.0.0 2025-08-26T19:47:19.8198058Z with: 2025-08-26T19:47:19.8198316Z shell: bash 2025-08-26T19:47:19.8198557Z timeout_minutes: 10 2025-08-26T19:47:19.8198818Z max_attempts: 5 2025-08-26T19:47:19.8199074Z retry_wait_seconds: 30 2025-08-26T19:47:19.8199902Z command: set -eux # PyYAML 6.0 doesn't work with MacOS x86 anymore # This must run on Python-3.7 (AmazonLinux2) so can't use request=3.32.2 python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-08-26T19:47:19.8200806Z polling_interval_seconds: 1 2025-08-26T19:47:19.8201108Z warning_on_retry: true 2025-08-26T19:47:19.8201385Z continue_on_error: false 2025-08-26T19:47:19.8201669Z env: 2025-08-26T19:47:19.8201877Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:19.8202306Z GITHUB_TOKEN: *** 2025-08-26T19:47:19.8202559Z ##[endgroup] 2025-08-26T19:47:19.9126760Z + python3 -m pip install requests==2.27.1 pyyaml==6.0.2 2025-08-26T19:47:20.1482448Z Defaulting to user installation because normal site-packages is not writeable 2025-08-26T19:47:20.7340587Z Collecting requests==2.27.1 2025-08-26T19:47:20.7553220Z Downloading requests-2.27.1-py2.py3-none-any.whl (63 kB) 2025-08-26T19:47:20.9630677Z Collecting pyyaml==6.0.2 2025-08-26T19:47:20.9676234Z Downloading PyYAML-6.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (737 kB) 2025-08-26T19:47:21.4019177Z Collecting charset-normalizer~=2.0.0 2025-08-26T19:47:21.4061336Z Downloading charset_normalizer-2.0.12-py3-none-any.whl (39 kB) 2025-08-26T19:47:21.4322589Z Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (1.25.10) 2025-08-26T19:47:21.4961210Z Collecting certifi>=2017.4.17 2025-08-26T19:47:21.5000315Z Downloading certifi-2025.8.3-py3-none-any.whl (161 kB) 2025-08-26T19:47:21.5303263Z Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3.9/site-packages (from requests==2.27.1) (2.10) 2025-08-26T19:47:21.6152167Z Installing collected packages: charset-normalizer, certifi, requests, pyyaml 2025-08-26T19:47:21.9412201Z Successfully installed certifi-2025.8.3 charset-normalizer-2.0.12 pyyaml-6.0.2 requests-2.27.1 2025-08-26T19:47:22.8973757Z Command completed after 1 attempt(s). 2025-08-26T19:47:22.9017643Z ##[group]Run set -x 2025-08-26T19:47:22.9017928Z set -x 2025-08-26T19:47:22.9018168Z  2025-08-26T19:47:22.9018561Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-08-26T19:47:22.9019255Z # in runner workspace 2025-08-26T19:47:22.9019680Z python3 "${GITHUB_ACTION_PATH}/../../scripts/parse_ref.py" 2025-08-26T19:47:22.9026054Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:22.9026601Z env: 2025-08-26T19:47:22.9026821Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:22.9027098Z ##[endgroup] 2025-08-26T19:47:22.9051101Z + python3 /home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/filter-test-configs/../../scripts/parse_ref.py 2025-08-26T19:47:22.9229666Z Setting output branch=main 2025-08-26T19:47:22.9360616Z ##[group]Run echo "Workflow: ${GITHUB_WORKFLOW}" 2025-08-26T19:47:22.9361047Z echo "Workflow: ${GITHUB_WORKFLOW}" 2025-08-26T19:47:22.9361399Z echo "Job name: ${JOB_NAME}" 2025-08-26T19:47:22.9361704Z  2025-08-26T19:47:22.9362103Z # Use relative path here as this could be checked out anywhere, not necessarily 2025-08-26T19:47:22.9362593Z # in runner workspace 2025-08-26T19:47:22.9363051Z python3 "${GITHUB_ACTION_PATH}/../../scripts/filter_test_configs.py" \ 2025-08-26T19:47:22.9363549Z  --workflow "${GITHUB_WORKFLOW}" \ 2025-08-26T19:47:22.9363912Z  --job-name "${JOB_NAME}" \ 2025-08-26T19:47:22.9366937Z  --test-matrix "{"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]}" \ 2025-08-26T19:47:22.9370072Z  --selected-test-configs "" \ 2025-08-26T19:47:22.9370431Z  --pr-number "${PR_NUMBER}" \ 2025-08-26T19:47:22.9370762Z  --tag "${TAG}" \ 2025-08-26T19:47:22.9371059Z  --event-name "${EVENT_NAME}" \ 2025-08-26T19:47:22.9371400Z  --schedule "${SCHEDULE}" \ 2025-08-26T19:47:22.9371728Z  --branch "${HEAD_BRANCH}" 2025-08-26T19:47:22.9377628Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:22.9378018Z env: 2025-08-26T19:47:22.9378250Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:22.9378869Z GITHUB_TOKEN: *** 2025-08-26T19:47:22.9379295Z JOB_NAME: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:22.9379776Z PR_NUMBER: 2025-08-26T19:47:22.9379994Z TAG: 2025-08-26T19:47:22.9380229Z EVENT_NAME: push 2025-08-26T19:47:22.9380474Z SCHEDULE: 2025-08-26T19:47:22.9380707Z HEAD_BRANCH: main 2025-08-26T19:47:22.9380953Z ##[endgroup] 2025-08-26T19:47:22.9403232Z Workflow: pull 2025-08-26T19:47:22.9403666Z Job name: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:23.1305297Z Setting output keep-going=True 2025-08-26T19:47:23.1305703Z Setting output ci-verbose-test-logs=False 2025-08-26T19:47:23.1306083Z Setting output ci-test-showlocals=False 2025-08-26T19:47:23.1306448Z Setting output ci-no-test-timeout=False 2025-08-26T19:47:23.1306784Z Setting output ci-no-td=False 2025-08-26T19:47:23.1307111Z Setting output ci-td-distributed=False 2025-08-26T19:47:23.1307462Z Setting output is-unstable=False 2025-08-26T19:47:23.1307788Z Setting output reenabled-issues= 2025-08-26T19:47:23.1311206Z Setting output test-matrix={"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]} 2025-08-26T19:47:23.1314621Z Setting output is-test-matrix-empty=False 2025-08-26T19:47:23.1476036Z ##[group]Run echo "Filtered matrix:" 2025-08-26T19:47:23.1476406Z echo "Filtered matrix:" 2025-08-26T19:47:23.1479410Z echo "{"include": [{"config": "default", "shard": 1, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 2, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 3, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 4, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "default", "shard": 5, "num_shards": 5, "runner": "lf.linux.4xlarge"}, {"config": "crossref", "shard": 1, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "crossref", "shard": 2, "num_shards": 2, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 1, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 2, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "dynamo_wrapped", "shard": 3, "num_shards": 3, "runner": "lf.linux.2xlarge"}, {"config": "einops", "shard": 1, "num_shards": 1, "runner": "lf.linux.2xlarge"}]}" 2025-08-26T19:47:23.1482395Z  2025-08-26T19:47:23.1482612Z echo 2025-08-26T19:47:23.1482883Z echo "Is the current job unstable? False" 2025-08-26T19:47:23.1483235Z  2025-08-26T19:47:23.1483443Z echo 2025-08-26T19:47:23.1483705Z echo "Is keep-going label set? True" 2025-08-26T19:47:23.1484021Z  2025-08-26T19:47:23.1484235Z echo 2025-08-26T19:47:23.1484485Z echo "Reenabled issues? " 2025-08-26T19:47:23.1490220Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:23.1490604Z env: 2025-08-26T19:47:23.1490831Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:23.1491101Z ##[endgroup] 2025-08-26T19:47:23.1513742Z Filtered matrix: 2025-08-26T19:47:23.1517392Z {include: [{config: default, shard: 1, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 2, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 3, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 4, num_shards: 5, runner: lf.linux.4xlarge}, {config: default, shard: 5, num_shards: 5, runner: lf.linux.4xlarge}, {config: crossref, shard: 1, num_shards: 2, runner: lf.linux.2xlarge}, {config: crossref, shard: 2, num_shards: 2, runner: lf.linux.2xlarge}, {config: dynamo_wrapped, shard: 1, num_shards: 3, runner: lf.linux.2xlarge}, {config: dynamo_wrapped, shard: 2, num_shards: 3, runner: lf.linux.2xlarge}, {config: dynamo_wrapped, shard: 3, num_shards: 3, runner: lf.linux.2xlarge}, {config: einops, shard: 1, num_shards: 1, runner: lf.linux.2xlarge}]} 2025-08-26T19:47:23.1520298Z 2025-08-26T19:47:23.1520432Z Is the current job unstable? False 2025-08-26T19:47:23.1520647Z 2025-08-26T19:47:23.1520775Z Is keep-going label set? True 2025-08-26T19:47:23.1520974Z 2025-08-26T19:47:23.1521071Z Reenabled issues? 2025-08-26T19:47:23.1638451Z ##[group]Run echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-08-26T19:47:23.1639004Z echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}" 2025-08-26T19:47:23.1644359Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:23.1644749Z env: 2025-08-26T19:47:23.1644974Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:23.1645369Z JOB_TIMEOUT: 240 2025-08-26T19:47:23.1645594Z ##[endgroup] 2025-08-26T19:47:23.1823057Z ##[group]Run env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-08-26T19:47:23.1823604Z env | grep '^GITHUB' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-08-26T19:47:23.1824075Z env | grep '^CI' >> "/tmp/github_env_${GITHUB_RUN_ID}" 2025-08-26T19:47:23.1829357Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T19:47:23.1829754Z env: 2025-08-26T19:47:23.1844616Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:23.1844988Z ##[endgroup] 2025-08-26T19:47:23.2031497Z ##[group]Run set -x 2025-08-26T19:47:23.2031857Z set -x 2025-08-26T19:47:23.2032078Z  2025-08-26T19:47:23.2032342Z if [[ $TEST_CONFIG == 'multigpu' ]]; then 2025-08-26T19:47:23.2032751Z  TEST_COMMAND=.ci/pytorch/multigpu-test.sh 2025-08-26T19:47:23.2033163Z elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then 2025-08-26T19:47:23.2033541Z  TEST_COMMAND=.ci/onnx/test.sh 2025-08-26T19:47:23.2033857Z else 2025-08-26T19:47:23.2034121Z  TEST_COMMAND=.ci/pytorch/test.sh 2025-08-26T19:47:23.2034441Z fi 2025-08-26T19:47:23.2034658Z  2025-08-26T19:47:23.2034919Z # Leaving 1GB for the runner and other things 2025-08-26T19:47:23.2035519Z TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo) 2025-08-26T19:47:23.2036429Z # https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap 2025-08-26T19:47:23.2037285Z # comes from https://github.com/pytorch/test-infra/pull/6058 2025-08-26T19:47:23.2038071Z TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3)) 2025-08-26T19:47:23.2038516Z  2025-08-26T19:47:23.2038801Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-08-26T19:47:23.2039170Z  SHM_OPTS= 2025-08-26T19:47:23.2039423Z  JENKINS_USER= 2025-08-26T19:47:23.2039806Z  # ensure that docker container cleanly exits in 12 hours 2025-08-26T19:47:23.2040319Z  # if for some reason cleanup action doesn't stop container 2025-08-26T19:47:23.2040745Z  # when job is cancelled 2025-08-26T19:47:23.2041067Z  DOCKER_SHELL_CMD="sleep 12h" 2025-08-26T19:47:23.2041389Z else 2025-08-26T19:47:23.2041657Z  SHM_OPTS="--shm-size=${SHM_SIZE}" 2025-08-26T19:47:23.2042019Z  JENKINS_USER="--user jenkins" 2025-08-26T19:47:23.2042360Z  DOCKER_SHELL_CMD= 2025-08-26T19:47:23.2042629Z fi 2025-08-26T19:47:23.2042852Z  2025-08-26T19:47:23.2043214Z # detached container should get cleaned up by teardown_ec2_linux 2025-08-26T19:47:23.2043786Z # TODO: Stop building test binaries as part of the build phase 2025-08-26T19:47:23.2044426Z # Used for GPU_FLAG, SHM_OPTS, JENKINS_USER and DOCKER_SHELL_CMD since that doesn't play nice 2025-08-26T19:47:23.2045003Z # shellcheck disable=SC2086,SC2090 2025-08-26T19:47:23.2045362Z container_name=$(docker run \ 2025-08-26T19:47:23.2045696Z  ${GPU_FLAG:-} \ 2025-08-26T19:47:23.2046007Z  ${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \ 2025-08-26T19:47:23.2046376Z  -e BUILD_ENVIRONMENT \ 2025-08-26T19:47:23.2046697Z  -e PR_NUMBER \ 2025-08-26T19:47:23.2046986Z  -e GITHUB_ACTIONS \ 2025-08-26T19:47:23.2047295Z  -e GITHUB_REPOSITORY \ 2025-08-26T19:47:23.2047606Z  -e GITHUB_WORKFLOW \ 2025-08-26T19:47:23.2047913Z  -e GITHUB_JOB \ 2025-08-26T19:47:23.2048200Z  -e GITHUB_RUN_ID \ 2025-08-26T19:47:23.2048500Z  -e GITHUB_RUN_NUMBER \ 2025-08-26T19:47:23.2048875Z  -e GITHUB_RUN_ATTEMPT \ 2025-08-26T19:47:23.2049204Z  -e JOB_ID \ 2025-08-26T19:47:23.2049478Z  -e JOB_NAME \ 2025-08-26T19:47:23.2049758Z  -e BASE_SHA \ 2025-08-26T19:47:23.2050178Z  -e BRANCH \ 2025-08-26T19:47:23.2050444Z  -e SHA1 \ 2025-08-26T19:47:23.2050712Z  -e AWS_DEFAULT_REGION \ 2025-08-26T19:47:23.2051028Z  -e IN_WHEEL_TEST \ 2025-08-26T19:47:23.2051311Z  -e SHARD_NUMBER \ 2025-08-26T19:47:23.2051605Z  -e TEST_CONFIG \ 2025-08-26T19:47:23.2051900Z  -e NUM_TEST_SHARDS \ 2025-08-26T19:47:23.2052208Z  -e REENABLED_ISSUES \ 2025-08-26T19:47:23.2052518Z  -e CONTINUE_THROUGH_ERROR \ 2025-08-26T19:47:23.2052967Z  -e VERBOSE_TEST_LOGS \ 2025-08-26T19:47:23.2053288Z  -e TEST_SHOWLOCALS \ 2025-08-26T19:47:23.2053597Z  -e NO_TEST_TIMEOUT \ 2025-08-26T19:47:23.2053879Z  -e NO_TD \ 2025-08-26T19:47:23.2054151Z  -e TD_DISTRIBUTED \ 2025-08-26T19:47:23.2054454Z  -e PR_LABELS \ 2025-08-26T19:47:23.2054773Z  -e MAX_JOBS="$(nproc --ignore=2)" \ 2025-08-26T19:47:23.2055119Z  -e SCCACHE_BUCKET \ 2025-08-26T19:47:23.2055420Z  -e SCCACHE_REGION \ 2025-08-26T19:47:23.2055716Z  -e XLA_CUDA \ 2025-08-26T19:47:23.2056032Z  -e XLA_CLANG_CACHE_S3_BUCKET_NAME \ 2025-08-26T19:47:23.2056406Z  -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \ 2025-08-26T19:47:23.2056801Z  -e PYTORCH_TEST_RERUN_DISABLED_TESTS \ 2025-08-26T19:47:23.2057200Z  -e SKIP_SCCACHE_INITIALIZATION=1 \ 2025-08-26T19:47:23.2057565Z  -e HUGGING_FACE_HUB_TOKEN \ 2025-08-26T19:47:23.2057922Z  -e VLLM_TEST_HUGGING_FACE_TOKEN \ 2025-08-26T19:47:23.2058276Z  -e SCRIBE_GRAPHQL_ACCESS_TOKEN \ 2025-08-26T19:47:23.2058620Z  -e DASHBOARD_TAG \ 2025-08-26T19:47:23.2058928Z  -e ARTIFACTS_FILE_SUFFIX \ 2025-08-26T19:47:23.2059319Z  --memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \ 2025-08-26T19:47:23.2059751Z  --memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \ 2025-08-26T19:47:23.2060196Z  --env-file="/tmp/github_env_${GITHUB_RUN_ID}" \ 2025-08-26T19:47:23.2060621Z  --security-opt seccomp=unconfined \ 2025-08-26T19:47:23.2060986Z  --cap-add=SYS_PTRACE \ 2025-08-26T19:47:23.2061287Z  --ipc=host \ 2025-08-26T19:47:23.2061562Z  ${SHM_OPTS} \ 2025-08-26T19:47:23.2061832Z  --tty \ 2025-08-26T19:47:23.2062084Z  --detach \ 2025-08-26T19:47:23.2062352Z  --name="${container_name}" \ 2025-08-26T19:47:23.2062685Z  ${JENKINS_USER} \ 2025-08-26T19:47:23.2063060Z  -v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \ 2025-08-26T19:47:23.2063487Z  -w /var/lib/jenkins/workspace \ 2025-08-26T19:47:23.2063829Z  "${DOCKER_IMAGE}" \ 2025-08-26T19:47:23.2064117Z  ${DOCKER_SHELL_CMD} 2025-08-26T19:47:23.2064400Z ) 2025-08-26T19:47:23.2064711Z # Propagate download.pytorch.org IP to container 2025-08-26T19:47:23.2065423Z grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts" 2025-08-26T19:47:23.2066176Z echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}" 2025-08-26T19:47:23.2066610Z  2025-08-26T19:47:23.2066894Z if [[ ${BUILD_ENVIRONMENT} == *"s390x"* ]]; then 2025-08-26T19:47:23.2067506Z  docker exec -t "${container_name}" sh -c "python3 -m pip install -r .ci/docker/requirements-ci.txt" 2025-08-26T19:47:23.2068061Z fi 2025-08-26T19:47:23.2068269Z  2025-08-26T19:47:23.2068793Z docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}" 2025-08-26T19:47:23.2074222Z shell: /usr/bin/bash -e {0} 2025-08-26T19:47:23.2074518Z env: 2025-08-26T19:47:23.2074733Z GIT_DEFAULT_BRANCH: main 2025-08-26T19:47:23.2075066Z BUILD_ENVIRONMENT: linux-jammy-py3.13-clang12 2025-08-26T19:47:23.2075430Z PR_NUMBER: 2025-08-26T19:47:23.2075687Z GITHUB_REPOSITORY: pytorch/pytorch 2025-08-26T19:47:23.2076091Z GITHUB_WORKFLOW: pull 2025-08-26T19:47:23.2076346Z GITHUB_JOB: test 2025-08-26T19:47:23.2076600Z GITHUB_RUN_ID: 17248463620 2025-08-26T19:47:23.2076888Z GITHUB_RUN_NUMBER: 350026 2025-08-26T19:47:23.2077168Z GITHUB_RUN_ATTEMPT: 1 2025-08-26T19:47:23.2077420Z JOB_ID: 48944862553 2025-08-26T19:47:23.2077837Z JOB_NAME: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:23.2078312Z BRANCH: main 2025-08-26T19:47:23.2078579Z SHA1: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:23.2079049Z BASE_SHA: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:23.2079393Z TEST_CONFIG: default 2025-08-26T19:47:23.2079650Z SHARD_NUMBER: 1 2025-08-26T19:47:23.2079894Z NUM_TEST_SHARDS: 5 2025-08-26T19:47:23.2080152Z REENABLED_ISSUES: 2025-08-26T19:47:23.2080408Z CONTINUE_THROUGH_ERROR: True 2025-08-26T19:47:23.2080702Z VERBOSE_TEST_LOGS: False 2025-08-26T19:47:23.2080981Z TEST_SHOWLOCALS: False 2025-08-26T19:47:23.2081263Z NO_TEST_TIMEOUT: False 2025-08-26T19:47:23.2081512Z NO_TD: False 2025-08-26T19:47:23.2081748Z TD_DISTRIBUTED: False 2025-08-26T19:47:23.2082073Z SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2 2025-08-26T19:47:23.2082574Z SCCACHE_REGION: us-east-1 2025-08-26T19:47:23.2082829Z SHM_SIZE: 1g 2025-08-26T19:47:23.2083554Z DOCKER_IMAGE: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:47:23.2084345Z XLA_CUDA: 2025-08-26T19:47:23.2084711Z XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla 2025-08-26T19:47:23.2085167Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: 0 2025-08-26T19:47:23.2085491Z PYTORCH_TEST_RERUN_DISABLED_TESTS: 0 2025-08-26T19:47:23.2085798Z DASHBOARD_TAG: 2025-08-26T19:47:23.2086247Z VLLM_TEST_HUGGING_FACE_TOKEN: *** 2025-08-26T19:47:23.2086660Z HUGGING_FACE_HUB_TOKEN: *** 2025-08-26T19:47:23.2087070Z SCRIBE_GRAPHQL_ACCESS_TOKEN: *** 2025-08-26T19:47:23.2087484Z ARTIFACTS_FILE_SUFFIX: test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T19:47:23.2087911Z ##[endgroup] 2025-08-26T19:47:23.2109038Z + [[ default == \m\u\l\t\i\g\p\u ]] 2025-08-26T19:47:23.2109399Z + [[ linux-jammy-py3.13-clang12 == *onnx* ]] 2025-08-26T19:47:23.2109727Z + TEST_COMMAND=.ci/pytorch/test.sh 2025-08-26T19:47:23.2112079Z ++ awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo 2025-08-26T19:47:23.2130305Z + TOTAL_AVAILABLE_MEMORY_IN_GB='29.641 ' 2025-08-26T19:47:23.2131019Z + TOTAL_MEMORY_WITH_SWAP=32 2025-08-26T19:47:23.2131692Z + [[ linux-jammy-py3.13-clang12 == *\s\3\9\0\x* ]] 2025-08-26T19:47:23.2132360Z + SHM_OPTS=--shm-size=1g 2025-08-26T19:47:23.2132868Z + JENKINS_USER='--user jenkins' 2025-08-26T19:47:23.2133421Z + DOCKER_SHELL_CMD= 2025-08-26T19:47:23.2140918Z +++ nproc --ignore=2 2025-08-26T19:47:23.2389982Z ++ docker run -e BUILD_ENVIRONMENT -e PR_NUMBER -e GITHUB_ACTIONS -e GITHUB_REPOSITORY -e GITHUB_WORKFLOW -e GITHUB_JOB -e GITHUB_RUN_ID -e GITHUB_RUN_NUMBER -e GITHUB_RUN_ATTEMPT -e JOB_ID -e JOB_NAME -e BASE_SHA -e BRANCH -e SHA1 -e AWS_DEFAULT_REGION -e IN_WHEEL_TEST -e SHARD_NUMBER -e TEST_CONFIG -e NUM_TEST_SHARDS -e REENABLED_ISSUES -e CONTINUE_THROUGH_ERROR -e VERBOSE_TEST_LOGS -e TEST_SHOWLOCALS -e NO_TEST_TIMEOUT -e NO_TD -e TD_DISTRIBUTED -e PR_LABELS -e MAX_JOBS=14 -e SCCACHE_BUCKET -e SCCACHE_REGION -e XLA_CUDA -e XLA_CLANG_CACHE_S3_BUCKET_NAME -e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK -e PYTORCH_TEST_RERUN_DISABLED_TESTS -e SKIP_SCCACHE_INITIALIZATION=1 -e HUGGING_FACE_HUB_TOKEN -e VLLM_TEST_HUGGING_FACE_TOKEN -e SCRIBE_GRAPHQL_ACCESS_TOKEN -e DASHBOARD_TAG -e ARTIFACTS_FILE_SUFFIX --memory=29g --memory-swap=32g --env-file=/tmp/github_env_17248463620 --security-opt seccomp=unconfined --cap-add=SYS_PTRACE --ipc=host --shm-size=1g --tty --detach --name= --user jenkins -v /home/ec2-user/actions-runner/_work/pytorch/pytorch:/var/lib/jenkins/workspace -w /var/lib/jenkins/workspace 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 2025-08-26T19:47:42.7263279Z + container_name=e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T19:47:42.7266804Z + grep download.pytorch.org /etc/hosts 2025-08-26T19:47:42.7268396Z + docker exec -i e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 sudo bash -c '/bin/cat >> /etc/hosts' 2025-08-26T19:47:42.9086776Z + echo DOCKER_CONTAINER_ID=e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T19:47:42.9087706Z + [[ linux-jammy-py3.13-clang12 == *\s\3\9\0\x* ]] 2025-08-26T19:47:42.9088174Z ++ echo dist/torch-2.9.0a0+git262640f-cp313-cp313-linux_x86_64.whl 2025-08-26T19:47:42.9089517Z + docker exec -t e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 sh -c 'python3 -m pip install dist/torch-2.9.0a0+git262640f-cp313-cp313-linux_x86_64.whl[opt-einsum] && .ci/pytorch/test.sh' 2025-08-26T19:47:43.2674616Z Processing ./dist/torch-2.9.0a0+git262640f-cp313-cp313-linux_x86_64.whl (from torch==2.9.0a0+git262640f) 2025-08-26T19:47:43.8091405Z Requirement already satisfied: filelock in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (3.19.1) 2025-08-26T19:47:43.8095024Z Requirement already satisfied: typing-extensions>=4.10.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (4.15.0) 2025-08-26T19:47:43.8100056Z Requirement already satisfied: setuptools in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (80.9.0) 2025-08-26T19:47:43.8103639Z Requirement already satisfied: sympy>=1.13.3 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (1.13.3) 2025-08-26T19:47:43.8107195Z Requirement already satisfied: networkx>=2.5.1 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (2.8.8) 2025-08-26T19:47:43.8110077Z Requirement already satisfied: jinja2 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (3.1.6) 2025-08-26T19:47:43.8113750Z Requirement already satisfied: fsspec>=0.8.5 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (2025.7.0) 2025-08-26T19:47:43.8127046Z Requirement already satisfied: opt-einsum>=3.3 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (3.3.0) 2025-08-26T19:47:43.8235091Z Requirement already satisfied: numpy>=1.7 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from opt-einsum>=3.3->torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (2.1.2) 2025-08-26T19:47:43.8280943Z Requirement already satisfied: mpmath<1.4,>=1.1.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from sympy>=1.13.3->torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (1.3.0) 2025-08-26T19:47:43.8314002Z Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/py_3.13/lib/python3.13/site-packages (from jinja2->torch==2.9.0a0+git262640f->torch==2.9.0a0+git262640f) (3.0.2) 2025-08-26T19:47:44.0565155Z Installing collected packages: torch 2025-08-26T19:47:54.2073391Z Successfully installed torch-2.9.0a0+git262640f 2025-08-26T19:47:54.2709017Z + export TERM=vt100 2025-08-26T19:47:54.2709481Z + TERM=vt100 2025-08-26T19:47:54.2712125Z ++ dirname .ci/pytorch/test.sh 2025-08-26T19:47:54.2719341Z + source .ci/pytorch/common.sh 2025-08-26T19:47:54.2722296Z +++ dirname .ci/pytorch/common.sh 2025-08-26T19:47:54.2728759Z ++ source .ci/pytorch/common_utils.sh 2025-08-26T19:47:54.2730064Z +++ declare -f -t trap_add 2025-08-26T19:47:54.2734854Z ++ set -ex -o pipefail 2025-08-26T19:47:54.2735146Z ++ [[ linux-jammy-py3.13-clang12 == *rocm* ]] 2025-08-26T19:47:54.2735499Z ++ BUILD_TEST_LIBTORCH=0 2025-08-26T19:47:54.2738531Z ++ dirname .ci/pytorch/test.sh 2025-08-26T19:47:54.2745371Z + source .ci/pytorch/common-build.sh 2025-08-26T19:47:54.2746948Z ++ [[ linux-jammy-py3.13-clang12 != *win-* ]] 2025-08-26T19:47:54.2752418Z ++++ dirname .ci/pytorch/common-build.sh 2025-08-26T19:47:54.2759056Z +++ cd .ci/pytorch 2025-08-26T19:47:54.2759314Z +++ pwd -P 2025-08-26T19:47:54.2761008Z ++ script_dir=/var/lib/jenkins/workspace/.ci/pytorch 2025-08-26T19:47:54.2761443Z ++ [[ linux-jammy-py3.13-clang12 == *-pch* ]] 2025-08-26T19:47:54.2761777Z ++ which sccache 2025-08-26T19:47:54.2772057Z ++ [[ -z ossci-compiler-cache-circleci-v2 ]] 2025-08-26T19:47:54.2772592Z ++ sccache --stop-server 2025-08-26T19:47:54.2794549Z ++ true 2025-08-26T19:47:54.2794818Z ++ rm -f /var/lib/jenkins/sccache_error.log 2025-08-26T19:47:54.2802783Z ++ trap_add sccache_epilogue EXIT 2025-08-26T19:47:54.2803122Z ++ trap_add_cmd=sccache_epilogue 2025-08-26T19:47:54.2803394Z ++ shift 2025-08-26T19:47:54.2803621Z ++ for trap_add_name in "$@" 2025-08-26T19:47:54.2809046Z ++++ trap -p EXIT 2025-08-26T19:47:54.2811158Z +++ eval 'extract_trap_cmd ' 2025-08-26T19:47:54.2811616Z ++++ extract_trap_cmd 2025-08-26T19:47:54.2811888Z ++++ printf '%s\n' '' 2025-08-26T19:47:54.2812162Z +++ printf '%s\n' sccache_epilogue 2025-08-26T19:47:54.2813302Z ++ trap -- ' 2025-08-26T19:47:54.2813742Z sccache_epilogue' EXIT 2025-08-26T19:47:54.2814176Z ++ [[ -n 1 ]] 2025-08-26T19:47:54.2814897Z ++ echo 'Skipping sccache server initialization, setting environment variables' 2025-08-26T19:47:54.2815798Z Skipping sccache server initialization, setting environment variables 2025-08-26T19:47:54.2816308Z ++ export SCCACHE_IDLE_TIMEOUT=0 2025-08-26T19:47:54.2816606Z ++ SCCACHE_IDLE_TIMEOUT=0 2025-08-26T19:47:54.2816975Z ++ export SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-08-26T19:47:54.2817445Z ++ SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-08-26T19:47:54.2817875Z ++ export RUST_LOG=sccache::server=error 2025-08-26T19:47:54.2818206Z ++ RUST_LOG=sccache::server=error 2025-08-26T19:47:54.2818514Z ++ sccache --zero-stats 2025-08-26T19:47:54.3960365Z Statistics zeroed. 2025-08-26T19:47:54.3963694Z ++ which ccache 2025-08-26T19:47:54.3974379Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]] 2025-08-26T19:47:54.3974833Z + [[ linux-jammy-py3.13-clang12 != *s390x* ]] 2025-08-26T19:47:54.3975211Z + [[ -d /var/lib/jenkins/workspace ]] 2025-08-26T19:47:54.3977327Z ++ stat -c %u /var/lib/jenkins/workspace 2025-08-26T19:47:54.3987426Z + WORKSPACE_ORIGINAL_OWNER_ID=1000 2025-08-26T19:47:54.3988015Z + trap_add cleanup_workspace EXIT 2025-08-26T19:47:54.3988527Z + trap_add_cmd=cleanup_workspace 2025-08-26T19:47:54.3988842Z + shift 2025-08-26T19:47:54.3989075Z + for trap_add_name in "$@" 2025-08-26T19:47:54.3994813Z +++ trap -p EXIT 2025-08-26T19:47:54.3996826Z ++ eval 'extract_trap_cmd trap -- '\'' 2025-08-26T19:47:54.3997163Z sccache_epilogue'\'' EXIT' 2025-08-26T19:47:54.3997454Z +++ extract_trap_cmd trap -- ' 2025-08-26T19:47:54.3997758Z sccache_epilogue' EXIT 2025-08-26T19:47:54.3998008Z +++ printf '%s\n' ' 2025-08-26T19:47:54.3998275Z sccache_epilogue' 2025-08-26T19:47:54.3998631Z ++ printf '%s\n' cleanup_workspace 2025-08-26T19:47:54.3999053Z + trap -- ' 2025-08-26T19:47:54.3999262Z sccache_epilogue 2025-08-26T19:47:54.3999508Z cleanup_workspace' EXIT 2025-08-26T19:47:54.3999829Z + sudo chown -R jenkins /var/lib/jenkins/workspace 2025-08-26T19:47:55.0015250Z + git config --global --add safe.directory /var/lib/jenkins/workspace 2025-08-26T19:47:55.0031268Z + echo 'Environment variables:' 2025-08-26T19:47:55.0031587Z Environment variables: 2025-08-26T19:47:55.0031849Z + env 2025-08-26T19:47:55.0038821Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-08-26T19:47:55.0039559Z CONTINUE_THROUGH_ERROR=True 2025-08-26T19:47:55.0039976Z BUILD_ENVIRONMENT=linux-jammy-py3.13-clang12 2025-08-26T19:47:55.0040815Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-08-26T19:47:55.0041384Z HOSTNAME=e12c338ce7d9 2025-08-26T19:47:55.0041991Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0042839Z GITHUB_ACTION=__run_2 2025-08-26T19:47:55.0043120Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-08-26T19:47:55.0043433Z GITHUB_RUN_NUMBER=350026 2025-08-26T19:47:55.0043702Z TEST_CONFIG=default 2025-08-26T19:47:55.0044005Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-08-26T19:47:55.0044346Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-08-26T19:47:55.0044660Z SCCACHE_IDLE_TIMEOUT=0 2025-08-26T19:47:55.0045078Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-08-26T19:47:55.0045399Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-08-26T19:47:55.0045828Z GITHUB_REF_TYPE=branch 2025-08-26T19:47:55.0046120Z BASE_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0046454Z XLA_CUDA= 2025-08-26T19:47:55.0046692Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-08-26T19:47:55.0047116Z HUGGING_FACE_HUB_TOKEN=*** 2025-08-26T19:47:55.0047580Z *** 2025-08-26T19:47:55.0047794Z GITHUB_REPOSITORY_ID=65600975 2025-08-26T19:47:55.0048087Z GITHUB_ACTIONS=true 2025-08-26T19:47:55.0048406Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-08-26T19:47:55.0048808Z SHA1=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0049248Z GITHUB_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0049775Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/pull.yml@refs/heads/main 2025-08-26T19:47:55.0050388Z UCC_HOME=/usr 2025-08-26T19:47:55.0050631Z VERBOSE_TEST_LOGS=False 2025-08-26T19:47:55.0050898Z GITHUB_REF=refs/heads/main 2025-08-26T19:47:55.0051178Z SHARD_NUMBER=1 2025-08-26T19:47:55.0051424Z GITHUB_REF_PROTECTED=true 2025-08-26T19:47:55.0051704Z HOME=/var/lib/jenkins 2025-08-26T19:47:55.0051984Z GITHUB_API_URL=https://api.github.com 2025-08-26T19:47:55.0052332Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-08-26T19:47:55.0052638Z UCX_COMMIT= 2025-08-26T19:47:55.0052861Z USE_SYSTEM_NCCL=1 2025-08-26T19:47:55.0053094Z NUM_TEST_SHARDS=5 2025-08-26T19:47:55.0053332Z UCX_HOME=/usr 2025-08-26T19:47:55.0053930Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0054765Z JOB_NAME=linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:55.0055565Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0056419Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json 2025-08-26T19:47:55.0057060Z GITHUB_EVENT_NAME=push 2025-08-26T19:47:55.0057317Z DASHBOARD_TAG= 2025-08-26T19:47:55.0057542Z GITHUB_RUN_ID=17248463620 2025-08-26T19:47:55.0057816Z INSTALLED_OPENBLAS= 2025-08-26T19:47:55.0058446Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0059290Z GITHUB_ACTOR=pytorchmergebot 2025-08-26T19:47:55.0059564Z PR_NUMBER= 2025-08-26T19:47:55.0059784Z DESIRED_CUDA= 2025-08-26T19:47:55.0060021Z GITHUB_RUN_ATTEMPT=1 2025-08-26T19:47:55.0060292Z ANACONDA_PYTHON_VERSION=3.13 2025-08-26T19:47:55.0060639Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-08-26T19:47:55.0061010Z TERM=vt100 2025-08-26T19:47:55.0061243Z INSTALLED_VISION=yes 2025-08-26T19:47:55.0061497Z BRANCH=main 2025-08-26T19:47:55.0061720Z SCCACHE_REGION=us-east-1 2025-08-26T19:47:55.0062119Z OPENSSL_ROOT_DIR=/opt/openssl 2025-08-26T19:47:55.0062418Z CUDA_PATH=/usr/local/cuda 2025-08-26T19:47:55.0062968Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-08-26T19:47:55.0063580Z GITHUB_SERVER_URL=https://github.com 2025-08-26T19:47:55.0063897Z UCC_COMMIT= 2025-08-26T19:47:55.0064123Z REENABLED_ISSUES= 2025-08-26T19:47:55.0064359Z DOCS= 2025-08-26T19:47:55.0064554Z SHLVL=1 2025-08-26T19:47:55.0064766Z MAX_JOBS=14 2025-08-26T19:47:55.0064998Z GITHUB_ACTOR_ID=97764156 2025-08-26T19:47:55.0065365Z GITHUB_WORKFLOW_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0065757Z GITHUB_REF_NAME=main 2025-08-26T19:47:55.0066162Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-08-26T19:47:55.0066728Z GITHUB_JOB=test 2025-08-26T19:47:55.0066974Z NO_TEST_TIMEOUT=False 2025-08-26T19:47:55.0067228Z TD_DISTRIBUTED=False 2025-08-26T19:47:55.0067515Z GITHUB_REPOSITORY=pytorch/pytorch 2025-08-26T19:47:55.0067841Z GITHUB_RETENTION_DAYS=90 2025-08-26T19:47:55.0068128Z OPENSSL_DIR=/opt/openssl 2025-08-26T19:47:55.0068402Z GITHUB_ACTION_REPOSITORY= 2025-08-26T19:47:55.0069301Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T19:47:55.0070157Z GITHUB_BASE_REF= 2025-08-26T19:47:55.0070404Z INSTALLED_ACL= 2025-08-26T19:47:55.0070763Z ARTIFACTS_FILE_SUFFIX=test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T19:47:55.0071202Z CI=true 2025-08-26T19:47:55.0071435Z GITHUB_REPOSITORY_OWNER=pytorch 2025-08-26T19:47:55.0071785Z RUST_LOG=sccache::server=error 2025-08-26T19:47:55.0072061Z JOB_ID=48944862553 2025-08-26T19:47:55.0072307Z GITHUB_HEAD_REF= 2025-08-26T19:47:55.0072548Z GITHUB_ACTION_REF= 2025-08-26T19:47:55.0072854Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-08-26T19:47:55.0073213Z TEST_SHOWLOCALS=False 2025-08-26T19:47:55.0073477Z GITHUB_WORKFLOW=pull 2025-08-26T19:47:55.0073751Z DEBIAN_FRONTEND=noninteractive 2025-08-26T19:47:55.0074413Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0075070Z NO_TD=False 2025-08-26T19:47:55.0075316Z SKIP_SCCACHE_INITIALIZATION=1 2025-08-26T19:47:55.0075637Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-08-26T19:47:55.0075971Z _=/usr/bin/env 2025-08-26T19:47:55.0076299Z ++ python -c 'import site; print(site.getsitepackages()[0])' 2025-08-26T19:47:55.0181189Z + TORCH_INSTALL_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch 2025-08-26T19:47:55.0181827Z + TORCH_BIN_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T19:47:55.0182445Z + TORCH_LIB_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib 2025-08-26T19:47:55.0183118Z + TORCH_TEST_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/test 2025-08-26T19:47:55.0183571Z + BUILD_DIR=build 2025-08-26T19:47:55.0183827Z + BUILD_RENAMED_DIR=build_renamed 2025-08-26T19:47:55.0184134Z + BUILD_BIN_DIR=build/bin 2025-08-26T19:47:55.0184407Z + SHARD_NUMBER=1 2025-08-26T19:47:55.0184629Z + NUM_TEST_SHARDS=5 2025-08-26T19:47:55.0184892Z + export TORCH_SERIALIZATION_DEBUG=1 2025-08-26T19:47:55.0185222Z + TORCH_SERIALIZATION_DEBUG=1 2025-08-26T19:47:55.0185506Z + export VALGRIND=ON 2025-08-26T19:47:55.0185742Z + VALGRIND=ON 2025-08-26T19:47:55.0186007Z + [[ linux-jammy-py3.13-clang12 == *clang9* ]] 2025-08-26T19:47:55.0186373Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]] 2025-08-26T19:47:55.0186699Z + detect_cuda_arch 2025-08-26T19:47:55.0186957Z + [[ linux-jammy-py3.13-clang12 == *cuda* ]] 2025-08-26T19:47:55.0187318Z + [[ linux-jammy-py3.13-clang12 == *s390x* ]] 2025-08-26T19:47:55.0187642Z + [[ 0 == \1 ]] 2025-08-26T19:47:55.0187867Z + [[ True == \1 ]] 2025-08-26T19:47:55.0188121Z + [[ linux-jammy-py3.13-clang12 != *bazel* ]] 2025-08-26T19:47:55.0188475Z ++ realpath build/custom_test_artifacts 2025-08-26T19:47:55.0193892Z + CUSTOM_TEST_ARTIFACT_BUILD_DIR=/var/lib/jenkins/workspace/build/custom_test_artifacts 2025-08-26T19:47:55.0194630Z + [[ -n '' ]] 2025-08-26T19:47:55.0194931Z + echo 'Environment variables' 2025-08-26T19:47:55.0195223Z Environment variables 2025-08-26T19:47:55.0195477Z + env 2025-08-26T19:47:55.0201465Z GITHUB_WORKSPACE=/home/ec2-user/actions-runner/_work/pytorch/pytorch 2025-08-26T19:47:55.0202128Z CONTINUE_THROUGH_ERROR=True 2025-08-26T19:47:55.0202524Z BUILD_ENVIRONMENT=linux-jammy-py3.13-clang12 2025-08-26T19:47:55.0203111Z VLLM_TEST_HUGGING_FACE_TOKEN=*** 2025-08-26T19:47:55.0203452Z HOSTNAME=e12c338ce7d9 2025-08-26T19:47:55.0204175Z GITHUB_PATH=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/add_path_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0205091Z GITHUB_ACTION=__run_2 2025-08-26T19:47:55.0205364Z PYTORCH_TEST_CUDA_MEM_LEAK_CHECK=0 2025-08-26T19:47:55.0205687Z GITHUB_RUN_NUMBER=350026 2025-08-26T19:47:55.0205965Z TEST_CONFIG=default 2025-08-26T19:47:55.0206231Z GITHUB_REPOSITORY_OWNER_ID=21003710 2025-08-26T19:47:55.0206562Z TORCH_NVCC_FLAGS=-Xfatbin -compress-all 2025-08-26T19:47:55.0207075Z SCCACHE_IDLE_TIMEOUT=0 2025-08-26T19:47:55.0207693Z SCRIBE_GRAPHQL_ACCESS_TOKEN=*** 2025-08-26T19:47:55.0208029Z GITHUB_TRIGGERING_ACTOR=pytorchmergebot 2025-08-26T19:47:55.0208621Z GITHUB_REF_TYPE=branch 2025-08-26T19:47:55.0209014Z BASE_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0209459Z XLA_CUDA= 2025-08-26T19:47:55.0209762Z NCCL_LIB_DIR=/usr/local/cuda/lib64/ 2025-08-26T19:47:55.0210396Z HUGGING_FACE_HUB_TOKEN=*** 2025-08-26T19:47:55.0210715Z *** 2025-08-26T19:47:55.0210938Z GITHUB_REPOSITORY_ID=65600975 2025-08-26T19:47:55.0211234Z GITHUB_ACTIONS=true 2025-08-26T19:47:55.0211542Z SCCACHE_ERROR_LOG=/var/lib/jenkins/sccache_error.log 2025-08-26T19:47:55.0211933Z SHA1=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0212301Z GITHUB_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0212817Z GITHUB_WORKFLOW_REF=pytorch/pytorch/.github/workflows/pull.yml@refs/heads/main 2025-08-26T19:47:55.0213292Z UCC_HOME=/usr 2025-08-26T19:47:55.0213518Z TORCH_SERIALIZATION_DEBUG=1 2025-08-26T19:47:55.0213800Z VERBOSE_TEST_LOGS=False 2025-08-26T19:47:55.0214065Z GITHUB_REF=refs/heads/main 2025-08-26T19:47:55.0214347Z SHARD_NUMBER=1 2025-08-26T19:47:55.0214581Z GITHUB_REF_PROTECTED=true 2025-08-26T19:47:55.0214853Z HOME=/var/lib/jenkins 2025-08-26T19:47:55.0215143Z GITHUB_API_URL=https://api.github.com 2025-08-26T19:47:55.0215492Z PYTORCH_TEST_RERUN_DISABLED_TESTS=0 2025-08-26T19:47:55.0215831Z UCX_COMMIT= 2025-08-26T19:47:55.0216040Z USE_SYSTEM_NCCL=1 2025-08-26T19:47:55.0216285Z NUM_TEST_SHARDS=5 2025-08-26T19:47:55.0216524Z UCX_HOME=/usr 2025-08-26T19:47:55.0217231Z GITHUB_STATE=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/save_state_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0218058Z JOB_NAME=linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T19:47:55.0218872Z GITHUB_ENV=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_env_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0219738Z GITHUB_EVENT_PATH=/home/ec2-user/actions-runner/_work/_temp/_github_workflow/event.json 2025-08-26T19:47:55.0220273Z GITHUB_EVENT_NAME=push 2025-08-26T19:47:55.0220543Z DASHBOARD_TAG= 2025-08-26T19:47:55.0220781Z GITHUB_RUN_ID=17248463620 2025-08-26T19:47:55.0221060Z INSTALLED_OPENBLAS= 2025-08-26T19:47:55.0221712Z GITHUB_STEP_SUMMARY=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/step_summary_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0222442Z GITHUB_ACTOR=pytorchmergebot 2025-08-26T19:47:55.0222717Z PR_NUMBER= 2025-08-26T19:47:55.0222938Z DESIRED_CUDA= 2025-08-26T19:47:55.0223170Z GITHUB_RUN_ATTEMPT=1 2025-08-26T19:47:55.0223423Z VALGRIND=ON 2025-08-26T19:47:55.0223648Z ANACONDA_PYTHON_VERSION=3.13 2025-08-26T19:47:55.0224004Z GITHUB_GRAPHQL_URL=https://api.github.com/graphql 2025-08-26T19:47:55.0224369Z TERM=vt100 2025-08-26T19:47:55.0224597Z INSTALLED_VISION=yes 2025-08-26T19:47:55.0224837Z BRANCH=main 2025-08-26T19:47:55.0225070Z SCCACHE_REGION=us-east-1 2025-08-26T19:47:55.0225357Z OPENSSL_ROOT_DIR=/opt/openssl 2025-08-26T19:47:55.0225658Z CUDA_PATH=/usr/local/cuda 2025-08-26T19:47:55.0226199Z GITHUB_ACTION_PATH=/home/ec2-user/actions-runner/_work/pytorch/pytorch/./.github/actions/setup-linux 2025-08-26T19:47:55.0226818Z GITHUB_SERVER_URL=https://github.com 2025-08-26T19:47:55.0227140Z UCC_COMMIT= 2025-08-26T19:47:55.0227366Z REENABLED_ISSUES= 2025-08-26T19:47:55.0227591Z DOCS= 2025-08-26T19:47:55.0227802Z SHLVL=1 2025-08-26T19:47:55.0228017Z MAX_JOBS=14 2025-08-26T19:47:55.0228238Z GITHUB_ACTOR_ID=97764156 2025-08-26T19:47:55.0228595Z GITHUB_WORKFLOW_SHA=262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T19:47:55.0229104Z GITHUB_REF_NAME=main 2025-08-26T19:47:55.0229505Z XLA_CLANG_CACHE_S3_BUCKET_NAME=ossci-compiler-clang-cache-circleci-xla 2025-08-26T19:47:55.0229958Z GITHUB_JOB=test 2025-08-26T19:47:55.0230188Z NO_TEST_TIMEOUT=False 2025-08-26T19:47:55.0230454Z TD_DISTRIBUTED=False 2025-08-26T19:47:55.0230732Z GITHUB_REPOSITORY=pytorch/pytorch 2025-08-26T19:47:55.0231036Z GITHUB_RETENTION_DAYS=90 2025-08-26T19:47:55.0231316Z OPENSSL_DIR=/opt/openssl 2025-08-26T19:47:55.0231600Z GITHUB_ACTION_REPOSITORY= 2025-08-26T19:47:55.0232490Z PATH=/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T19:47:55.0233345Z GITHUB_BASE_REF= 2025-08-26T19:47:55.0233575Z INSTALLED_ACL= 2025-08-26T19:47:55.0233954Z ARTIFACTS_FILE_SUFFIX=test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T19:47:55.0234395Z CI=true 2025-08-26T19:47:55.0234631Z GITHUB_REPOSITORY_OWNER=pytorch 2025-08-26T19:47:55.0234962Z RUST_LOG=sccache::server=error 2025-08-26T19:47:55.0235252Z JOB_ID=48944862553 2025-08-26T19:47:55.0235492Z GITHUB_HEAD_REF= 2025-08-26T19:47:55.0235730Z GITHUB_ACTION_REF= 2025-08-26T19:47:55.0236022Z SCCACHE_BUCKET=ossci-compiler-cache-circleci-v2 2025-08-26T19:47:55.0236393Z TEST_SHOWLOCALS=False 2025-08-26T19:47:55.0236657Z GITHUB_WORKFLOW=pull 2025-08-26T19:47:55.0236919Z DEBIAN_FRONTEND=noninteractive 2025-08-26T19:47:55.0237831Z GITHUB_OUTPUT=/home/ec2-user/actions-runner/_work/_temp/_runner_file_commands/set_output_bd2804de-bd37-4253-a701-415313d627cd 2025-08-26T19:47:55.0238526Z NO_TD=False 2025-08-26T19:47:55.0238775Z SKIP_SCCACHE_INITIALIZATION=1 2025-08-26T19:47:55.0239101Z NCCL_INCLUDE_DIR=/usr/local/cuda/include/ 2025-08-26T19:47:55.0239490Z _=/usr/bin/env 2025-08-26T19:47:55.0239843Z + echo 'Testing pytorch' 2025-08-26T19:47:55.0240131Z Testing pytorch 2025-08-26T19:47:55.0240377Z + export LANG=C.UTF-8 2025-08-26T19:47:55.0240617Z + LANG=C.UTF-8 2025-08-26T19:47:55.0240845Z + PR_NUMBER= 2025-08-26T19:47:55.0241090Z + [[ default == \d\e\f\a\u\l\t ]] 2025-08-26T19:47:55.0241391Z + export CUDA_VISIBLE_DEVICES=0 2025-08-26T19:47:55.0241689Z + CUDA_VISIBLE_DEVICES=0 2025-08-26T19:47:55.0241973Z + export HIP_VISIBLE_DEVICES=0 2025-08-26T19:47:55.0242271Z + HIP_VISIBLE_DEVICES=0 2025-08-26T19:47:55.0242540Z + [[ default == \d\i\s\t\r\i\b\u\t\e\d ]] 2025-08-26T19:47:55.0242864Z + [[ default == \s\l\o\w ]] 2025-08-26T19:47:55.0243210Z + [[ linux-jammy-py3.13-clang12 == *slow-gradcheck* ]] 2025-08-26T19:47:55.0243620Z + [[ linux-jammy-py3.13-clang12 == *cuda* ]] 2025-08-26T19:47:55.0243978Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]] 2025-08-26T19:47:55.0244349Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]] 2025-08-26T19:47:55.0244693Z + [[ default == *crossref* ]] 2025-08-26T19:47:55.0245008Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]] 2025-08-26T19:47:55.0245364Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]] 2025-08-26T19:47:55.0245720Z + [[ linux-jammy-py3.13-clang12 != *-bazel-* ]] 2025-08-26T19:47:55.0246075Z + pip_install ninja==1.10.2 2025-08-26T19:47:55.0246462Z + pip_install_pkg='python3 -m pip install --progress-bar off' 2025-08-26T19:47:55.0246958Z + python3 -m pip install --progress-bar off ninja==1.10.2 2025-08-26T19:47:56.2954876Z Collecting ninja==1.10.2 2025-08-26T19:47:56.3126970Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl.metadata (5.0 kB) 2025-08-26T19:47:56.3520319Z Downloading ninja-1.10.2-py2.py3-none-manylinux_2_5_x86_64.manylinux1_x86_64.whl (108 kB) 2025-08-26T19:47:56.5449464Z Installing collected packages: ninja 2025-08-26T19:47:56.5450363Z Attempting uninstall: ninja 2025-08-26T19:47:56.5483833Z Found existing installation: ninja 1.11.1.3 2025-08-26T19:47:56.5505557Z Uninstalling ninja-1.11.1.3: 2025-08-26T19:47:56.5574434Z Successfully uninstalled ninja-1.11.1.3 2025-08-26T19:47:56.6034092Z Successfully installed ninja-1.10.2 2025-08-26T19:47:56.6629529Z + export PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T19:47:56.6631403Z + PATH=/var/lib/jenkins/.local/bin:/opt/cache/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/opt/conda/envs/py_3.13/bin:/opt/conda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin 2025-08-26T19:47:56.6632399Z + [[ linux-jammy-py3.13-clang12 == *aarch64* ]] 2025-08-26T19:47:56.6632797Z + [[ linux-jammy-py3.13-clang12 == *asan* ]] 2025-08-26T19:47:56.6633164Z + [[ linux-jammy-py3.13-clang12 == *-debug* ]] 2025-08-26T19:47:56.6633635Z + [[ linux-jammy-py3.13-clang12 != *-bazel-* ]] 2025-08-26T19:47:56.6634173Z + echo 'We are not in debug mode: linux-jammy-py3.13-clang12. Expect the assertion to pass' 2025-08-26T19:47:56.6634833Z We are not in debug mode: linux-jammy-py3.13-clang12. Expect the assertion to pass 2025-08-26T19:47:56.6635302Z + cd test 2025-08-26T19:47:56.6635652Z + python -c 'import torch; torch._C._crash_if_debug_asserts_fail(424242)' 2025-08-26T19:47:58.0247863Z + [[ default == \n\o\g\p\u\_\N\O\_\A\V\X\2 ]] 2025-08-26T19:47:58.0248286Z + [[ default == \n\o\g\p\u\_\A\V\X\5\1\2 ]] 2025-08-26T19:47:58.0248678Z + [[ default == \l\e\g\a\c\y\_\n\v\i\d\i\a\_\d\r\i\v\e\r ]] 2025-08-26T19:47:58.0252087Z + DYNAMO_BENCHMARK_FLAGS=() 2025-08-26T19:47:58.0252967Z + [[ default == *pr_time_benchmarks* ]] 2025-08-26T19:47:58.0253360Z + [[ default == *dynamo_eager* ]] 2025-08-26T19:47:58.0253675Z + [[ default == *aot_eager* ]] 2025-08-26T19:47:58.0253991Z + [[ default == *aot_inductor* ]] 2025-08-26T19:47:58.0254403Z + [[ default == *max_autotune_inductor* ]] 2025-08-26T19:47:58.0254740Z + [[ default == *inductor* ]] 2025-08-26T19:47:58.0255037Z + [[ default == *dynamic* ]] 2025-08-26T19:47:58.0255321Z + [[ default == *cpu* ]] 2025-08-26T19:47:58.0255618Z + DYNAMO_BENCHMARK_FLAGS+=(--device cuda) 2025-08-26T19:47:58.0276597Z + [[ linux-jammy-py3.13-clang12 == *libtorch* ]] 2025-08-26T19:47:58.0277013Z + [[ linux-jammy-py3.13-clang12 == *-bazel-* ]] 2025-08-26T19:47:58.0279524Z + cd test 2025-08-26T19:47:58.0279981Z + python -c 'import torch; print(torch.__config__.show())' 2025-08-26T19:47:59.1145986Z PyTorch built with: 2025-08-26T19:47:59.1146303Z - GCC 4.2 2025-08-26T19:47:59.1146538Z - C++ Version: 201703 2025-08-26T19:47:59.1146797Z - clang 12.0.1 2025-08-26T19:47:59.1147368Z - Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-08-26T19:47:59.1148140Z - Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-08-26T19:47:59.1148627Z - OpenMP 201811 2025-08-26T19:47:59.1148910Z - LAPACK is enabled (usually provided by MKL) 2025-08-26T19:47:59.1149267Z - NNPACK is enabled 2025-08-26T19:47:59.1149548Z - CPU capability usage: AVX512 2025-08-26T19:47:59.1155176Z - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, COMMIT_SHA=a03cc53e6f6e2fe67316cb8c74c25f5b953f445b, CXX_COMPILER=/opt/cache/bin/clang++, CXX_FLAGS= -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DLIBKINETO_NOROCTRACER -DLIBKINETO_NOXPUPTI=ON -DUSE_FBGEMM -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -DC10_NODEPRECATED -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=braced-scalar-init -Werror=range-loop-construct -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-unknown-pragmas -Wno-unused-parameter -Wno-strict-overflow -Wno-strict-aliasing -Wvla-extension -Wsuggest-override -Wnewline-eof -Winconsistent-missing-override -Winconsistent-missing-destructor-override -Wno-pass-failed -Wno-error=old-style-cast -Wconstant-conversion -Qunused-arguments -faligned-new -Werror -fno-math-errno -fno-trapping-math -Werror=format, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, TORCH_VERSION=2.9.0, USE_CUDA=OFF, USE_CUDNN=OFF, USE_CUSPARSELT=OFF, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_GLOO=ON, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF, USE_ROCM_KERNEL_ASSERT=OFF, USE_XCCL=OFF, USE_XPU=OFF, 2025-08-26T19:47:59.1161155Z 2025-08-26T19:47:59.3579280Z + cd test 2025-08-26T19:47:59.3579706Z + python -c 'import torch; print(torch.__config__.parallel_info())' 2025-08-26T19:48:00.4529089Z ATen/Parallel: 2025-08-26T19:48:00.4529442Z at::get_num_threads() : 8 2025-08-26T19:48:00.4529769Z at::get_num_interop_threads() : 8 2025-08-26T19:48:00.4530084Z OpenMP 201811 2025-08-26T19:48:00.4530317Z omp_get_max_threads() : 8 2025-08-26T19:48:00.4531209Z Intel(R) oneAPI Math Kernel Library Version 2024.2-Product Build 20240605 for Intel(R) 64 architecture applications 2025-08-26T19:48:00.4531850Z mkl_get_max_threads() : 8 2025-08-26T19:48:00.4532266Z Intel(R) MKL-DNN v3.7.1 (Git Hash 8d263e693366ef8db40acc569cc7d8edf644556d) 2025-08-26T19:48:00.4532729Z std::thread::hardware_concurrency() : 16 2025-08-26T19:48:00.4533071Z Environment variables: 2025-08-26T19:48:00.4533347Z OMP_NUM_THREADS : [not set] 2025-08-26T19:48:00.4533639Z MKL_NUM_THREADS : [not set] 2025-08-26T19:48:00.4533939Z ATen parallel backend: OpenMP 2025-08-26T19:48:00.4534148Z 2025-08-26T19:48:00.6926907Z + [[ default == *numpy_2* ]] 2025-08-26T19:48:00.6927305Z + [[ linux-jammy-py3.13-clang12 == *aarch64* ]] 2025-08-26T19:48:00.6927711Z + [[ default == *backward* ]] 2025-08-26T19:48:00.6927992Z + [[ default == *xla* ]] 2025-08-26T19:48:00.6928265Z + [[ default == *vllm* ]] 2025-08-26T19:48:00.6928546Z + [[ default == *executorch* ]] 2025-08-26T19:48:00.6928853Z + [[ default == \j\i\t\_\l\e\g\a\c\y ]] 2025-08-26T19:48:00.6929298Z + [[ linux-jammy-py3.13-clang12 == *libtorch* ]] 2025-08-26T19:48:00.6929669Z + [[ default == distributed ]] 2025-08-26T19:48:00.6930003Z + [[ default == *operator_benchmark* ]] 2025-08-26T19:48:00.6930355Z + [[ default == *inductor_distributed* ]] 2025-08-26T19:48:00.6930706Z + [[ default == *inductor-halide* ]] 2025-08-26T19:48:00.6931036Z + [[ default == *inductor-triton-cpu* ]] 2025-08-26T19:48:00.6931409Z + [[ default == *inductor-micro-benchmark* ]] 2025-08-26T19:48:00.6931786Z + [[ default == *huggingface* ]] 2025-08-26T19:48:00.6932088Z + [[ default == *timm* ]] 2025-08-26T19:48:00.6932359Z + [[ default == cachebench ]] 2025-08-26T19:48:00.6932663Z + [[ default == verify_cachebench ]] 2025-08-26T19:48:00.6932989Z + [[ default == *torchbench* ]] 2025-08-26T19:48:00.6933305Z + [[ default == *inductor_cpp_wrapper* ]] 2025-08-26T19:48:00.6933632Z + [[ default == *inductor* ]] 2025-08-26T19:48:00.6933923Z + [[ default == *einops* ]] 2025-08-26T19:48:00.6934215Z + [[ default == *dynamo_wrapped* ]] 2025-08-26T19:48:00.6934579Z + [[ linux-jammy-py3.13-clang12 == *rocm* ]] 2025-08-26T19:48:00.6934899Z + [[ 1 == 1 ]] 2025-08-26T19:48:00.6935145Z + [[ 5 -gt 1 ]] 2025-08-26T19:48:00.6935421Z + test_lazy_tensor_meta_reference_disabled 2025-08-26T19:48:00.6935849Z + export TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1 2025-08-26T19:48:00.6936296Z + TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE=1 2025-08-26T19:48:00.6936765Z + echo 'Testing lazy tensor operations without meta reference' 2025-08-26T19:48:00.6937257Z Testing lazy tensor operations without meta reference 2025-08-26T19:48:00.6937950Z + python test/run_test.py --include lazy/test_ts_opinfo.py --verbose 2025-08-26T19:48:03.0893568Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T19:48:03.0895197Z import pkg_resources 2025-08-26T19:48:04.6448357Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-08-26T19:48:04.7007054Z Ignoring disabled issues: [''] 2025-08-26T19:48:04.7138712Z Found test times from artifacts 2025-08-26T19:48:04.7644253Z Found test times from artifacts 2025-08-26T19:48:04.7659074Z Running all tests 2025-08-26T19:48:04.7662252Z Running parallel tests on 3 processes 2025-08-26T19:48:04.7662618Z Name: tests to run (est. time: 0.49min) 2025-08-26T19:48:04.7662943Z Serial tests (0): 2025-08-26T19:48:04.7663199Z Parallel tests (1): 2025-08-26T19:48:04.7663473Z lazy/test_ts_opinfo 1/1 2025-08-26T19:48:04.7663855Z Name: excluded (est. time: 0.0min) 2025-08-26T19:48:04.7664211Z Serial tests (0): 2025-08-26T19:48:04.7664463Z Parallel tests (0): 2025-08-26T19:48:04.7664821Z Running lazy/test_ts_opinfo 1/1 ... [2025-08-26 19:48:04.766311] 2025-08-26T19:48:04.7665393Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:48:04.7668297Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:48:04.766612] 2025-08-26T19:48:08.9871976Z 2025-08-26T19:48:08.9872859Z lazy/test_ts_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_ts_opinfo_1.1_532edf2792b89407_.log 2025-08-26T19:48:08.9873691Z Running 0 items in this shard: 2025-08-26T19:48:08.9873892Z 2025-08-26T19:48:09.2544124Z Uploading artifacts took 0.27 seconds 2025-08-26T19:48:11.7365975Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T19:48:11.7367569Z import pkg_resources 2025-08-26T19:48:11.7742343Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T19:48:11.7743901Z import pkg_resources 2025-08-26T19:48:11.7745372Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T19:48:11.7746885Z import pkg_resources 2025-08-26T19:48:11.8551512Z Running lazy/test_ts_opinfo 1/1 ... [2025-08-26 19:48:11.854866] 2025-08-26T19:48:11.8551990Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:48:11.8554116Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:48:11.855184] 2025-08-26T19:48:27.4404685Z 2025-08-26T19:48:27.4405747Z lazy/test_ts_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_ts_opinfo_1.1_6b9006e432a812df_.log 2025-08-26T19:48:27.4524417Z Running 292 items in this shard: test/lazy/test_ts_opinfo.py::TestLazyTensor::testConvolutionBackward, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_tensor_ctr, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_view_mark_step_preserved, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_block_diag_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diag_embed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_logsumexp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_narrow_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_new_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_nuc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_block_diag_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diag_embed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_logsumexp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_narrow_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_new_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_nuc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addcdiv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_bernoulli_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_pow_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_adaptiveavgpool3d_dynamic, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_nonzero_dynamic 2025-08-26T19:48:27.4642161Z 2025-08-26T19:48:28.1987496Z Running test batch 'tests to run' cost 23.43 seconds 2025-08-26T19:48:28.9179197Z 2025-08-26T19:48:28.9179634Z real 0m28.225s 2025-08-26T19:48:28.9179916Z user 1m31.267s 2025-08-26T19:48:28.9180182Z sys 0m4.137s 2025-08-26T19:48:28.9180533Z + export -n TORCH_DISABLE_FUNCTIONALIZATION_META_REFERENCE 2025-08-26T19:48:28.9180945Z + test_without_numpy 2025-08-26T19:48:28.9183833Z ++ dirname .ci/pytorch/test.sh 2025-08-26T19:48:28.9194187Z + pushd .ci/pytorch 2025-08-26T19:48:28.9194485Z ~/workspace/.ci/pytorch ~/workspace 2025-08-26T19:48:28.9195365Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');from unittest import TestCase;import torch;x=torch.randn(3,3);TestCase().assertRaises(RuntimeError, lambda: x.numpy())' 2025-08-26T19:48:29.5499525Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_subclasses/functional_tensor.py:279: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:84.) 2025-08-26T19:48:29.5511458Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-08-26T19:48:30.1767387Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');import torch;print(torch.tensor([torch.tensor(0.), torch.tensor(1.)]))' 2025-08-26T19:48:30.8077502Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_subclasses/functional_tensor.py:279: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:84.) 2025-08-26T19:48:30.8079017Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-08-26T19:48:31.1981086Z tensor([0., 1.]) 2025-08-26T19:48:31.4230303Z + [[ default == *dynamo_wrapped* ]] 2025-08-26T19:48:31.4230899Z + python -c 'import sys;sys.path.insert(0, '\''fake_numpy'\'');import torch; import torch.onnx' 2025-08-26T19:48:32.0535256Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_subclasses/functional_tensor.py:279: UserWarning: Failed to initialize NumPy: Sorry PyTorch, but our NumPy is in the other folder (Triggered internally at /var/lib/jenkins/workspace/torch/csrc/utils/tensor_numpy.cpp:84.) 2025-08-26T19:48:32.0536991Z cpu = _conversion_method_template(device=torch.device("cpu")) 2025-08-26T19:48:32.7030912Z + popd 2025-08-26T19:48:32.7031188Z ~/workspace 2025-08-26T19:48:32.7031432Z + install_torchvision 2025-08-26T19:48:32.7031715Z + local orig_preload 2025-08-26T19:48:32.7031968Z + local commit 2025-08-26T19:48:32.7034582Z ++ get_pinned_commit vision 2025-08-26T19:48:32.7034897Z ++ cat .github/ci_commit_pins/vision.txt 2025-08-26T19:48:32.7047121Z + commit=966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T19:48:32.7047632Z + orig_preload= 2025-08-26T19:48:32.7047991Z + '[' -n '' ']' 2025-08-26T19:48:32.7048363Z + [[ linux-jammy-py3.13-clang12 == *cuda* ]] 2025-08-26T19:48:32.7049587Z + pip_build_and_install git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 dist/vision 2025-08-26T19:48:32.7050702Z + local build_target=git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T19:48:32.7051296Z + local wheel_dir=dist/vision 2025-08-26T19:48:32.7051604Z + local found_whl=0 2025-08-26T19:48:32.7051872Z + for file in "${wheel_dir}"/*.whl 2025-08-26T19:48:32.7052192Z + [[ -f dist/vision/*.whl ]] 2025-08-26T19:48:32.7052461Z + '[' 0 == 0 ']' 2025-08-26T19:48:32.7053247Z + python3 -m pip wheel --no-build-isolation --no-deps --no-use-pep517 -w dist/vision git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T19:48:33.0207827Z Collecting git+https://github.com/pytorch/vision.git@966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T19:48:33.0212591Z Cloning https://github.com/pytorch/vision.git (to revision 966da7e46f65d6d49df3e31214470a4fe5cc8e66) to /tmp/pip-req-build-pnmm47ys 2025-08-26T19:48:33.0230725Z Running command git clone --filter=blob:none --quiet https://github.com/pytorch/vision.git /tmp/pip-req-build-pnmm47ys 2025-08-26T19:48:34.5364386Z Running command git rev-parse -q --verify 'sha^966da7e46f65d6d49df3e31214470a4fe5cc8e66' 2025-08-26T19:48:34.5382296Z Running command git fetch -q https://github.com/pytorch/vision.git 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T19:48:34.6570272Z Running command git checkout -q 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T19:48:34.9757288Z Resolved https://github.com/pytorch/vision.git to commit 966da7e46f65d6d49df3e31214470a4fe5cc8e66 2025-08-26T19:48:36.8836048Z Preparing metadata (setup.py) ... [?25l- \ | done 2025-08-26T19:48:36.8878812Z [?25hBuilding wheels for collected packages: torchvision 2025-08-26T19:48:36.8926315Z  DEPRECATION: Building 'torchvision' using the legacy setup.py bdist_wheel mechanism, which will be removed in a future version. pip 25.3 will enforce this behaviour change. A possible replacement is to use the standardized build interface by setting the `--use-pep517` option, (possibly combined with `--no-build-isolation`), or adding a `pyproject.toml` file to the source tree of 'torchvision'. Discussion can be found at https://github.com/pypa/pip/issues/6334 2025-08-26T19:49:28.6789472Z  Building wheel for torchvision (setup.py) ... [?25l- \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ | / - \ done 2025-08-26T19:49:28.6827706Z [?25h Created wheel for torchvision: filename=torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl size=1200294 sha256=ba698d2da075853743228da1cf447fc29bea5330936927c9ba6a44d6c66dbd46 2025-08-26T19:49:28.6829496Z Stored in directory: /var/lib/jenkins/.cache/pip/wheels/89/53/07/16d05bff0990e585bfa232438657da6e5e4f6d0cea71bd3e09 2025-08-26T19:49:28.6865074Z Successfully built torchvision 2025-08-26T19:49:28.7689830Z + for file in "${wheel_dir}"/*.whl 2025-08-26T19:49:28.7690462Z + pip_install_whl dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl 2025-08-26T19:49:28.7691200Z + args=('dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl') 2025-08-26T19:49:28.7691675Z + local args 2025-08-26T19:49:28.7692407Z + [[ dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl == *\ * ]] 2025-08-26T19:49:28.7692936Z + for path in "${args[@]}" 2025-08-26T19:49:28.7693435Z + echo 'Installing dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl' 2025-08-26T19:49:28.7694169Z Installing dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl 2025-08-26T19:49:28.7694995Z + python3 -mpip install --no-index --no-deps dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl 2025-08-26T19:49:29.0956187Z Processing ./dist/vision/torchvision-0.22.0a0+966da7e-cp313-cp313-linux_x86_64.whl 2025-08-26T19:49:29.1057770Z Installing collected packages: torchvision 2025-08-26T19:49:29.5786192Z Successfully installed torchvision-0.22.0a0+966da7e 2025-08-26T19:49:29.6245330Z + '[' -n '' ']' 2025-08-26T19:49:29.6245621Z + test_python_shard 1 2025-08-26T19:49:29.6245892Z + [[ -z 5 ]] 2025-08-26T19:49:29.6246580Z + python test/run_test.py --exclude-jit-executor --exclude-distributed-tests --shard 1 5 --verbose --upload-artifacts-while-running 2025-08-26T19:49:31.9633284Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T19:49:31.9634870Z import pkg_resources 2025-08-26T19:49:33.5294323Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-08-26T19:49:33.5421491Z Found test times from artifacts 2025-08-26T19:49:33.5936194Z Found test times from artifacts 2025-08-26T19:49:33.5951685Z Running all tests 2025-08-26T19:49:33.6336490Z Running parallel tests on 3 processes 2025-08-26T19:49:33.6344695Z Name: tests to run (est. time: 77.75min) 2025-08-26T19:49:33.6345039Z Serial tests (47): 2025-08-26T19:49:33.6345416Z inductor/test_flex_attention 1/1 2025-08-26T19:49:33.6345749Z test_ci_sanity_check_fail 1/1 2025-08-26T19:49:33.6346061Z test_overrides 1/1 2025-08-26T19:49:33.6346340Z test_reductions 1/1 2025-08-26T19:49:33.6346613Z test_tensor_creation_ops 1/1 2025-08-26T19:49:33.6346948Z test_cpp_extensions_mtia_backend 1/1 2025-08-26T19:49:33.6347280Z test_nn 1/1 2025-08-26T19:49:33.6347538Z test_cpp_extensions_stream_and_event 1/1 2025-08-26T19:49:33.6347881Z doctests 1/1 2025-08-26T19:49:33.6348144Z inductor/test_max_autotune 1/1 2025-08-26T19:49:33.6348473Z inductor/test_benchmark_fusion 1/1 2025-08-26T19:49:33.6348795Z inductor/test_cutlass_backend 1/1 2025-08-26T19:49:33.6349142Z inductor/test_distributed_patterns 1/1 2025-08-26T19:49:33.6349491Z dynamo/test_fake_distributed 1/1 2025-08-26T19:49:33.6349802Z test_utils 1/1 2025-08-26T19:49:33.6350032Z test_fx 1/1 2025-08-26T19:49:33.6350294Z test_transformers_privateuse1 1/1 2025-08-26T19:49:33.6350628Z test_cpp_api_parity 1/1 2025-08-26T19:49:33.6350919Z test_extension_utils 1/1 2025-08-26T19:49:33.6351192Z test_openreg 1/1 2025-08-26T19:49:33.6351450Z test_show_pickle 1/1 2025-08-26T19:49:33.6351713Z test_torch 1/1 2025-08-26T19:49:33.6351961Z test_tensorexpr 1/1 2025-08-26T19:49:33.6352232Z test_namedtuple_return_api 1/1 2025-08-26T19:49:33.6352554Z test_multiprocessing 1/1 2025-08-26T19:49:33.6352856Z test_autograd_fallback 1/1 2025-08-26T19:49:33.6353382Z test_fake_tensor 1/1 2025-08-26T19:49:33.6353649Z test_python_dispatch 1/1 2025-08-26T19:49:33.6353938Z test_autocast 1/1 2025-08-26T19:49:33.6354208Z test_jit_disabled 1/1 2025-08-26T19:49:33.6354487Z test_dispatch 1/1 2025-08-26T19:49:33.6354738Z test_native_mha 1/1 2025-08-26T19:49:33.6355007Z test_sort_and_select 1/1 2025-08-26T19:49:33.6355304Z test_cpp_extensions_jit 1/1 2025-08-26T19:49:33.6355602Z nn/test_pooling 1/1 2025-08-26T19:49:33.6355863Z nn/test_convolution 1/1 2025-08-26T19:49:33.6356258Z test_multiprocessing_spawn 1/1 2025-08-26T19:49:33.6356584Z test_cuda_primary_ctx 1/1 2025-08-26T19:49:33.6356886Z test_mobile_optimizer 1/1 2025-08-26T19:49:33.6357166Z test_cuda_trace 1/1 2025-08-26T19:49:33.6357446Z test_cuda_nvml_based_avail 1/1 2025-08-26T19:49:33.6357763Z test_spectral_ops 1/1 2025-08-26T19:49:33.6358071Z distributions/test_distributions 1/1 2025-08-26T19:49:33.6358418Z test_cpp_extensions_aot_no_ninja 1/1 2025-08-26T19:49:33.6358755Z test_autoload_disable 1/1 2025-08-26T19:49:33.6359053Z test_autoload_enable 1/1 2025-08-26T19:49:33.6359358Z test_cpp_extensions_aot_ninja 1/1 2025-08-26T19:49:33.6359670Z Parallel tests (118): 2025-08-26T19:49:33.6359964Z inductor/test_compile_subprocess 2/2 2025-08-26T19:49:33.6360300Z inductor/test_memory 1/1 2025-08-26T19:49:33.6360583Z test_jit 1/1 2025-08-26T19:49:33.6360821Z test_binary_ufuncs 1/1 2025-08-26T19:49:33.6361126Z higher_order_ops/test_with_effects 1/1 2025-08-26T19:49:33.6361473Z test_content_store 1/1 2025-08-26T19:49:33.6361754Z test_numpy_interop 1/1 2025-08-26T19:49:33.6362034Z functorch/test_control_flow 1/1 2025-08-26T19:49:33.6362368Z functorch/test_aotdispatch 1/6 2025-08-26T19:49:33.6362691Z functorch/test_aotdispatch 3/6 2025-08-26T19:49:33.6363003Z test_indexing 1/1 2025-08-26T19:49:33.6363261Z test_type_promotion 1/1 2025-08-26T19:49:33.6363570Z functorch/test_eager_transforms 1/1 2025-08-26T19:49:33.6363913Z inductor/test_flex_decoding 1/1 2025-08-26T19:49:33.6364318Z export/test_export_training_ir_to_run_decomp 1/1 2025-08-26T19:49:33.6364708Z inductor/test_pattern_matcher 1/1 2025-08-26T19:49:33.6365030Z inductor/test_inductor_utils 1/1 2025-08-26T19:49:33.6365402Z inductor/test_torchinductor_strided_blocks 1/1 2025-08-26T19:49:33.6365786Z inductor/test_subgraph_choice 1/1 2025-08-26T19:49:33.6366130Z inductor/test_aot_inductor_package 1/1 2025-08-26T19:49:33.6366475Z inductor/test_triton_heuristics 1/1 2025-08-26T19:49:33.6366813Z inductor/test_inplacing_pass 1/1 2025-08-26T19:49:33.6367145Z inductor/test_online_softmax 1/1 2025-08-26T19:49:33.6367487Z inductor/test_cpu_select_algorithm 4/16 2025-08-26T19:49:33.6367839Z inductor/test_cpu_select_algorithm 8/16 2025-08-26T19:49:33.6368207Z inductor/test_cpu_select_algorithm 12/16 2025-08-26T19:49:33.6368574Z inductor/test_scatter_optimization 1/1 2025-08-26T19:49:33.6369011Z dynamo/test_list 1/1 2025-08-26T19:49:33.6369282Z dynamo/test_sources 1/1 2025-08-26T19:49:33.6369577Z dynamo/test_model_output 1/1 2025-08-26T19:49:33.6369891Z dynamo/test_profiler 1/1 2025-08-26T19:49:33.6370193Z export/test_export_opinfo 1/1 2025-08-26T19:49:33.6370504Z nn/test_multihead_attention 1/1 2025-08-26T19:49:33.6370842Z inductor/test_auto_functionalize 1/1 2025-08-26T19:49:33.6371180Z dynamo/test_base_hop 1/1 2025-08-26T19:49:33.6371474Z export/test_upgrader 1/1 2025-08-26T19:49:33.6371760Z export/test_export 1/1 2025-08-26T19:49:33.6372056Z inductor/test_binary_folding 1/1 2025-08-26T19:49:33.6372404Z dynamo/test_backward_higher_order_ops 1/1 2025-08-26T19:49:33.6372758Z dynamo/test_deviceguard 1/1 2025-08-26T19:49:33.6373047Z export/test_swap 1/1 2025-08-26T19:49:33.6373326Z dynamo/test_export 1/1 2025-08-26T19:49:33.6373614Z dynamo/test_debug_utils 1/1 2025-08-26T19:49:33.6373917Z dynamo/test_flat_apply 1/1 2025-08-26T19:49:33.6374302Z dynamo/test_optimizers 1/1 2025-08-26T19:49:33.6374619Z dynamo/test_verify_correctness 1/1 2025-08-26T19:49:33.6374947Z dynamo/test_sets 1/1 2025-08-26T19:49:33.6375247Z inductor/test_unbacked_symints 1/1 2025-08-26T19:49:33.6375580Z dynamo/test_python_dispatcher 1/1 2025-08-26T19:49:33.6375915Z dynamo/test_cudagraphs 1/1 2025-08-26T19:49:33.6376222Z export/test_unflatten 1/1 2025-08-26T19:49:33.6376547Z inductor/test_efficient_conv_bn_eval 1/1 2025-08-26T19:49:33.6376880Z export/test_nativert 1/1 2025-08-26T19:49:33.6377265Z dynamo/test_activation_checkpointing 1/1 2025-08-26T19:49:33.6377610Z dynamo/test_hooks 1/1 2025-08-26T19:49:33.6377890Z dynamo/test_generator 1/1 2025-08-26T19:49:33.6378181Z dynamo/test_reorder_logs 1/1 2025-08-26T19:49:33.6378489Z export/test_verifier 1/1 2025-08-26T19:49:33.6378781Z export/test_sparse 1/1 2025-08-26T19:49:33.6379066Z dynamo/test_comptime 1/1 2025-08-26T19:49:33.6379359Z dynamo/test_python_autograd 1/1 2025-08-26T19:49:33.6379670Z test_ao_sparsity 1/1 2025-08-26T19:49:33.6379936Z test_package 1/1 2025-08-26T19:49:33.6380198Z profiler/test_kineto 1/1 2025-08-26T19:49:33.6380510Z higher_order_ops/test_invoke_subgraph 1/1 2025-08-26T19:49:33.6380859Z test_comparison_utils 1/1 2025-08-26T19:49:33.6381165Z functorch/test_ac_logging 1/1 2025-08-26T19:49:33.6381472Z test_mkl_verbose 1/1 2025-08-26T19:49:33.6381727Z test_decomp 1/11 2025-08-26T19:49:33.6381991Z test_transformers 1/2 2025-08-26T19:49:33.6382276Z test_transformers 2/2 2025-08-26T19:49:33.6382555Z test_mkldnn_verbose 1/1 2025-08-26T19:49:33.6382836Z test_utils_config_module 1/1 2025-08-26T19:49:33.6383137Z test_ops_jit 1/2 2025-08-26T19:49:33.6383402Z functorch/test_ops 4/6 2025-08-26T19:49:33.6383678Z test_ops 3/7 2025-08-26T19:49:33.6383905Z test_ops 6/7 2025-08-26T19:49:33.6384149Z test_jiterator 1/1 2025-08-26T19:49:33.6384419Z test_ops_gradients 2/2 2025-08-26T19:49:33.6384708Z lazy/test_step_closures 1/1 2025-08-26T19:49:33.6385007Z test_sparse_semi_structured 1/1 2025-08-26T19:49:33.6385330Z nn/test_packed_sequence 1/1 2025-08-26T19:49:33.6385648Z profiler/test_record_function 1/1 2025-08-26T19:49:33.6385977Z nn/test_lazy_modules 1/1 2025-08-26T19:49:33.6386260Z test_fx_reinplace_pass 1/1 2025-08-26T19:49:33.6386569Z profiler/test_cpp_thread 1/1 2025-08-26T19:49:33.6386890Z test_cuda_expandable_segments 1/1 2025-08-26T19:49:33.6387223Z test_numba_integration 1/1 2025-08-26T19:49:33.6387517Z test_segment_reductions 1/1 2025-08-26T19:49:33.6387811Z test_logging 1/1 2025-08-26T19:49:33.6388099Z test_functionalization_of_rng_ops 1/1 2025-08-26T19:49:33.6388485Z functorch/test_aot_joint_with_descriptors 1/1 2025-08-26T19:49:33.6388830Z test_subclass 1/1 2025-08-26T19:49:33.6389089Z test_itt 1/1 2025-08-26T19:49:33.6389346Z profiler/test_torch_tidy 1/1 2025-08-26T19:49:33.6389685Z torch_np/numpy_tests/core/test_numeric 1/1 2025-08-26T19:49:33.6390021Z test_bundled_inputs 1/1 2025-08-26T19:49:33.6390299Z test_masked 1/1 2025-08-26T19:49:33.6390542Z test_monitor 1/1 2025-08-26T19:49:33.6390802Z test_sympy_utils 1/1 2025-08-26T19:49:33.6391108Z torch_np/numpy_tests/lib/test_function_base 1/1 2025-08-26T19:49:33.6391494Z functorch/test_vmap_registrations 1/1 2025-08-26T19:49:33.6391840Z torch_np/test_indexing 1/1 2025-08-26T19:49:33.6392297Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 2025-08-26T19:49:33.6392786Z test_mkldnn_fusion 1/1 2025-08-26T19:49:33.6393067Z test_import_stats 1/1 2025-08-26T19:49:33.6393347Z test_tensorboard 1/1 2025-08-26T19:49:33.6393621Z nn/test_embedding 1/1 2025-08-26T19:49:33.6393883Z nn/test_dropout 1/1 2025-08-26T19:49:33.6394186Z torch_np/numpy_tests/lib/test_type_check 1/1 2025-08-26T19:49:33.6394544Z test_public_bindings 1/1 2025-08-26T19:49:33.6394954Z torch_np/numpy_tests/core/test_indexing 1/1 2025-08-26T19:49:33.6395295Z test_maskedtensor 1/1 2025-08-26T19:49:33.6395610Z torch_np/numpy_tests/lib/test_histograms 1/1 2025-08-26T19:49:33.6395967Z lazy/test_ts_opinfo 1/1 2025-08-26T19:49:33.6396253Z test_schema_check 1/1 2025-08-26T19:49:33.6396518Z optim/test_optim 1/1 2025-08-26T19:49:33.6396795Z test_quantization 2/4 2025-08-26T19:49:33.6397085Z Name: excluded (est. time: 0.0min) 2025-08-26T19:49:33.6397399Z Serial tests (0): 2025-08-26T19:49:33.6397644Z Parallel tests (0): 2025-08-26T19:49:33.6398155Z Running inductor/test_flex_attention 1/1 ... [2025-08-26 19:49:33.637459] 2025-08-26T19:49:33.6398636Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:49:33.6399770Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_flex_attention.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:49:33.637790] 2025-08-26T19:49:40.1607879Z 2025-08-26T19:49:40.1608989Z inductor/test_flex_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_attention_1.1_a4d5804deca751e1_.log 2025-08-26T19:49:40.1967749Z Running 644 items in this shard: test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_causal_mask_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod0_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod1_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod2_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod3_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod4_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod5_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod6_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_GQA_score_mod7_cpu_float32, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod0_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod1_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod2_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod3_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod4_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_aot_eager_gradcheck_score_mod5_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_autograd_function_in_score_mod_cpu, test/inductor/test_flex_attention.py::TestFlexAttentionCPU::test_block_mask_non_divisible_cpu, 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test/inductor/test_flex_attention.py::TestLearnableBiasesCPU::test_weird_bias_batch:2_head:4_seq_len:256_headdim:16_dtype:float32_cpu, test/inductor/test_flex_attention.py::TestLearnableBiasesCPU::test_weird_bias_batch:2_head:4_seq_len:277_headdim:16_dtype:float16_cpu, test/inductor/test_flex_attention.py::TestLearnableBiasesCPU::test_weird_bias_batch:2_head:4_seq_len:277_headdim:16_dtype:float32_cpu, test/inductor/test_flex_attention.py::TestLearnableBiasesCPU::test_weird_bias_batch:2_head:4_seq_len:37_headdim:16_dtype:float16_cpu, test/inductor/test_flex_attention.py::TestLearnableBiasesCPU::test_weird_bias_batch:2_head:4_seq_len:37_headdim:16_dtype:float32_cpu 2025-08-26T19:49:40.2317278Z 2025-08-26T19:49:40.6482864Z Uploading artifacts took 0.49 seconds 2025-08-26T19:49:40.6486157Z Running test_ci_sanity_check_fail 1/1 ... [2025-08-26 19:49:40.648447] 2025-08-26T19:49:40.6486637Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:49:40.6490497Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ci_sanity_check_fail.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:49:40.648813] 2025-08-26T19:49:53.4869245Z Running test_overrides 1/1 ... [2025-08-26 19:49:53.486592] 2025-08-26T19:49:53.4869720Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:49:53.4871833Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_overrides.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:49:53.486933] 2025-08-26T19:50:00.7606709Z 2025-08-26T19:50:00.7607642Z test_overrides 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_overrides_1.1_f16e972b98e3afa5_.log 2025-08-26T19:50:00.8114714Z Running 1470 items in this shard: test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_H___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase_T___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__backward_hooks___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__base___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__cdata___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__grad___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__grad_fn___get__, test/test_overrides.py::TestTorchFunctionOverride::test_TensorBase__post_accumulate_grad_hooks___get__, 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test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cholesky_solve, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clamp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clamp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clamp_max, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clamp_max_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clamp_min, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clamp_min_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clip, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clip_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_clone, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_coalesce, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_col_indices, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_conj, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_conj_physical, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_conj_physical_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_contiguous, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_copy_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_copysign, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_copysign_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_corrcoef, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cos, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cos_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cosh, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cosh_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_count_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cov, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cpu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cross, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_crow_indices, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cuda, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cummax, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cummin, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cumprod, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cumprod_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cumsum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_cumsum_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_data_ptr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_deg2rad, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_deg2rad_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_dense_dim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_dequantize, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_det, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_detach, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_detach_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_diag, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_diag_embed, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_diagflat, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_diagonal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_diagonal_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_diff, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_digamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_digamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_dim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_dim_order, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_dist, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_div, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_div_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_divide, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_divide_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_dot, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_double, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_dsplit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_element_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_eq, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_eq_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_erf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_erf_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_erfc, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_erfc_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_erfinv, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_erfinv_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_exp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_exp2, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_exp2_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_exp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_expand, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_expand_as, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_expm1, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_expm1_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_exponential_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fill_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fill_diagonal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fix, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fix_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_flatten, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_flip, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fliplr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_flipud, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_float, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_float_power, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_float_power_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_floor, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_floor_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_floor_divide, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_floor_divide_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fmax, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fmin, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fmod, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_fmod_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_frac, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_frac_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_frexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_gather, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_gcd, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_gcd_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ge, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ge_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_geometric_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_geqrf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ger, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_get_device, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_greater, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_greater_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_greater_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_greater_equal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_gt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_gt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_half, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hardshrink, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_has_names, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hash_tensor, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_heaviside, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_heaviside_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_histc, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_histogram, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hsplit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hypot, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_hypot_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_i0, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_i0_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igammac, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_igammac_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_add, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_add_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_copy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_copy_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_fill, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_fill_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_put, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_put_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_reduce_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_index_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_indices, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_inner, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_int, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_int_repr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ipu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_coalesced, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_complex, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_conj, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_contiguous, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_distributed, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_floating_point, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_inference, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_pinned, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_same_size, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_set_to, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_shared, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_is_signed, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isclose, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isfinite, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isinf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isnan, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isneginf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isposinf, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_isreal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_istft, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_item, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_kron, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_kthvalue, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lcm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lcm_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ldexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ldexp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_le, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_le_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lerp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lerp_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_less_equal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lgamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lgamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log10, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log10_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log1p, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log1p_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log2, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log2_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logaddexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logaddexp2, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logcumsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logdet, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_and, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_and_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_not, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_not_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_or, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_or_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_xor, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logical_xor_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logit, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logit_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_logsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_long, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lt, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lt_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_lu_solve, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_map2_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_map_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_fill, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_fill_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_scatter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_masked_select, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matrix_exp, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_matrix_power, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_max, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_maximum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mean, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_median, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_min, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_minimum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mode, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_module_load, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_moveaxis, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_movedim, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_msort, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mtia, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mul, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mul_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multinomial, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multiply, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_multiply_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mv, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mvlgamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_mvlgamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nan_to_num, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nan_to_num_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanmean, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanmedian, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nanquantile, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nansum, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_narrow, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_narrow_copy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ndimension, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ne, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ne_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_neg, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_neg_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_negative, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_negative_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nelement, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nextafter, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nextafter_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_nonzero_static, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_norm, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_not_equal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_not_equal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_numel, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_numpy, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_orgqr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_ormqr, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_outer, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_permute, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pin_memory, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pinverse, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_polygamma, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_polygamma_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_positive, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pow, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_pow_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_prelu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_prod, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_put, 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test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reciprocal, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_reciprocal_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_record_stream, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_refine_names, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_register_hook, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_register_post_accumulate_grad_hook, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_relu, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_relu_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_remainder, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_remainder_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rename, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_rename_, test/test_overrides.py::TestTorchFunctionOverride::test_Tensor_renorm, 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test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_logit, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_logsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_modified_bessel_i0, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_modified_bessel_i1, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_modified_bessel_k0, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_modified_bessel_k1, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_multigammaln, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_ndtr, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_ndtri, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_polygamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_psi, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_round, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_scaled_modified_bessel_k0, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_scaled_modified_bessel_k1, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_shifted_chebyshev_polynomial_t, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_shifted_chebyshev_polynomial_u, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_shifted_chebyshev_polynomial_v, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_shifted_chebyshev_polynomial_w, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_sinc, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_spherical_bessel_j0, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_xlog1py, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_xlogy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__C__special_special_zeta, test/test_overrides.py::TestTorchFunctionOverride::test_torch__assert_async, test/test_overrides.py::TestTorchFunctionOverride::test_torch__conj_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__functional_assert_async, test/test_overrides.py::TestTorchFunctionOverride::test_torch__fused_rms_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch__fw_primal_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__lobpcg_lobpcg, test/test_overrides.py::TestTorchFunctionOverride::test_torch__lowrank_pca_lowrank, test/test_overrides.py::TestTorchFunctionOverride::test_torch__lowrank_svd_lowrank, test/test_overrides.py::TestTorchFunctionOverride::test_torch__make_dual_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__native_batch_norm_legit, test/test_overrides.py::TestTorchFunctionOverride::test_torch__neg_view_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__reshape_alias_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__rowwise_prune, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sparse_broadcast_to_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_acos, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_asin, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_atan, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_cos, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_cosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sin, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_tan, test/test_overrides.py::TestTorchFunctionOverride::test_torch__sym_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch__values_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch__wrapped_linear_prepack, test/test_overrides.py::TestTorchFunctionOverride::test_torch__wrapped_quantized_linear_prepacked, test/test_overrides.py::TestTorchFunctionOverride::test_torch_abs, test/test_overrides.py::TestTorchFunctionOverride::test_torch_absolute, test/test_overrides.py::TestTorchFunctionOverride::test_torch_acos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_acosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adaptive_avg_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adaptive_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addbmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addcdiv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addcmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addmv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_addr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_adjoint, test/test_overrides.py::TestTorchFunctionOverride::test_torch_affine_grid_generator, test/test_overrides.py::TestTorchFunctionOverride::test_torch_alias_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_all, test/test_overrides.py::TestTorchFunctionOverride::test_torch_allclose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_amax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_amin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_aminmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_angle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_any, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arccos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arccosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arcsin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arcsinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctan2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_arctanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argsort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_argwhere, test/test_overrides.py::TestTorchFunctionOverride::test_torch_as_strided_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_as_strided_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_asin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_asinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atan2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_atanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_avg_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_baddbmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_backward_elemt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_backward_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_elemt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_gather_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_gather_stats_with_counts, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_batch_norm_update_stats, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bernoulli, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bilinear, test/test_overrides.py::TestTorchFunctionOverride::test_torch_binary_cross_entropy_with_logits, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bincount, test/test_overrides.py::TestTorchFunctionOverride::test_torch_binomial, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_and, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_left_shift, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_or, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_right_shift, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bitwise_xor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_broadcast_to, test/test_overrides.py::TestTorchFunctionOverride::test_torch_bucketize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ccol_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ceil, test/test_overrides.py::TestTorchFunctionOverride::test_torch_celu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_channel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cholesky_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_choose_qparams_optimized, test/test_overrides.py::TestTorchFunctionOverride::test_torch_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clamp_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clip, test/test_overrides.py::TestTorchFunctionOverride::test_torch_clone, test/test_overrides.py::TestTorchFunctionOverride::test_torch_col_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_column_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_combinations, test/test_overrides.py::TestTorchFunctionOverride::test_torch_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_concat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_concatenate, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conj_physical, test/test_overrides.py::TestTorchFunctionOverride::test_torch_constant_pad_nd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_tbc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_conv_transpose3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_copysign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_corrcoef, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cos, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosine_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cosine_similarity, test/test_overrides.py::TestTorchFunctionOverride::test_torch_count_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cov, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cross, test/test_overrides.py::TestTorchFunctionOverride::test_torch_crow_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ctc_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cummax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cummin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumprod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumsum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_cumulative_trapezoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_deg2rad, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dequantize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_det, test/test_overrides.py::TestTorchFunctionOverride::test_torch_detach, test/test_overrides.py::TestTorchFunctionOverride::test_torch_detach_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diag_embed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagflat, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diagonal_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_diff, test/test_overrides.py::TestTorchFunctionOverride::test_torch_digamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dsmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_dstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_embedding, test/test_overrides.py::TestTorchFunctionOverride::test_torch_embedding_bag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_empty_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_eq, test/test_overrides.py::TestTorchFunctionOverride::test_torch_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erfc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_erfinv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_exp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_exp2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_expand_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_expm1, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fake_quantize_per_channel_affine, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fake_quantize_per_tensor_affine, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_fp16_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_fp16_weight_fp32_activation, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_int8_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_int8_weight_fp32_activation, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_linear_quantize_weight, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_pack_gemm_matrix_fp16, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fbgemm_pack_quantized_matrix, test/test_overrides.py::TestTorchFunctionOverride::test_torch_feature_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_feature_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fix, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flatten, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flip, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fliplr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_flipud, test/test_overrides.py::TestTorchFunctionOverride::test_torch_float_power, test/test_overrides.py::TestTorchFunctionOverride::test_torch_floor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_floor_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fmod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frac, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_frobenius_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_full_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_atleast_3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_block_diag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_broadcast_tensors, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_cartesian_prod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_cdist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_chain_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_einsum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_lu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_meshgrid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_stft, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_tensordot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unique, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unique_consecutive, test/test_overrides.py::TestTorchFunctionOverride::test_torch_functional_unravel_index, test/test_overrides.py::TestTorchFunctionOverride::test_torch_fused_moving_avg_obs_fake_quant, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gather, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gcd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ge, test/test_overrides.py::TestTorchFunctionOverride::test_torch_geqrf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ger, test/test_overrides.py::TestTorchFunctionOverride::test_torch_get_device, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gradient, test/test_overrides.py::TestTorchFunctionOverride::test_torch_greater, test/test_overrides.py::TestTorchFunctionOverride::test_torch_greater_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler_2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_grid_sampler_3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gru, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gru_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_gt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hardshrink, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hash_tensor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_heaviside, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hinge_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histogram, test/test_overrides.py::TestTorchFunctionOverride::test_torch_histogramdd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hsmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_hypot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_i0, test/test_overrides.py::TestTorchFunctionOverride::test_torch_igamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_igammac, test/test_overrides.py::TestTorchFunctionOverride::test_torch_imag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_fill, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_put, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_index_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_inner, test/test_overrides.py::TestTorchFunctionOverride::test_torch_instance_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_int_repr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_distributed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_floating_point, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_inference, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_same_size, test/test_overrides.py::TestTorchFunctionOverride::test_torch_is_signed, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isclose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isfinite, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isinf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isnan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isneginf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isposinf, test/test_overrides.py::TestTorchFunctionOverride::test_torch_isreal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_istft, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kl_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kron, test/test_overrides.py::TestTorchFunctionOverride::test_torch_kthvalue, test/test_overrides.py::TestTorchFunctionOverride::test_torch_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lcm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ldexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_le, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lerp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_less, test/test_overrides.py::TestTorchFunctionOverride::test_torch_less_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lgamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log10, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log1p, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logaddexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logaddexp2, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logcumsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logdet, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_and, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_or, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logical_xor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_logsumexp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lstm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lstm_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lu_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_lu_unpack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_margin_ranking_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_fill, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_masked_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matmul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matrix_exp, test/test_overrides.py::TestTorchFunctionOverride::test_torch_matrix_power, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_maximum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_median, test/test_overrides.py::TestTorchFunctionOverride::test_torch_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_minimum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_add_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_convolution_transpose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_depthwise_convolution, test/test_overrides.py::TestTorchFunctionOverride::test_torch_miopen_rnn, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mode, test/test_overrides.py::TestTorchFunctionOverride::test_torch_moveaxis, test/test_overrides.py::TestTorchFunctionOverride::test_torch_movedim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_msort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mul, test/test_overrides.py::TestTorchFunctionOverride::test_torch_multinomial, test/test_overrides.py::TestTorchFunctionOverride::test_torch_multiply, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mv, test/test_overrides.py::TestTorchFunctionOverride::test_torch_mvlgamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nan_to_num, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanmean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanmedian, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nanquantile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nansum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_narrow, test/test_overrides.py::TestTorchFunctionOverride::test_torch_narrow_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_channel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_native_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ne, test/test_overrides.py::TestTorchFunctionOverride::test_torch_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_negative, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nextafter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional__threshold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_avg_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_avg_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_adaptive_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_affine_grid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_binary_cross_entropy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_binary_cross_entropy_with_logits, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_celu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_cosine_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_cross_entropy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_ctc_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_dropout3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_elu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_embedding, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_embedding_bag, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_feature_alpha_dropout, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_fractional_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_gaussian_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_glu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_grid_sample, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_group_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_gumbel_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_hardtanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_hinge_embedding_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_huber_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_instance_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_interpolate, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_kl_div, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_l1_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_layer_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_leaky_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_local_response_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_log_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_lp_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_margin_ranking_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool1d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool2d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_pool3d_with_indices, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_max_unpool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_mish, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_mse_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multi_head_attention_forward, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multi_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multilabel_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_multilabel_soft_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_normalize, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_pad, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_poisson_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_relu6, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_rms_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_rrelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_selu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_silu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_smooth_l1_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_soft_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softmin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_softsign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_tanhshrink, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_triplet_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_triplet_margin_with_distance_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_functional_unfold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_constant_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_kaiming_uniform_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_normal_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nn_init_uniform_, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nonzero, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nonzero_static, test/test_overrides.py::TestTorchFunctionOverride::test_torch_norm_except_dim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_not_equal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_nuclear_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_numel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ones_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_orgqr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ormqr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_outer, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pairwise_distance, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pdist, test/test_overrides.py::TestTorchFunctionOverride::test_torch_permute, test/test_overrides.py::TestTorchFunctionOverride::test_torch_permute_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pinverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pixel_shuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pixel_unshuffle, test/test_overrides.py::TestTorchFunctionOverride::test_torch_poisson, test/test_overrides.py::TestTorchFunctionOverride::test_torch_poisson_nll_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_polar, test/test_overrides.py::TestTorchFunctionOverride::test_torch_polygamma, test/test_overrides.py::TestTorchFunctionOverride::test_torch_positive, test/test_overrides.py::TestTorchFunctionOverride::test_torch_pow, test/test_overrides.py::TestTorchFunctionOverride::test_torch_prelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_prod, test/test_overrides.py::TestTorchFunctionOverride::test_torch_put, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_axis, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_scales, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_per_channel_zero_points, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_scale, test/test_overrides.py::TestTorchFunctionOverride::test_torch_q_zero_point, test/test_overrides.py::TestTorchFunctionOverride::test_torch_qr, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_channel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_tensor, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantize_per_tensor_dynamic, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_batch_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_gru_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_lstm_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool1d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool2d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_max_pool3d, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_rnn_relu_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_quantized_rnn_tanh_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rad2deg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rand_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_randint_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_randn_like, test/test_overrides.py::TestTorchFunctionOverride::test_torch_ravel, test/test_overrides.py::TestTorchFunctionOverride::test_torch_real, test/test_overrides.py::TestTorchFunctionOverride::test_torch_reciprocal, test/test_overrides.py::TestTorchFunctionOverride::test_torch_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_remainder, test/test_overrides.py::TestTorchFunctionOverride::test_torch_renorm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_repeat_interleave, test/test_overrides.py::TestTorchFunctionOverride::test_torch_reshape, test/test_overrides.py::TestTorchFunctionOverride::test_torch_resolve_conj, test/test_overrides.py::TestTorchFunctionOverride::test_torch_resolve_neg, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rms_norm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_relu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_relu_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rnn_tanh_cell, test/test_overrides.py::TestTorchFunctionOverride::test_torch_roll, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rot90, test/test_overrides.py::TestTorchFunctionOverride::test_torch_round, test/test_overrides.py::TestTorchFunctionOverride::test_torch_row_indices_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_row_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rrelu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rsqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_rsub, test/test_overrides.py::TestTorchFunctionOverride::test_torch_saddmm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter_add, test/test_overrides.py::TestTorchFunctionOverride::test_torch_scatter_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_searchsorted, test/test_overrides.py::TestTorchFunctionOverride::test_torch_segment_reduce, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_select_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_selu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sgn, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sigmoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sign, test/test_overrides.py::TestTorchFunctionOverride::test_torch_signbit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sin, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sinc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sinh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_inverse, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slice_scatter, test/test_overrides.py::TestTorchFunctionOverride::test_torch_slogdet, test/test_overrides.py::TestTorchFunctionOverride::test_torch_smm, test/test_overrides.py::TestTorchFunctionOverride::test_torch_softmax, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sort, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_split_with_sizes_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sqrt, test/test_overrides.py::TestTorchFunctionOverride::test_torch_square, test/test_overrides.py::TestTorchFunctionOverride::test_torch_squeeze, test/test_overrides.py::TestTorchFunctionOverride::test_torch_squeeze_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_stack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_std, test/test_overrides.py::TestTorchFunctionOverride::test_torch_std_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sub, test/test_overrides.py::TestTorchFunctionOverride::test_torch_subtract, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_svd, test/test_overrides.py::TestTorchFunctionOverride::test_torch_swapaxes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_swapdims, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_float, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_int, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_ite, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_max, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_min, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_not, test/test_overrides.py::TestTorchFunctionOverride::test_torch_sym_sum, test/test_overrides.py::TestTorchFunctionOverride::test_torch_t, test/test_overrides.py::TestTorchFunctionOverride::test_torch_t_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_take, test/test_overrides.py::TestTorchFunctionOverride::test_torch_take_along_dim, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tan, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tanh, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tensor_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_threshold, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tile, test/test_overrides.py::TestTorchFunctionOverride::test_torch_topk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trace, test/test_overrides.py::TestTorchFunctionOverride::test_torch_transpose, test/test_overrides.py::TestTorchFunctionOverride::test_torch_transpose_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trapezoid, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trapz, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triangular_solve, test/test_overrides.py::TestTorchFunctionOverride::test_torch_tril, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triplet_margin_loss, test/test_overrides.py::TestTorchFunctionOverride::test_torch_triu, test/test_overrides.py::TestTorchFunctionOverride::test_torch_true_divide, test/test_overrides.py::TestTorchFunctionOverride::test_torch_trunc, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unbind, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unbind_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unflatten, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unfold_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_chunk, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_split, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsafe_split_with_sizes, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsqueeze, test/test_overrides.py::TestTorchFunctionOverride::test_torch_unsqueeze_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_values_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_var, test/test_overrides.py::TestTorchFunctionOverride::test_torch_var_mean, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vdot, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_complex, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_complex_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_real, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_as_real_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_view_copy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vsplit, test/test_overrides.py::TestTorchFunctionOverride::test_torch_vstack, test/test_overrides.py::TestTorchFunctionOverride::test_torch_where, test/test_overrides.py::TestTorchFunctionOverride::test_torch_xlogy, test/test_overrides.py::TestTorchFunctionOverride::test_torch_zeros_like, test/test_overrides.py::TestTorchFunctionOverride::test_user_implementation_raises, test/test_overrides.py::TestEinsumOverride::test_wrapper, test/test_overrides.py::TestGradCheckOverride::test_gradcheck, test/test_overrides.py::TestNamedTuple::test_max, test/test_overrides.py::TestGradNewOnesOverride::test_newones, test/test_overrides.py::TestPickle::test_pickle, test/test_overrides.py::TestBroadcastAllOverride::test_broadcast_all, test/test_overrides.py::TestWrapTorchFunction::test_wrap_torch_function, test/test_overrides.py::TestIndexing::test_getitem, test/test_overrides.py::TestIndexing::test_getitem_subclass, test/test_overrides.py::TestIndexing::test_setitem, test/test_overrides.py::TestIndexing::test_setitem_subclass, test/test_overrides.py::TestIndexing::test_setitem_val, test/test_overrides.py::TestIterator::test_iterator, test/test_overrides.py::TestRNN::test_rnn, test/test_overrides.py::TestDisabledTorchFunction::test_parameter_does_not_prevent_dispatch, test/test_overrides.py::TestResolveName::test_resolve_name, test/test_overrides.py::TestTorchFunctionWarning::test_warn_on_invalid_torch_function_standalone_class, test/test_overrides.py::TestTorchFunctionWarning::test_warn_on_invalid_torch_function_tensor_subclass, test/test_overrides.py::TestDisabledUserWarnings::test_no_implicit_user_warning_for_deprecated_functions, test/test_overrides.py::TestTorchFunctionMode::test_all_same_mode, test/test_overrides.py::TestTorchFunctionMode::test_basic, test/test_overrides.py::TestTorchFunctionMode::test_custom_device_type, test/test_overrides.py::TestTorchFunctionMode::test_device_context_semantics, test/test_overrides.py::TestTorchFunctionMode::test_disable_enable_subclass, test/test_overrides.py::TestTorchFunctionMode::test_disable_enable_torch_function_ctx, test/test_overrides.py::TestTorchFunctionMode::test_disable_subclass_mode, test/test_overrides.py::TestTorchFunctionMode::test_disable_subclass_not_mode, test/test_overrides.py::TestTorchFunctionMode::test_distributions_bernoulli, test/test_overrides.py::TestTorchFunctionMode::test_error_using_class_method_on_mode, test/test_overrides.py::TestTorchFunctionMode::test_factory_override, test/test_overrides.py::TestTorchFunctionMode::test_get_cur_mode, test/test_overrides.py::TestTorchFunctionMode::test_get_mode_stack, test/test_overrides.py::TestTorchFunctionMode::test_getitem_call, test/test_overrides.py::TestTorchFunctionMode::test_mode_notimplemented_loop, test/test_overrides.py::TestTorchFunctionMode::test_modes_handle_first, test/test_overrides.py::TestTorchFunctionMode::test_modes_return_notimplemented, test/test_overrides.py::TestTorchFunctionMode::test_nested_modes_with_python_has_torch_function, test/test_overrides.py::TestTorchFunctionMode::test_nested_same_mode, test/test_overrides.py::TestTorchFunctionMode::test_nn_parse_to, test/test_overrides.py::TestTorchFunctionMode::test_reentrant_mode_idiom, test/test_overrides.py::TestTorchFunctionMode::test_restacking_with_ancestor, test/test_overrides.py::TestTorchFunctionMode::test_subclass_hash, test/test_overrides.py::TestTorchFunctionMode::test_torch_function_all_disabled_api, test/test_overrides.py::TestTorchFunctionMode::test_with_mode, test/test_overrides.py::TestTorchFunctionMode::test_with_mode_created_separately, test/test_overrides.py::TestTorchFunctionMode::test_with_nested_modes 2025-08-26T19:50:00.8608818Z 2025-08-26T19:50:00.8609026Z Running test_reductions 1/1 ... [2025-08-26 19:50:00.762608] 2025-08-26T19:50:00.8609460Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:50:00.8610536Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_reductions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:50:00.762914] 2025-08-26T19:53:15.3906280Z 2025-08-26T19:53:15.3907182Z test_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_reductions_1.1_6831566037f10b73_.log 2025-08-26T19:53:15.5740471Z Running 4673 items in this shard: test/test_reductions.py::TestReductionsCPU::test_accreal_type_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_all_any_vs_numpy_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_all_any_with_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_all_issue117215_cpu, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_amax_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_amin_amax_some_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_amin_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_aminmax_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_aminmax_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_aminmax_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_aminmax_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_argminmax_axis_with_dim_one_cpu, test/test_reductions.py::TestReductionsCPU::test_argminmax_large_axis_cpu, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_argminmax_multiple_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_bincount_cpu, test/test_reductions.py::TestReductionsCPU::test_bucketization_cpu, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_count_nonzero_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_cumprod_integer_upcast_cpu, test/test_reductions.py::TestReductionsCPU::test_cumsum_integer_upcast_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_dim_arg_reduction_scalar_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_amax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_any_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_linalg_vector_norm_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_prod_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_std_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_sum_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default__refs_var_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_amax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_any_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_argmax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_argmin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_hash_tensor_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_amax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_any_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_linalg_vector_norm_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_prod_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_std_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_sum_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim__refs_var_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_all_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_amax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_any_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_argmax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_argmin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_count_nonzero_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_hash_tensor_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_linalg_vector_norm_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_masked_amax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_masked_amin_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_masked_argmax_cpu, test/test_reductions.py::TestReductionsCPU::test_dim_default_keepdim_masked_argmin_cpu, 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test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_masked_var_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_mean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nanmean_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nanmean_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nanmean_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nanmean_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_nansum_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_prod_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_std_unbiased_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_sum_cpu_uint8, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_result_dtype_var_unbiased_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_std_correction_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_std_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_std_mean_all_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_std_mean_correction_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_std_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_std_mean_some_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_std_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_all_cpu_bool, test/test_reductions.py::TestReductionsCPU::test_sum_all_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_cpu_device_mismatch_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_dim_reduction_uint8_overflow_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_integer_upcast_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_lowp_cpu_bfloat16, test/test_reductions.py::TestReductionsCPU::test_sum_noncontig_lowp_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_sum_out_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_parallel_cpu, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float16, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int16, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int32, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int64, test/test_reductions.py::TestReductionsCPU::test_sum_vs_numpy_cpu_int8, test/test_reductions.py::TestReductionsCPU::test_tensor_compare_ops_argmax_argmix_kthvalue_dim_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_tensor_compare_ops_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_tensor_reduce_ops_empty_cpu, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_correction_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_var_cpu, test/test_reductions.py::TestReductionsCPU::test_var_dim_cpu, test/test_reductions.py::TestReductionsCPU::test_var_large_input_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_all_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_mean_correction_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_var_mean_cpu, test/test_reductions.py::TestReductionsCPU::test_var_mean_some_dims_cpu, test/test_reductions.py::TestReductionsCPU::test_var_stability2_cpu, test/test_reductions.py::TestReductionsCPU::test_var_stability_cpu, test/test_reductions.py::TestReductionsCPU::test_var_unbiased_cpu, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_var_vs_numpy_cpu_float64, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_complex128, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_complex64, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_float32, test/test_reductions.py::TestReductionsCPU::test_warn_invalid_degrees_of_freedom_cpu_float64 2025-08-26T19:53:15.7796540Z 2025-08-26T19:53:15.7796977Z Running test_tensor_creation_ops 1/1 ... [2025-08-26 19:53:15.396818] 2025-08-26T19:53:15.7797866Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:53:15.7800304Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensor_creation_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:53:15.397134] 2025-08-26T19:53:35.6882928Z 2025-08-26T19:53:35.6883636Z test_tensor_creation_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensor_creation_ops_1.1_f32e180e282ac664_.log 2025-08-26T19:53:35.7130385Z Running 641 items in this shard: test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_device_vs_cpu_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_lowp_cpu_bfloat16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_arange_lowp_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_as_strided_neg_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_as_tensor_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_block_diag_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_block_diag_scipy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cartesian_prod_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat2_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_all_dtypes_and_devices_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_big_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_empty_legacy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_in_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_mem_overlap_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_channels_last_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_fast_path_dim0_dim1_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_out_memory_format_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_cat_preserve_channels_last_cpu, 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test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_refs_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_repeat_interleave_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_roll_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_bartlett_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_blackman_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hamming_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_window_functions_window_hann_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_bartlett_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_bartlett_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_blackman_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_blackman_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_cosine_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_cosine_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hamming_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hamming_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hann_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_hann_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_nuttall_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_signal_windows_functions_window_nuttall_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_simple_scalar_cast_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_stack_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_stack_out_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_storage_filename_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_strided_mismatched_stride_shape_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_ctor_device_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_device_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factories_empty_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_copy_var_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_gpu_type_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_gpu_type_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_factory_type_inference_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_from_non_writable_numpy_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_tensor_from_sequence_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_floating_dtype_error_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_out_dtype_error_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_out_dtype_error_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_same_dtype_error_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_complex_same_dtype_error_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_polar_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_torch_polar_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_unpack_double_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_unpack_double_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vander_types_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vsplit_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_complex128, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_float64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_int8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_vstack_row_stack_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_cpu, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_bool, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_complex64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_float16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_float32, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_int16, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_int64, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_dtype_layout_device_match_cpu_uint8, test/test_tensor_creation_ops.py::TestTensorCreationCPU::test_zeros_out_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_normal_std_error_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex128, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_complex64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_rand_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_distribution_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randint_inference_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_bfloat16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex128, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_complex64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randn_cpu_float64, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_random_neg_values_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_device_compatibility_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_randperm_large_cpu, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float16, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float32, test/test_tensor_creation_ops.py::TestRandomTensorCreationCPU::test_uniform_from_to_cpu_float64, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_empty_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_full_like_inference_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_ones_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_ones_like_multiple_device_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_zeros_like_cpu, test/test_tensor_creation_ops.py::TestLikeTensorCreationCPU::test_zeros_like_multiple_device_cpu, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_byte_to_int_cpu, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_invalid_positional_args_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_non_writable_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_not_a_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_requires_grad_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_same_type_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_shared_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_and_offset_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_count_cpu_uint8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_bool, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_complex128, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_complex64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_float64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_int8, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint16, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint32, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint64, test/test_tensor_creation_ops.py::TestBufferProtocolCPU::test_with_offset_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_dlpack_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_numpy_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_alias_from_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_astensor_consistency_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_buffer_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_dlpack_mult_devices_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_numpy_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_from_tensor_mult_devices_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_list_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_bfloat16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_bool, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_complex128, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_float64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int16, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_int8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_copy_tensor_cpu_uint8, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_default_device_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_device_without_index_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_numpy_scalars_cpu, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_retain_autograd_history_cpu_complex64, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_retain_autograd_history_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_unsupported_alias_cpu_float32, test/test_tensor_creation_ops.py::TestAsArrayCPU::test_unsupported_alias_mult_devices_cpu_float32 2025-08-26T19:53:35.7372065Z 2025-08-26T19:53:35.7372327Z Running test_cpp_extensions_mtia_backend 1/1 ... [2025-08-26 19:53:35.689312] 2025-08-26T19:53:35.7372834Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:53:35.7373987Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_mtia_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:53:35.689598] 2025-08-26T19:53:39.2584163Z 2025-08-26T19:53:39.2585277Z test_cpp_extensions_mtia_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_mtia_backend_1.1_e234f9ba252a9db3_.log 2025-08-26T19:53:39.2588431Z Running 5 items in this shard: test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_device_context, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_get_device_module, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_basic, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_context, test/test_cpp_extensions_mtia_backend.py::TestCppExtensionMTIABackend::test_stream_context_different_device 2025-08-26T19:53:39.2590853Z 2025-08-26T19:53:39.2591033Z Running test_nn 1/1 ... [2025-08-26 19:53:39.258601] 2025-08-26T19:53:39.2591426Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:53:39.2592457Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_nn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:53:39.258889] 2025-08-26T19:55:50.3386502Z 2025-08-26T19:55:50.3387277Z test_nn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_nn_1.1_be56ff8b70992a27_.log 2025-08-26T19:55:50.4613199Z Running 2230 items in this shard: test/test_nn.py::TestNN::test_AdaptiveLogSoftmax, test/test_nn.py::TestNN::test_AdaptiveLogSoftmax_cuda, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_BCELoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_BCELoss_no_reduce, test/test_nn.py::TestNN::test_BCELoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_no_reduce_scalar, test/test_nn.py::TestNN::test_BCELoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_scalar, test/test_nn.py::TestNN::test_BCELoss_weights_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_legacy_enum, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_legacy_enum_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_scalar, test/test_nn.py::TestNN::test_BCEWithLogitsLoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_CELU_no_batch_dim, test/test_nn.py::TestNN::test_CELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_CTCLoss_critical_target_len, test/test_nn.py::TestNN::test_CTCLoss_lengthchecks_cpu, test/test_nn.py::TestNN::test_CTCLoss_lengthchecks_cuda, test/test_nn.py::TestNN::test_CTCLoss_long_targets, test/test_nn.py::TestNN::test_CTCLoss_typechecks, test/test_nn.py::TestNN::test_CTCLoss_zero_infinity, test/test_nn.py::TestNN::test_CTCLoss_zero_lengths, test/test_nn.py::TestNN::test_Conv1d, test/test_nn.py::TestNN::test_Conv1d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_cuda, test/test_nn.py::TestNN::test_Conv1d_dilated, test/test_nn.py::TestNN::test_Conv1d_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_groups, test/test_nn.py::TestNN::test_Conv1d_groups_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1, test/test_nn.py::TestNN::test_Conv1d_pad1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad1size1, test/test_nn.py::TestNN::test_Conv1d_pad1size1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad2, test/test_nn.py::TestNN::test_Conv1d_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_pad2size1, test/test_nn.py::TestNN::test_Conv1d_pad2size1_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same, test/test_nn.py::TestNN::test_Conv1d_pad_same2, test/test_nn.py::TestNN::test_Conv1d_pad_same2_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv1d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv1d_pad_valid, test/test_nn.py::TestNN::test_Conv1d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv1d_reflect_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_reflect_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv1d_stride, test/test_nn.py::TestNN::test_Conv1d_stride_cuda, test/test_nn.py::TestNN::test_Conv1d_zero_batch, test/test_nn.py::TestNN::test_Conv1d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv1d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv1d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d, test/test_nn.py::TestNN::test_Conv2d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise, test/test_nn.py::TestNN::test_Conv2d_depthwise_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_dilated, test/test_nn.py::TestNN::test_Conv2d_depthwise_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_padded, test/test_nn.py::TestNN::test_Conv2d_depthwise_padded_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided, test/test_nn.py::TestNN::test_Conv2d_depthwise_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_depthwise_with_multiplier, test/test_nn.py::TestNN::test_Conv2d_depthwise_with_multiplier_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated, test/test_nn.py::TestNN::test_Conv2d_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_dilated_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_dilated_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_groups, test/test_nn.py::TestNN::test_Conv2d_groups_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_thnn, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_groups_thnn_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_no_bias, test/test_nn.py::TestNN::test_Conv2d_no_bias_cuda, test/test_nn.py::TestNN::test_Conv2d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_same, test/test_nn.py::TestNN::test_Conv2d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv2d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv2d_pad_valid, test/test_nn.py::TestNN::test_Conv2d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv2d_padding, test/test_nn.py::TestNN::test_Conv2d_padding_cuda, test/test_nn.py::TestNN::test_Conv2d_padding_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_padding_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_reflect_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_reflect_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv2d_strided, test/test_nn.py::TestNN::test_Conv2d_strided_cuda, test/test_nn.py::TestNN::test_Conv2d_strided_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_strided_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch, test/test_nn.py::TestNN::test_Conv2d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor, test/test_nn.py::TestNN::test_Conv2d_zero_batch_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv2d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv2d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_1x1x1_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_circular_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_cuda, test/test_nn.py::TestNN::test_Conv3d_dilated, test/test_nn.py::TestNN::test_Conv3d_dilated_cuda, test/test_nn.py::TestNN::test_Conv3d_dilated_strided, test/test_nn.py::TestNN::test_Conv3d_dilated_strided_cuda, test/test_nn.py::TestNN::test_Conv3d_groups, test/test_nn.py::TestNN::test_Conv3d_groups_cuda, test/test_nn.py::TestNN::test_Conv3d_groups_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias, test/test_nn.py::TestNN::test_Conv3d_no_bias_cuda, test/test_nn.py::TestNN::test_Conv3d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_same, test/test_nn.py::TestNN::test_Conv3d_pad_same_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_same_dilated, test/test_nn.py::TestNN::test_Conv3d_pad_same_dilated_cuda, test/test_nn.py::TestNN::test_Conv3d_pad_valid, test/test_nn.py::TestNN::test_Conv3d_pad_valid_cuda, test/test_nn.py::TestNN::test_Conv3d_replicate_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_replicate_stride2_pad2_cuda, test/test_nn.py::TestNN::test_Conv3d_stride, test/test_nn.py::TestNN::test_Conv3d_stride_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding, test/test_nn.py::TestNN::test_Conv3d_stride_padding_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_padding_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_stride_padding_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_stride_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_stride_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_zero_batch, test/test_nn.py::TestNN::test_Conv3d_zero_batch_cuda, test/test_nn.py::TestNN::test_Conv3d_zero_batch_with_long_tensor, test/test_nn.py::TestNN::test_Conv3d_zero_batch_with_long_tensor_cuda, test/test_nn.py::TestNN::test_Conv3d_zeros_stride2_pad2, test/test_nn.py::TestNN::test_Conv3d_zeros_stride2_pad2_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d, test/test_nn.py::TestNN::test_ConvTranspose1d_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated, test/test_nn.py::TestNN::test_ConvTranspose1d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_groups, test/test_nn.py::TestNN::test_ConvTranspose1d_groups_cuda, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose1d_no_bias_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d, test/test_nn.py::TestNN::test_ConvTranspose2d_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_dilated_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_groups_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_no_bias_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor, test/test_nn.py::TestNN::test_ConvTranspose2d_with_long_tensor_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d, test/test_nn.py::TestNN::test_ConvTranspose3d_cuda, test/test_nn.py::TestNN::test_ConvTranspose3d_dilated, test/test_nn.py::TestNN::test_ConvTranspose3d_dilated_cuda, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_CosineEmbeddingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_CrossMapLRN2d, test/test_nn.py::TestNN::test_CrossMapLRN2d_cuda, test/test_nn.py::TestNN::test_ELU_no_batch_dim, test/test_nn.py::TestNN::test_ELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Embedding, test/test_nn.py::TestNN::test_EmbeddingBag_discontiguous, test/test_nn.py::TestNN::test_EmbeddingBag_discontiguous_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_max, test/test_nn.py::TestNN::test_EmbeddingBag_max_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_max_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_max_padding_idx_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean, test/test_nn.py::TestNN::test_EmbeddingBag_mean_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_mean_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_mean_padding_idx_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sparse, test/test_nn.py::TestNN::test_EmbeddingBag_sparse_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sum, test/test_nn.py::TestNN::test_EmbeddingBag_sum_cuda, test/test_nn.py::TestNN::test_EmbeddingBag_sum_padding_idx, test/test_nn.py::TestNN::test_EmbeddingBag_sum_padding_idx_cuda, test/test_nn.py::TestNN::test_Embedding_cuda, test/test_nn.py::TestNN::test_Embedding_discontiguous, test/test_nn.py::TestNN::test_Embedding_discontiguous_cuda, test/test_nn.py::TestNN::test_Embedding_sparse, test/test_nn.py::TestNN::test_Embedding_sparse_cuda, test/test_nn.py::TestNN::test_Flatten, test/test_nn.py::TestNN::test_Flatten_cuda, test/test_nn.py::TestNN::test_Flatten_no_batch_dim, test/test_nn.py::TestNN::test_Flatten_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Fold, test/test_nn.py::TestNN::test_Fold_cuda, test/test_nn.py::TestNN::test_Fold_int_input, test/test_nn.py::TestNN::test_Fold_int_input_cuda, test/test_nn.py::TestNN::test_Fold_no_batch_dim_input, test/test_nn.py::TestNN::test_Fold_no_batch_dim_input_cuda, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input, test/test_nn.py::TestNN::test_Fold_no_batch_dim_int_input_cuda, test/test_nn.py::TestNN::test_GELU_no_batch_dim, test/test_nn.py::TestNN::test_GELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_GLU_no_batch_dim, test/test_nn.py::TestNN::test_GLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardshrink_no_batch_dim, test/test_nn.py::TestNN::test_Hardshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardsigmoid_no_batch_dim, test/test_nn.py::TestNN::test_Hardsigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardswish_no_batch_dim, test/test_nn.py::TestNN::test_Hardswish_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Hardtanh_no_batch_dim, test/test_nn.py::TestNN::test_Hardtanh_no_batch_dim_cuda, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_margin_no_reduce, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_margin_no_reduce_cuda, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_reduce, test/test_nn.py::TestNN::test_HingeEmbeddingLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_HuberLoss_delta, test/test_nn.py::TestNN::test_HuberLoss_delta_cuda, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_HuberLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean, test/test_nn.py::TestNN::test_KLDivLoss_batch_mean_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_KLDivLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_log_target_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target, test/test_nn.py::TestNN::test_KLDivLoss_no_reduce_scalar_log_target_cuda, test/test_nn.py::TestNN::test_KLDivLoss_with_log_target_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_with_log_target_no_reduce_cuda, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce, test/test_nn.py::TestNN::test_KLDivLoss_with_target_no_reduce_cuda, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_L1Loss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_L1Loss_no_reduce, test/test_nn.py::TestNN::test_L1Loss_no_reduce_complex, test/test_nn.py::TestNN::test_L1Loss_no_reduce_complex_cuda, test/test_nn.py::TestNN::test_L1Loss_no_reduce_cuda, test/test_nn.py::TestNN::test_L1Loss_no_reduce_scalar, test/test_nn.py::TestNN::test_L1Loss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_LSTM_cell, test/test_nn.py::TestNN::test_LSTM_cell_forward_hidden_size, test/test_nn.py::TestNN::test_LSTM_cell_forward_input_size, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_cuda, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_eval, test/test_nn.py::TestNN::test_LayerNorm_3d_no_affine_large_feature_eval_cuda, test/test_nn.py::TestNN::test_LeakyReLU_no_batch_dim, test/test_nn.py::TestNN::test_LeakyReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Linear, test/test_nn.py::TestNN::test_Linear_cuda, test/test_nn.py::TestNN::test_Linear_no_batch_dim, test/test_nn.py::TestNN::test_Linear_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Linear_no_bias, test/test_nn.py::TestNN::test_Linear_no_bias_cuda, test/test_nn.py::TestNN::test_LogSigmoid_no_batch_dim, test/test_nn.py::TestNN::test_LogSigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MSELoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MSELoss_no_reduce, test/test_nn.py::TestNN::test_MSELoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MSELoss_no_reduce_scalar, test/test_nn.py::TestNN::test_MSELoss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MarginRankingLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MaxUnpool1d_net, test/test_nn.py::TestNN::test_MaxUnpool1d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool1d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net, test/test_nn.py::TestNN::test_MaxUnpool2d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool2d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool2d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_MaxUnpool3d_net, test/test_nn.py::TestNN::test_MaxUnpool3d_net_cuda, test/test_nn.py::TestNN::test_MaxUnpool3d_net_no_batch_dim, test/test_nn.py::TestNN::test_MaxUnpool3d_net_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Mish_no_batch_dim, test/test_nn.py::TestNN::test_Mish_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ModuleDict, test/test_nn.py::TestNN::test_ModuleList, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_0d_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_0d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_1d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_index_neg, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_index_neg_cuda, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_MultiLabelSoftMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_1d_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_1d_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_margin_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_margin_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_p_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_p_no_reduce_cuda, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce, test/test_nn.py::TestNN::test_MultiMarginLoss_weights_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss2d_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLossNd_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_NLLLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_NLLLoss_no_reduce, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_ignore_index, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_cuda, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_neg, test/test_nn.py::TestNN::test_NLLLoss_no_reduce_weights_ignore_index_neg_cuda, test/test_nn.py::TestNN::test_PReLU_backward_requires_grad_false, test/test_nn.py::TestNN::test_PReLU_no_batch_dim, test/test_nn.py::TestNN::test_PReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_PairwiseDistance, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_lhs, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_lhs_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_rhs, test/test_nn.py::TestNN::test_PairwiseDistance_broadcast_rhs_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_no_batch_dim, test/test_nn.py::TestNN::test_PairwiseDistance_no_batch_dim_cuda, test/test_nn.py::TestNN::test_PairwiseDistance_with_non_default_args, test/test_nn.py::TestNN::test_PairwiseDistance_with_non_default_args_cuda, test/test_nn.py::TestNN::test_ParameterDict, test/test_nn.py::TestNN::test_ParameterDict_replication, test/test_nn.py::TestNN::test_ParameterList, test/test_nn.py::TestNN::test_ParameterList_meta, test/test_nn.py::TestNN::test_ParameterList_replication, test/test_nn.py::TestNN::test_PixelShuffle, test/test_nn.py::TestNN::test_PixelShuffle_cuda, test/test_nn.py::TestNN::test_PixelUnshuffle, test/test_nn.py::TestNN::test_PixelUnshuffle_cuda, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_reduce, test/test_nn.py::TestNN::test_PoissonNLLLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_RNN_cell, test/test_nn.py::TestNN::test_RNN_cell_forward_zero_hidden_size, test/test_nn.py::TestNN::test_RNN_cell_no_broadcasting, test/test_nn.py::TestNN::test_RNN_change_dropout, test/test_nn.py::TestNN::test_RNN_cpu_vs_cudnn_no_dropout, test/test_nn.py::TestNN::test_RNN_cpu_vs_cudnn_with_dropout, test/test_nn.py::TestNN::test_RNN_cudnn_weight_norm, test/test_nn.py::TestNN::test_RNN_dropout, test/test_nn.py::TestNN::test_RNN_dropout_state, test/test_nn.py::TestNN::test_RNN_input_size_zero, test/test_nn.py::TestNN::test_RNN_nonlinearity, test/test_nn.py::TestNN::test_RNN_nonlinearity_passed_as_arg, test/test_nn.py::TestNN::test_RReLU, test/test_nn.py::TestNN::test_RReLU_cuda, test/test_nn.py::TestNN::test_RReLU_no_batch_dim, test/test_nn.py::TestNN::test_RReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_RReLU_with_up_down, test/test_nn.py::TestNN::test_RReLU_with_up_down_cuda, test/test_nn.py::TestNN::test_RReLU_with_up_down_scalar, test/test_nn.py::TestNN::test_RReLU_with_up_down_scalar_cuda, test/test_nn.py::TestNN::test_ReLU6_no_batch_dim, test/test_nn.py::TestNN::test_ReLU6_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReLU_no_batch_dim, test/test_nn.py::TestNN::test_ReLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d, test/test_nn.py::TestNN::test_ReplicationPad3d_complex, test/test_nn.py::TestNN::test_ReplicationPad3d_complex_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_cuda, test/test_nn.py::TestNN::test_ReplicationPad3d_no_batch_dim, test/test_nn.py::TestNN::test_ReplicationPad3d_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SELU_no_batch_dim, test/test_nn.py::TestNN::test_SELU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sequential_add, test/test_nn.py::TestNN::test_Sequential_append, test/test_nn.py::TestNN::test_Sequential_delitem, test/test_nn.py::TestNN::test_Sequential_extend, test/test_nn.py::TestNN::test_Sequential_getitem, test/test_nn.py::TestNN::test_Sequential_iadd, test/test_nn.py::TestNN::test_Sequential_imul, test/test_nn.py::TestNN::test_Sequential_insert, test/test_nn.py::TestNN::test_Sequential_insert_fail_case, test/test_nn.py::TestNN::test_Sequential_mul, test/test_nn.py::TestNN::test_Sequential_pop, test/test_nn.py::TestNN::test_Sequential_rmul, test/test_nn.py::TestNN::test_Sequential_setitem, test/test_nn.py::TestNN::test_Sequential_setitem_named, test/test_nn.py::TestNN::test_SiLU_no_batch_dim, test/test_nn.py::TestNN::test_SiLU_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Sigmoid_no_batch_dim, test/test_nn.py::TestNN::test_Sigmoid_no_batch_dim_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_beta, test/test_nn.py::TestNN::test_SmoothL1Loss_beta_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_SmoothL1Loss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_scalar, test/test_nn.py::TestNN::test_SmoothL1Loss_no_reduce_scalar_cuda, test/test_nn.py::TestNN::test_SmoothL1Loss_zero_beta, test/test_nn.py::TestNN::test_SmoothL1Loss_zero_beta_cuda, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_SoftMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_SoftMarginLoss_no_reduce, test/test_nn.py::TestNN::test_SoftMarginLoss_no_reduce_cuda, test/test_nn.py::TestNN::test_Softplus_no_batch_dim, test/test_nn.py::TestNN::test_Softplus_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Softshrink_no_batch_dim, test/test_nn.py::TestNN::test_Softshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Softsign_no_batch_dim, test/test_nn.py::TestNN::test_Softsign_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Tanh_no_batch_dim, test/test_nn.py::TestNN::test_Tanh_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Tanhshrink_no_batch_dim, test/test_nn.py::TestNN::test_Tanhshrink_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Threshold_no_batch_dim, test/test_nn.py::TestNN::test_Threshold_no_batch_dim_cuda, test/test_nn.py::TestNN::test_TransformerDecoderLayer_gelu_activation, test/test_nn.py::TestNN::test_TransformerDecoderLayer_gelu_activation_cuda, test/test_nn.py::TestNN::test_TransformerDecoderLayer_relu_activation, test/test_nn.py::TestNN::test_TransformerDecoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_gelu_activation, test/test_nn.py::TestNN::test_TransformerEncoderLayer_gelu_activation_cuda, test/test_nn.py::TestNN::test_TransformerEncoderLayer_relu_activation, test/test_nn.py::TestNN::test_TransformerEncoderLayer_relu_activation_cuda, test/test_nn.py::TestNN::test_Transformer_cell, test/test_nn.py::TestNN::test_Transformer_multilayer_coder, test/test_nn.py::TestNN::test_Transformer_multilayer_coder_cuda, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_mean_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_none_cuda_half, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_double, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_float, test/test_nn.py::TestNN::test_TripletMarginLoss_no_batch_dim_sum_cuda_half, test/test_nn.py::TestNN::test_Unflatten_no_batch_dim, test/test_nn.py::TestNN::test_Unflatten_no_batch_dim_cuda, test/test_nn.py::TestNN::test_Unfold, test/test_nn.py::TestNN::test_Unfold_cuda, test/test_nn.py::TestNN::test_Unfold_int_input, test/test_nn.py::TestNN::test_Unfold_int_input_cuda, test/test_nn.py::TestNN::test_adaptive_log_softmax, test/test_nn.py::TestNN::test_add_module, test/test_nn.py::TestNN::test_add_module_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_affine_grid, test/test_nn.py::TestNN::test_affine_grid_3d, test/test_nn.py::TestNN::test_affine_grid_backward_cl_cf_consistency_device_cpu_nd_2, test/test_nn.py::TestNN::test_affine_grid_backward_cl_cf_consistency_device_cpu_nd_3, test/test_nn.py::TestNN::test_affine_grid_error_checking, test/test_nn.py::TestNN::test_assignment, test/test_nn.py::TestNN::test_batch_norm_update_stats, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_inference_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_2D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_inference_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_float32, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_cpu_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_float32, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_bfloat16, test/test_nn.py::TestNN::test_batchnorm_3D_train_NCHW_vs_native_mixed_float16, test/test_nn.py::TestNN::test_batchnorm_buffer_update_when_stats_are_not_tracked, test/test_nn.py::TestNN::test_batchnorm_cudnn_half, test/test_nn.py::TestNN::test_batchnorm_cudnn_nhwc, test/test_nn.py::TestNN::test_batchnorm_half_overflow, test/test_nn.py::TestNN::test_batchnorm_load_state_dict, test/test_nn.py::TestNN::test_batchnorm_nhwc_cpu, test/test_nn.py::TestNN::test_batchnorm_nhwc_cuda, test/test_nn.py::TestNN::test_batchnorm_non_contig_cpu_BatchNorm2d, test/test_nn.py::TestNN::test_batchnorm_non_contig_cpu_SyncBatchNorm, test/test_nn.py::TestNN::test_batchnorm_nonaffine_cuda_half_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_bias_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_less_than_one_value_per_channel, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_mean_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_var_is_not_same_size_as_input, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_running_var_or_running_mean_have_forward_grad, test/test_nn.py::TestNN::test_batchnorm_raises_error_if_weight_is_not_same_size_as_input, test/test_nn.py::TestNN::test_bce_loss_always_nonnegative, test/test_nn.py::TestNN::test_bce_loss_broadcasts_weights, test/test_nn.py::TestNN::test_bce_loss_input_range, test/test_nn.py::TestNN::test_bce_loss_size_mismatch, test/test_nn.py::TestNN::test_bce_with_logits_broadcasts_pos_weights, test/test_nn.py::TestNN::test_bce_with_logits_broadcasts_weights, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss, test/test_nn.py::TestNN::test_bce_with_logits_gives_same_result_as_sigmoid_and_bce_loss_large_tensors_with_grad, test/test_nn.py::TestNN::test_bce_with_logits_has_correct_forward_grad, test/test_nn.py::TestNN::test_bce_with_logits_has_correct_grad_at_zero, test/test_nn.py::TestNN::test_bce_with_logits_ones_in_pos_weights_are_the_same_as_none, test/test_nn.py::TestNN::test_bce_with_logits_raises_if_target_and_input_are_different_size, test/test_nn.py::TestNN::test_bce_with_logits_stability, test/test_nn.py::TestNN::test_bce_with_logits_with_pos_weight_has_correct_grad_at_zero, test/test_nn.py::TestNN::test_bilinear, test/test_nn.py::TestNN::test_bilinear_broadcasting, test/test_nn.py::TestNN::test_bilinear_no_bias, test/test_nn.py::TestNN::test_bilinear_non_contiguous, test/test_nn.py::TestNN::test_bilinear_value_error, test/test_nn.py::TestNN::test_broadcast_double_backwards_gpu, test/test_nn.py::TestNN::test_broadcast_no_grad, test/test_nn.py::TestNN::test_broadcast_not_requiring_grad, test/test_nn.py::TestNN::test_buffer_bad_module_subclass, test/test_nn.py::TestNN::test_buffer_not_persistent, test/test_nn.py::TestNN::test_buffer_not_persistent_assign, test/test_nn.py::TestNN::test_buffer_not_persistent_del, test/test_nn.py::TestNN::test_buffer_not_persistent_load, test/test_nn.py::TestNN::test_buffer_not_persistent_overwrite, test/test_nn.py::TestNN::test_buffers_and_named_buffers, test/test_nn.py::TestNN::test_call_supports_python_dict_output, test/test_nn.py::TestNN::test_channel_shuffle_input_checks, test/test_nn.py::TestNN::test_channel_shuffle_return_alias_of_self, test/test_nn.py::TestNN::test_children, test/test_nn.py::TestNN::test_container_copy, test/test_nn.py::TestNN::test_convert_sync_batchnorm, test/test_nn.py::TestNN::test_cosine_embedding_loss_error_on_diff_shapes, test/test_nn.py::TestNN::test_cosine_embedding_loss_error_on_nonexpandable_shapes, test/test_nn.py::TestNN::test_cosine_embedding_loss_invalid_shape, test/test_nn.py::TestNN::test_cosine_embedding_loss_margin_no_reduce, test/test_nn.py::TestNN::test_cosine_embedding_loss_no_reduce, test/test_nn.py::TestNN::test_cosine_embedding_loss_with_diff_type, test/test_nn.py::TestNN::test_cosine_similarity, test/test_nn.py::TestNN::test_cross_entropy_loss, test/test_nn.py::TestNN::test_cross_entropy_loss_precision, test/test_nn.py::TestNN::test_cross_entropy_loss_zero_div, test/test_nn.py::TestNN::test_cudnn_forward_exception, test/test_nn.py::TestNN::test_cudnn_rnn_dropout_states_device, test/test_nn.py::TestNN::test_cudnn_weight_format, test/test_nn.py::TestNN::test_cudnn_weight_tying, test/test_nn.py::TestNN::test_dir, test/test_nn.py::TestNN::test_dir_digit, test/test_nn.py::TestNN::test_elu_inplace_gradgrad, test/test_nn.py::TestNN::test_elu_inplace_on_view, test/test_nn.py::TestNN::test_error_RNN_seq_len_zero, test/test_nn.py::TestNN::test_extra_state, test/test_nn.py::TestNN::test_extra_state_missing_get_extra_state, test/test_nn.py::TestNN::test_extra_state_missing_set_extra_state, test/test_nn.py::TestNN::test_extra_state_non_dict, test/test_nn.py::TestNN::test_fb_fc_packed, test/test_nn.py::TestNN::test_flatten, test/test_nn.py::TestNN::test_fold_invalid_arg, test/test_nn.py::TestNN::test_fractional_max_pool2d_invalid_output_ratio, test/test_nn.py::TestNN::test_gaussian_nll_loss_args, test/test_nn.py::TestNN::test_gaussian_nll_loss_broadcasting, test/test_nn.py::TestNN::test_gaussian_nll_loss_scalar_var, test/test_nn.py::TestNN::test_get_buffer, test/test_nn.py::TestNN::test_get_buffer_from_submodules, test/test_nn.py::TestNN::test_getattr_with_property, test/test_nn.py::TestNN::test_grid_sample, test/test_nn.py::TestNN::test_grid_sample_3d, test/test_nn.py::TestNN::test_grid_sample_error_checking, test/test_nn.py::TestNN::test_grid_sample_nearest_neighbor_rounding_mode_consistency, test/test_nn.py::TestNN::test_hardtanh_backward, test/test_nn.py::TestNN::test_hardtanh_inplace_gradgrad, test/test_nn.py::TestNN::test_huber_loss_invalid_delta, test/test_nn.py::TestNN::test_inplace_thnn, test/test_nn.py::TestNN::test_interpolate, test/test_nn.py::TestNN::test_interpolate_bicubic_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bicubic_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_shared_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bicubic_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_bilinear_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_shared_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_shared_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_scale_tuple_skewed_2d_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_align_corners, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_bilinear_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_buffer_overflow, test/test_nn.py::TestNN::test_interpolate_illegal_memory_access, test/test_nn.py::TestNN::test_interpolate_linear_1d, test/test_nn.py::TestNN::test_interpolate_linear_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_1d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_cuda, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_linear_1d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_linear_scale_1d_cuda, test/test_nn.py::TestNN::test_interpolate_linear_tuple_1d, test/test_nn.py::TestNN::test_interpolate_linear_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d, test/test_nn.py::TestNN::test_interpolate_nearest_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_1d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_1d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d, test/test_nn.py::TestNN::test_interpolate_nearest_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs, test/test_nn.py::TestNN::test_interpolate_nearest_2d_launch_configs_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_2d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_2d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_3d, test/test_nn.py::TestNN::test_interpolate_nearest_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim, test/test_nn.py::TestNN::test_interpolate_nearest_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_1d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d, test/test_nn.py::TestNN::test_interpolate_nearest_scale_3d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_1d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_2d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_2d_cuda, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_3d, test/test_nn.py::TestNN::test_interpolate_nearest_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_zero_dim, test/test_nn.py::TestNN::test_interpolate_trilinear_3d_zero_dim_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_scale_3d_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_align_corners_cuda, test/test_nn.py::TestNN::test_interpolate_trilinear_tuple_3d_cuda, test/test_nn.py::TestNN::test_interpolate_undefined_behavior_casting, test/test_nn.py::TestNN::test_kl_div_log_softmax_target, test/test_nn.py::TestNN::test_kl_div_with_diff_type, test/test_nn.py::TestNN::test_kl_div_with_diff_type_log_target, test/test_nn.py::TestNN::test_l1_loss_correct, test/test_nn.py::TestNN::test_layer_norm_backwards_eps, test/test_nn.py::TestNN::test_layer_norm_eps, test/test_nn.py::TestNN::test_layer_norm_grads_with_create_graph_flag, test/test_nn.py::TestNN::test_layer_norm_large_tensor, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCOO, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCSC, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightCSR, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_bias_weightStrided, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCOO, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCSC, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightCSR, test/test_nn.py::TestNN::test_linear_autograd_device_cpu_nobias_weightStrided, test/test_nn.py::TestNN::test_linear_broadcasting, test/test_nn.py::TestNN::test_linear_raise_on_scalar_input, test/test_nn.py::TestNN::test_log_softmax_dim0, test/test_nn.py::TestNN::test_log_softmax_dim0_cuda, test/test_nn.py::TestNN::test_log_softmax_dim3, test/test_nn.py::TestNN::test_log_softmax_dim3_cuda, test/test_nn.py::TestNN::test_log_softmax_lastdim, test/test_nn.py::TestNN::test_log_softmax_lastdim_cuda, test/test_nn.py::TestNN::test_log_softmax_scalar, test/test_nn.py::TestNN::test_log_softmax_scalar_cuda, test/test_nn.py::TestNN::test_log_softmax_spatial, test/test_nn.py::TestNN::test_log_softmax_spatial_cuda, test/test_nn.py::TestNN::test_log_softmax_spatial_special, test/test_nn.py::TestNN::test_log_softmax_spatial_special_cuda, test/test_nn.py::TestNN::test_loss_equal_input_target_shape, test/test_nn.py::TestNN::test_margin_ranking_loss_margin_no_reduce, test/test_nn.py::TestNN::test_margin_ranking_loss_no_reduce, test/test_nn.py::TestNN::test_max_pool1d_invalid_output_size, test/test_nn.py::TestNN::test_module_apply_inplace_op, test/test_nn.py::TestNN::test_module_backcompat, test/test_nn.py::TestNN::test_module_super_init, test/test_nn.py::TestNN::test_module_to_argparse, test/test_nn.py::TestNN::test_modules, test/test_nn.py::TestNN::test_mse_loss_size_warning, test/test_nn.py::TestNN::test_multimarginloss_1d_input_0d_target_no_reduce, test/test_nn.py::TestNN::test_multimarginloss_1d_input_0d_target_no_reduce_cuda, test/test_nn.py::TestNN::test_named_children, test/test_nn.py::TestNN::test_named_modules, test/test_nn.py::TestNN::test_named_parameters_remove_duplicate, test/test_nn.py::TestNN::test_native_channel_shuffle_return_alias_of_self, test/test_nn.py::TestNN::test_nested_tensor_from_mask, test/test_nn.py::TestNN::test_nested_tensor_from_mask_error, test/test_nn.py::TestNN::test_no_grad, test/test_nn.py::TestNN::test_non_leaf_parameters, test/test_nn.py::TestNN::test_normalize, test/test_nn.py::TestNN::test_overwrite_module_params_on_conversion, test/test_nn.py::TestNN::test_pack_sequence_batch_sizes_throw, test/test_nn.py::TestNN::test_pad_scalar_error, test/test_nn.py::TestNN::test_padding_list, test/test_nn.py::TestNN::test_pairwise_distance, test/test_nn.py::TestNN::test_parameter_assignment, test/test_nn.py::TestNN::test_parameterlistdict_pickle, test/test_nn.py::TestNN::test_parameterlistdict_setting_attributes, test/test_nn.py::TestNN::test_parameters_and_named_parameters, test/test_nn.py::TestNN::test_parameters_to_vector, test/test_nn.py::TestNN::test_parse_to, test/test_nn.py::TestNN::test_partial_flat_weights, test/test_nn.py::TestNN::test_pdist, test/test_nn.py::TestNN::test_pdist_cpu_gradgrad_unimplemented, test/test_nn.py::TestNN::test_pdist_cuda_gradgrad_unimplemented, test/test_nn.py::TestNN::test_pdist_empty_col, test/test_nn.py::TestNN::test_pdist_empty_row, test/test_nn.py::TestNN::test_pdist_large, test/test_nn.py::TestNN::test_pdist_zeros, test/test_nn.py::TestNN::test_pickle_module_no_weights_only_warning, test/test_nn.py::TestNN::test_pixel_shuffle_nhwc_cpu, test/test_nn.py::TestNN::test_pixel_shuffle_unshuffle, test/test_nn.py::TestNN::test_pointwise_loss_broadcast, test/test_nn.py::TestNN::test_pointwise_loss_target_grad_none_reduction, test/test_nn.py::TestNN::test_projections_errors_on_gru_and_rnn, test/test_nn.py::TestNN::test_projections_lstm_args_check, test/test_nn.py::TestNN::test_projections_lstm_check_device, test/test_nn.py::TestNN::test_projections_lstm_initial_hidden_state, test/test_nn.py::TestNN::test_register_buffer_allows_overwriting_with_same_name, test/test_nn.py::TestNN::test_register_buffer_allows_tensor_like_object, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_name_is_not_string, test/test_nn.py::TestNN::test_register_buffer_raises_error_if_not_tensor, test/test_nn.py::TestNN::test_register_parameter_allows_overwriting_with_same_name, test/test_nn.py::TestNN::test_register_parameter_raises_error_if_attr_exists, test/test_nn.py::TestNN::test_register_parameter_raises_error_if_name_is_not_string, test/test_nn.py::TestNN::test_relu_inplace_on_view, test/test_nn.py::TestNN::test_repr, test/test_nn.py::TestNN::test_requires_grad_, test/test_nn.py::TestNN::test_rnn_args_check, test/test_nn.py::TestNN::test_rnn_check_device, test/test_nn.py::TestNN::test_rnn_initial_hidden_state, test/test_nn.py::TestNN::test_rnn_weight_norm, test/test_nn.py::TestNN::test_set_submodule, test/test_nn.py::TestNN::test_share_memory, test/test_nn.py::TestNN::test_smoothl1loss_intergral_target, test/test_nn.py::TestNN::test_smoothl1loss_negative_beta_not_supported, test/test_nn.py::TestNN::test_softmax_functional_dim0, test/test_nn.py::TestNN::test_softmax_functional_dim0_cuda, test/test_nn.py::TestNN::test_softmax_functional_dim3, test/test_nn.py::TestNN::test_softmax_functional_dim3_cuda, test/test_nn.py::TestNN::test_softmax_functional_scalar, test/test_nn.py::TestNN::test_softmax_functional_scalar_cuda, test/test_nn.py::TestNN::test_softmax_lastdim, test/test_nn.py::TestNN::test_softmax_lastdim_cuda, test/test_nn.py::TestNN::test_softmax_lastdim_dtype, test/test_nn.py::TestNN::test_softmax_lastdim_dtype_cuda, test/test_nn.py::TestNN::test_softmax_spatial, test/test_nn.py::TestNN::test_softmax_spatial_cuda, test/test_nn.py::TestNN::test_softmax_spatial_dtype, test/test_nn.py::TestNN::test_softmax_spatial_dtype_cuda, test/test_nn.py::TestNN::test_softmax_spatial_special, test/test_nn.py::TestNN::test_softmax_spatial_special_cuda, test/test_nn.py::TestNN::test_softmin, test/test_nn.py::TestNN::test_spectral_norm, test/test_nn.py::TestNN::test_spectral_norm_dim, test/test_nn.py::TestNN::test_spectral_norm_forward, test/test_nn.py::TestNN::test_spectral_norm_load_state_dict, test/test_nn.py::TestNN::test_spectral_norm_pickle, test/test_nn.py::TestNN::test_state_dict, test/test_nn.py::TestNN::test_swap_module_params_poisons_acc_grad, test/test_nn.py::TestNN::test_sync_batchnorm_accuracy_cuda, test/test_nn.py::TestNN::test_sync_batchnorm_backward_elemt, test/test_nn.py::TestNN::test_threshold_bfloat16_half, test/test_nn.py::TestNN::test_threshold_int, test/test_nn.py::TestNN::test_to, test/test_nn.py::TestNN::test_train_errors_for_invalid_mode, test/test_nn.py::TestNN::test_transformer_args_check, test/test_nn.py::TestNN::test_transformer_layer_args_check, test/test_nn.py::TestNN::test_transformerdecoder, test/test_nn.py::TestNN::test_transformerdecoderlayer, test/test_nn.py::TestNN::test_transformerdecoderlayer_gelu, test/test_nn.py::TestNN::test_triplet_margin_loss, test/test_nn.py::TestNN::test_triplet_margin_loss_no_reduce, test/test_nn.py::TestNN::test_triplet_margin_loss_swap, test/test_nn.py::TestNN::test_triplet_margin_loss_swap_no_reduce, test/test_nn.py::TestNN::test_type, test/test_nn.py::TestNN::test_unflatten, test/test_nn.py::TestNN::test_unflatten_invalid_arg, test/test_nn.py::TestNN::test_unfold_invalid_arg, test/test_nn.py::TestNN::test_upsamplingBilinear2d_spatial_invariance, test/test_nn.py::TestNN::test_upsamplingLinear1d, test/test_nn.py::TestNN::test_upsamplingLinear1d_spatial_invariance, test/test_nn.py::TestNN::test_upsamplingTrilinear3d_spatial_invariance, test/test_nn.py::TestNN::test_upsampling_bfloat16, test/test_nn.py::TestNN::test_upsampling_not_recompute_scale_factor, test/test_nn.py::TestNN::test_upsampling_small_scale, test/test_nn.py::TestNN::test_vector_to_parameters, test/test_nn.py::TestNN::test_weight_norm, test/test_nn.py::TestNN::test_weight_norm_pickle, test/test_nn.py::TestNN::test_weighted_huber_loss, test/test_nn.py::TestNN::test_weighted_l1_loss_with_weights, test/test_nn.py::TestNN::test_weighted_mse_loss, test/test_nn.py::TestNN::test_zero_grad, test/test_nn.py::TestFusionEval::test_fuse_module_eval_numerics, test/test_nn.py::TestConstantPadNd::test_constant_pad_nd, test/test_nn.py::TestConstantPadNd::test_preserves_memory_format, test/test_nn.py::TestAddRelu::test_add_relu, test/test_nn.py::TestAddRelu::test_add_relu_broadcasting, test/test_nn.py::TestFunctionalPickle::test_pickle_softsign, test/test_nn.py::TestFusionUtils::test_fuse_conv_bn_requires_grad, test/test_nn.py::TestFusionUtils::test_fuse_linear_bn_requires_grad, test/test_nn.py::TestUtils::test_consume_prefix_in_state_dict_if_present, test/test_nn.py::TestNNDeviceTypeCPU::test_BatchNorm_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_Bilinear_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_cudnn_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_empty_target_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_mean_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_none_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_CTCLoss_no_batch_dim_reduction_sum_use_module_form_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GRU_grad_and_gradgrad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_memory_format_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_numeric_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_GroupNorm_raises_error_if_one_value_per_group_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm1d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm2d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_InstanceNorm3d_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_differentiable_backward_using_oneDNN_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_differentiable_backward_using_oneDNN_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_LSTM_grad_and_gradgrad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_LayerNorm_general_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LayerNorm_numeric_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_LocalResponseNorm_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_race_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_race_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_MarginLoss_warnings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad2d_large_deterministic_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad3d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_empty_cpu_complex64, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_ReflectionPad_fails_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad1d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad2d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad3d_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad_empty_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_ReplicationPad_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerDecoderLayer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerDecoder_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerEncoderLayer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_TransformerEncoder_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_Transformer_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_Unfold_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_activations_bfloat16_half_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_adaptiveavg_pool1d_shmem_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate45_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotate90_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_2d_rotateRandom_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_affine_3d_rotateRandom_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_avg_pool_large_tensor_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_affine_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_eval_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_large_batch_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_large_batch_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_mixed_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_simple_average_mixed_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_batchnorm_update_stats_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_channel_shuffle_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_error_if_nonfinite_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_1_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_4_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_False_norm_type_inf_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_0_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_1_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_2_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_4_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_foreach_True_norm_type_inf_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_multi_device_foreach_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_norm_multi_device_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_clip_grad_value_foreach_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_conv_empty_input_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_64bit_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_consistent_index_target_and_probs_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_errors_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_weight_ignore_indices_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_label_smoothing_with_probs_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_large_tensor_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_2d_out_of_bounds_class_index_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_2d_out_of_bounds_class_index_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_index_target_unit_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_one_hot_target_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_all_reductions_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_mean_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_none_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_no_batch_dim_reduction_sum_weighted_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_cross_entropy_loss_prob_target_unit_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_tensor_cpu_length_cuda_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_cudnn_tensor_cuda_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_ctc_loss_error_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_device_mask_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_elu_inplace_with_neg_alpha_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_fold_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_glu_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_bfloat16_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_half_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_2d_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_2d_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_3d_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_large_index_3d_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_nan_inf_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_grid_sample_nan_inf_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_groupnorm_nhwc_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_gumbel_softmax_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_hardsigmoid_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_corner_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_hardswish_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_for_single_spatial_element_during_training_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm1d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm2d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_False_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_False_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_input_channels_is_not_num_features_InstanceNorm3d_no_batch_dim_True_affine_True_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_instancenorm_raises_error_if_less_than_one_value_per_channel_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_invalid_reduction_strings_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_layernorm_half_precision_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_layernorm_weight_bias_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_neg_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_leaky_relu_inplace_with_zero_slope_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_linear_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_big_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_log_softmax_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_logsigmoid_out_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_lstmcell_backward_only_one_output_grad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_TxT_layout_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_devices_parity_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_forward_with_nans_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_grad_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_lowp_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_lowp_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_mask_types_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_masked_softmax_transformer_layout_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_mish_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_module_to_empty_non_recursive_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_mse_loss_error_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_all_ignored_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_byte_target_matches_long_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_mean_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_none_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_empty_tensor_reduction_sum_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_invalid_target_dim_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_invalid_weights_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_mean_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_none_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_large_tensor_reduction_sum_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_mismatched_batch_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_out_of_bounds_ignore_index_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nll_loss_total_weight_is_zero_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_empty_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_scalars_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nn_scalars_reductions_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_nonlinearity_propagate_nan_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_one_hot_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_overwrite_module_params_on_conversion_cpu_device_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_pad_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_pad_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_prelu_backward_32bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_replicatepad_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_epsilon_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_numeric_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_rmsnorm_numeric_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_fused_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_fused_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_rnn_retain_variables_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_save_lstm_compatibility_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_silu_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_skip_init_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smooth_l1_loss_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smooth_l1_loss_vs_huber_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_smoothl1loss_backward_zero_beta_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_64bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_smem_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_unaligned_grad_output_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_unaligned_output_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_backward_without_fully_vectorized_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_bfloat16_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_double_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_forward_64bit_indexing_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softmax_results_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_softplus_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softplus_low_threshold_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_softshrink_negative_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_threshold_inplace_overlap_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex128, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_complex64, test/test_nn.py::TestNNDeviceTypeCPU::test_to_complex_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_fast_path_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_transformerencoderlayer_gelu_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_triplet_margin_with_distance_loss_default_parity_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_False_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format0_align_corners_True_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_False_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_399_output_size_437_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiLinear2d_consistency_interp_size_bug_memory_format1_align_corners_True_input_size_403_output_size_377_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_False_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_False_align_corners_True_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_False_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bicubic_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_antialias_True_align_corners_True_mode_bilinear_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format0_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bicubic_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_False_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_False_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_3_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_32_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_False_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_False_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_restrided_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_consistency_memory_format1_mode_bilinear_antialias_True_align_corners_True_num_channels_5_output_size_600_check_as_unsqueezed_3d_tensor_True_non_contig_sliced_batch_size_5_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_False_num_channels_5_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_3_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bicubic_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_bilinear_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest-exact_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float32_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_float64_cpu_float64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int16_cpu_int16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int32_cpu_int32, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int64_cpu_int64, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_int8_cpu_int8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBiMode2d_nonsupported_dtypes_antialias_True_num_channels_5_mode_nearest_uint8_cpu_uint8, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_aa_correctness_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_aa_correctness_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBicubic2d_correctness_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBilinear2d_aa_correctness_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingBilinear2d_aa_correctness_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_correctness_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_correctness_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest1d_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_fail_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_launch_rocm_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format0_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format0_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format1_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest2d_memory_format1_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_launch_config_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format0_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format0_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format1_mode_nearest-exact_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearest3d_memory_format1_mode_nearest_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_correctness_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact1d_rescale_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact2d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format0_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_10_osize_15_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingNearestExact3d_correctness_memory_format1_isize_20_osize_11_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_False_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_False_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_True_memory_format0_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingTrilinear3d_align_corners_True_memory_format1_cpu, test/test_nn.py::TestNNDeviceTypeCPU::test_upsampling_64bit_indexing_channels_last_cpu_bfloat16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsampling_64bit_indexing_channels_last_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_upsamplingnearest2d_backward_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_variable_sequence_cpu_float32, test/test_nn.py::TestNNDeviceTypeCPU::test_warp_softmax_64bit_indexing_cpu_float16, test/test_nn.py::TestNNDeviceTypeCPU::test_warp_softmax_64bit_indexing_cpu_float32 2025-08-26T19:55:50.5810539Z 2025-08-26T19:55:50.5810846Z Running test_cpp_extensions_stream_and_event 1/1 ... [2025-08-26 19:55:50.342356] 2025-08-26T19:55:50.5811384Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:55:50.5812553Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_stream_and_event.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:55:50.342665] 2025-08-26T19:55:54.1119014Z 2025-08-26T19:55:54.1120074Z test_cpp_extensions_stream_and_event 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_stream_and_event_1.1_be2f746d4d6a4c0e_.log 2025-08-26T19:55:54.1121422Z Running 1 items in this shard: test/test_cpp_extensions_stream_and_event.py::TestCppExtensionStreamAndEvent::test_stream_event 2025-08-26T19:55:54.1122053Z 2025-08-26T19:55:54.1122516Z Running doctests 1/1 ... [2025-08-26 19:55:54.112105] 2025-08-26T19:55:54.2093664Z Start doctest_module('/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch') 2025-08-26T19:55:54.2094214Z Listing tests 2025-08-26T19:55:54.4361853Z msg = Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py line=1493. 2025-08-26T19:55:54.4362780Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.4363184Z 2025-08-26T19:55:54.4363321Z dim_order(ambiguity_check=False) -> tuple 2025-08-26T19:55:54.4363564Z 2025-08-26T19:55:54.4363819Z Returns the uniquely determined tuple of int describing the dim order or 2025-08-26T19:55:54.4364325Z physical layout of :attr:`self`. 2025-08-26T19:55:54.4364529Z 2025-08-26T19:55:54.4364791Z The dim order represents how dimensions are laid out in memory of dense tensors, 2025-08-26T19:55:54.4365357Z starting from the outermost to the innermost dimension. 2025-08-26T19:55:54.4365655Z 2025-08-26T19:55:54.4365846Z Note that the dim order may not always be uniquely determined. 2025-08-26T19:55:54.4366558Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined; 2025-08-26T19:55:54.4367487Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted 2025-08-26T19:55:54.4368282Z into exactly one of the given memory formats, or it cannot be uniquely determined. 2025-08-26T19:55:54.4369058Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness. 2025-08-26T19:55:54.4369637Z Otherwise, it will raise TypeError. 2025-08-26T19:55:54.4369857Z 2025-08-26T19:55:54.4369957Z Args: 2025-08-26T19:55:54.4370402Z ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order. 2025-08-26T19:55:54.4370862Z 2025-08-26T19:55:54.4370979Z Examples:: 2025-08-26T19:55:54.4371118Z 2025-08-26T19:55:54.4371235Z >>> torch.empty((2, 3, 5, 7)).dim_order() 2025-08-26T19:55:54.4371553Z (0, 1, 2, 3) 2025-08-26T19:55:54.4371864Z >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order() 2025-08-26T19:55:54.4372463Z (0, 2, 1, 3) 2025-08-26T19:55:54.4372823Z >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order() 2025-08-26T19:55:54.4373248Z (0, 2, 3, 1) 2025-08-26T19:55:54.4373507Z >>> torch.empty((1, 2, 3, 4)).dim_order() 2025-08-26T19:55:54.4373813Z (0, 1, 2, 3) 2025-08-26T19:55:54.4374046Z >>> try: 2025-08-26T19:55:54.4374363Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True) 2025-08-26T19:55:54.4374796Z ... except RuntimeError as e: 2025-08-26T19:55:54.4375184Z ... print(e) 2025-08-26T19:55:54.4375669Z The tensor does not have unique dim order, or cannot map to exact one of the given memory formats. 2025-08-26T19:55:54.4376239Z >>> torch.empty((1, 2, 3, 4)).dim_order( 2025-08-26T19:55:54.4376687Z ... ambiguity_check=[torch.contiguous_format, torch.channels_last] 2025-08-26T19:55:54.4377160Z ... ) # It can be mapped to contiguous format 2025-08-26T19:55:54.4377491Z (0, 1, 2, 3) 2025-08-26T19:55:54.4377722Z >>> try: 2025-08-26T19:55:54.4378044Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL") 2025-08-26T19:55:54.4378465Z ... except TypeError as e: 2025-08-26T19:55:54.4378741Z ... print(e) 2025-08-26T19:55:54.4379138Z The ambiguity_check argument must be a bool or a list of memory formats. 2025-08-26T19:55:54.4379509Z 2025-08-26T19:55:54.4379604Z .. warning:: 2025-08-26T19:55:54.4379942Z The dim_order tensor API is experimental and subject to change. 2025-08-26T19:55:54.4380263Z 2025-08-26T19:55:54.4380520Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.4380912Z 2025-08-26T19:55:54.5002838Z msg = Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=397. 2025-08-26T19:55:54.5003761Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5004430Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors. 2025-08-26T19:55:54.5004797Z 2025-08-26T19:55:54.5004994Z This is helpful when you want to visualize data over some 2025-08-26T19:55:54.5005441Z range of inputs. See below for a plotting example. 2025-08-26T19:55:54.5005724Z 2025-08-26T19:55:54.5005897Z Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as 2025-08-26T19:55:54.5006383Z inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`, 2025-08-26T19:55:54.5006903Z this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots 2025-08-26T19:55:54.5007373Z G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where 2025-08-26T19:55:54.5007850Z the output :math:`G_i` is constructed by expanding :math:`T_i` 2025-08-26T19:55:54.5008279Z to the result shape. 2025-08-26T19:55:54.5008464Z 2025-08-26T19:55:54.5008600Z .. note:: 2025-08-26T19:55:54.5008973Z 0D inputs are treated equivalently to 1D inputs of a 2025-08-26T19:55:54.5009368Z single element. 2025-08-26T19:55:54.5009546Z 2025-08-26T19:55:54.5009653Z .. warning:: 2025-08-26T19:55:54.5010000Z `torch.meshgrid(*tensors)` currently has the same behavior 2025-08-26T19:55:54.5010479Z as calling `numpy.meshgrid(*arrays, indexing='ij')`. 2025-08-26T19:55:54.5010762Z 2025-08-26T19:55:54.5010932Z In the future `torch.meshgrid` will transition to 2025-08-26T19:55:54.5011310Z `indexing='xy'` as the default. 2025-08-26T19:55:54.5011544Z 2025-08-26T19:55:54.5011761Z https://github.com/pytorch/pytorch/issues/50276 tracks 2025-08-26T19:55:54.5012239Z this issue with the goal of migrating to NumPy's behavior. 2025-08-26T19:55:54.5012554Z 2025-08-26T19:55:54.5012646Z .. seealso:: 2025-08-26T19:55:54.5012811Z 2025-08-26T19:55:54.5012986Z :func:`torch.cartesian_prod` has the same effect but it 2025-08-26T19:55:54.5013417Z collects the data in a tensor of vectors. 2025-08-26T19:55:54.5013967Z 2025-08-26T19:55:54.5014054Z Args: 2025-08-26T19:55:54.5014469Z tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be 2025-08-26T19:55:54.5015039Z treated as tensors of size :math:`(1,)` automatically 2025-08-26T19:55:54.5015323Z 2025-08-26T19:55:54.5015519Z indexing: (str, optional): the indexing mode, either "xy" 2025-08-26T19:55:54.5015993Z or "ij", defaults to "ij". See warning for future changes. 2025-08-26T19:55:54.5016389Z 2025-08-26T19:55:54.5016553Z If "xy" is selected, the first dimension corresponds 2025-08-26T19:55:54.5017005Z to the cardinality of the second input and the second 2025-08-26T19:55:54.5017473Z dimension corresponds to the cardinality of the first 2025-08-26T19:55:54.5017863Z input. 2025-08-26T19:55:54.5018020Z 2025-08-26T19:55:54.5018175Z If "ij" is selected, the dimensions are in the same 2025-08-26T19:55:54.5018589Z order as the cardinality of the inputs. 2025-08-26T19:55:54.5018854Z 2025-08-26T19:55:54.5018943Z Returns: 2025-08-26T19:55:54.5019261Z seq (sequence of Tensors): If the input has :math:`N` 2025-08-26T19:55:54.5019740Z tensors of size :math:`S_0 \ldots S_{N-1}``, then the 2025-08-26T19:55:54.5020214Z output will also have :math:`N` tensors, where each tensor 2025-08-26T19:55:54.5020640Z is of shape :math:`(S_0, ..., S_{N-1})`. 2025-08-26T19:55:54.5020894Z 2025-08-26T19:55:54.5020995Z Example:: 2025-08-26T19:55:54.5021139Z 2025-08-26T19:55:54.5021270Z >>> x = torch.tensor([1, 2, 3]) 2025-08-26T19:55:54.5021622Z >>> y = torch.tensor([4, 5, 6]) 2025-08-26T19:55:54.5021841Z 2025-08-26T19:55:54.5022037Z Observe the element-wise pairings across the grid, (1, 4), 2025-08-26T19:55:54.5022494Z (1, 5), ..., (3, 6). This is the same thing as the 2025-08-26T19:55:54.5022865Z cartesian product. 2025-08-26T19:55:54.5023228Z >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij') 2025-08-26T19:55:54.5023597Z >>> grid_x 2025-08-26T19:55:54.5023860Z tensor([[1, 1, 1], 2025-08-26T19:55:54.5024140Z [2, 2, 2], 2025-08-26T19:55:54.5024424Z [3, 3, 3]]) 2025-08-26T19:55:54.5024688Z >>> grid_y 2025-08-26T19:55:54.5024945Z tensor([[4, 5, 6], 2025-08-26T19:55:54.5025229Z [4, 5, 6], 2025-08-26T19:55:54.5025505Z [4, 5, 6]]) 2025-08-26T19:55:54.5025685Z 2025-08-26T19:55:54.5025868Z This correspondence can be seen when these grids are 2025-08-26T19:55:54.5026253Z stacked properly. 2025-08-26T19:55:54.5026653Z >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))), 2025-08-26T19:55:54.5027120Z ... torch.cartesian_prod(x, y)) 2025-08-26T19:55:54.5027466Z True 2025-08-26T19:55:54.5027606Z 2025-08-26T19:55:54.5027783Z `torch.meshgrid` is commonly used to produce a grid for 2025-08-26T19:55:54.5028182Z plotting. 2025-08-26T19:55:54.5028484Z >>> # xdoctest: +REQUIRES(module:matplotlib) 2025-08-26T19:55:54.5028872Z >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW) 2025-08-26T19:55:54.5029237Z >>> import matplotlib.pyplot as plt 2025-08-26T19:55:54.5029616Z >>> xs = torch.linspace(-5, 5, steps=100) 2025-08-26T19:55:54.5029991Z >>> ys = torch.linspace(-5, 5, steps=100) 2025-08-26T19:55:54.5030373Z >>> x, y = torch.meshgrid(xs, ys, indexing='xy') 2025-08-26T19:55:54.5030751Z >>> z = torch.sin(torch.sqrt(x * x + y * y)) 2025-08-26T19:55:54.5031121Z >>> ax = plt.axes(projection='3d') 2025-08-26T19:55:54.5031513Z >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy()) 2025-08-26T19:55:54.5031884Z >>> plt.show() 2025-08-26T19:55:54.5032138Z 2025-08-26T19:55:54.5032277Z .. image:: ../_static/img/meshgrid.png 2025-08-26T19:55:54.5032594Z :width: 512 2025-08-26T19:55:54.5032763Z 2025-08-26T19:55:54.5032849Z 2025-08-26T19:55:54.5033232Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5033608Z 2025-08-26T19:55:54.5034167Z msg = Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=793. 2025-08-26T19:55:54.5035128Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5035921Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor] 2025-08-26T19:55:54.5036431Z 2025-08-26T19:55:54.5036602Z Returns the unique elements of the input tensor. 2025-08-26T19:55:54.5036871Z 2025-08-26T19:55:54.5037186Z .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that 2025-08-26T19:55:54.5037981Z this function also eliminates non-consecutive duplicate values. 2025-08-26T19:55:54.5038329Z 2025-08-26T19:55:54.5038567Z .. note:: Currently in the CUDA implementation and the CPU implementation, 2025-08-26T19:55:54.5039223Z `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument. 2025-08-26T19:55:54.5039943Z Sorting could be slow, so if your input tensor is already sorted, it is recommended to use 2025-08-26T19:55:54.5040544Z :func:`torch.unique_consecutive` which avoids the sorting. 2025-08-26T19:55:54.5040843Z 2025-08-26T19:55:54.5040931Z Args: 2025-08-26T19:55:54.5041178Z input (Tensor): the input tensor 2025-08-26T19:55:54.5041627Z sorted (bool): Whether to sort the unique elements in ascending order 2025-08-26T19:55:54.5042092Z before returning as output. 2025-08-26T19:55:54.5042531Z return_inverse (bool): Whether to also return the indices for where 2025-08-26T19:55:54.5043109Z elements in the original input ended up in the returned unique list. 2025-08-26T19:55:54.5043682Z return_counts (bool): Whether to also return the counts for each unique 2025-08-26T19:55:54.5044123Z element. 2025-08-26T19:55:54.5044497Z dim (int, optional): the dimension to operate upon. If ``None``, the 2025-08-26T19:55:54.5045038Z unique of the flattened input is returned. Otherwise, each of the 2025-08-26T19:55:54.5045571Z tensors indexed by the given dimension is treated as one of the 2025-08-26T19:55:54.5046116Z elements to apply the unique operation upon. See examples for more 2025-08-26T19:55:54.5046570Z details. Default: ``None`` 2025-08-26T19:55:54.5046781Z 2025-08-26T19:55:54.5046882Z Returns: 2025-08-26T19:55:54.5047299Z (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing 2025-08-26T19:55:54.5047722Z 2025-08-26T19:55:54.5047926Z - **output** (*Tensor*): the output list of unique scalar elements. 2025-08-26T19:55:54.5048392Z - **inverse_indices** (*Tensor*): (optional) if 2025-08-26T19:55:54.5048914Z :attr:`return_inverse` is True, there will be an additional 2025-08-26T19:55:54.5049441Z returned tensor (same shape as input) representing the indices 2025-08-26T19:55:54.5049968Z for where elements in the original input map to in the output; 2025-08-26T19:55:54.5050497Z otherwise, this function will only return a single tensor. 2025-08-26T19:55:54.5050944Z - **counts** (*Tensor*): (optional) if 2025-08-26T19:55:54.5051367Z :attr:`return_counts` is True, there will be an additional 2025-08-26T19:55:54.5051862Z returned tensor (same shape as output or output.size(dim), 2025-08-26T19:55:54.5052361Z if dim was specified) representing the number of occurrences 2025-08-26T19:55:54.5052933Z for each unique value or tensor. 2025-08-26T19:55:54.5053197Z 2025-08-26T19:55:54.5053295Z Example:: 2025-08-26T19:55:54.5053429Z 2025-08-26T19:55:54.5053661Z >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long)) 2025-08-26T19:55:54.5054102Z >>> output 2025-08-26T19:55:54.5054341Z tensor([1, 2, 3]) 2025-08-26T19:55:54.5054527Z 2025-08-26T19:55:54.5054658Z >>> output, inverse_indices = torch.unique( 2025-08-26T19:55:54.5055235Z ... torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T19:55:54.5055696Z >>> output 2025-08-26T19:55:54.5055934Z tensor([1, 2, 3]) 2025-08-26T19:55:54.5056209Z >>> inverse_indices 2025-08-26T19:55:54.5056491Z tensor([0, 2, 1, 2]) 2025-08-26T19:55:54.5056670Z 2025-08-26T19:55:54.5056814Z >>> output, inverse_indices = torch.unique( 2025-08-26T19:55:54.5057299Z ... torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T19:55:54.5057765Z >>> output 2025-08-26T19:55:54.5058013Z tensor([1, 2, 3]) 2025-08-26T19:55:54.5058285Z >>> inverse_indices 2025-08-26T19:55:54.5058551Z tensor([[0, 2], 2025-08-26T19:55:54.5058806Z [1, 2]]) 2025-08-26T19:55:54.5058982Z 2025-08-26T19:55:54.5059081Z >>> a = torch.tensor([ 2025-08-26T19:55:54.5059363Z ... [ 2025-08-26T19:55:54.5059596Z ... [1, 1, 0, 0], 2025-08-26T19:55:54.5059883Z ... [1, 1, 0, 0], 2025-08-26T19:55:54.5060171Z ... [0, 0, 1, 1], 2025-08-26T19:55:54.5060447Z ... ], 2025-08-26T19:55:54.5060666Z ... [ 2025-08-26T19:55:54.5060900Z ... [0, 0, 1, 1], 2025-08-26T19:55:54.5061179Z ... [0, 0, 1, 1], 2025-08-26T19:55:54.5061461Z ... [1, 1, 1, 1], 2025-08-26T19:55:54.5061723Z ... ], 2025-08-26T19:55:54.5061954Z ... [ 2025-08-26T19:55:54.5062191Z ... [1, 1, 0, 0], 2025-08-26T19:55:54.5062474Z ... [1, 1, 0, 0], 2025-08-26T19:55:54.5062749Z ... [0, 0, 1, 1], 2025-08-26T19:55:54.5063026Z ... ], 2025-08-26T19:55:54.5063258Z ... ]) 2025-08-26T19:55:54.5063389Z 2025-08-26T19:55:54.5063622Z >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]` 2025-08-26T19:55:54.5064167Z >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match 2025-08-26T19:55:54.5064642Z >>> # each other, so one of them will be removed. 2025-08-26T19:55:54.5065010Z >>> (a[0, :, :] == a[2, :, :]).all() 2025-08-26T19:55:54.5065320Z tensor(True) 2025-08-26T19:55:54.5065605Z >>> a_unique_dim0 = torch.unique(a, dim=0) 2025-08-26T19:55:54.5065932Z >>> a_unique_dim0 2025-08-26T19:55:54.5066201Z tensor([[[0, 0, 1, 1], 2025-08-26T19:55:54.5066478Z [0, 0, 1, 1], 2025-08-26T19:55:54.5066749Z [1, 1, 1, 1]], 2025-08-26T19:55:54.5067018Z [[1, 1, 0, 0], 2025-08-26T19:55:54.5067290Z [1, 1, 0, 0], 2025-08-26T19:55:54.5067565Z [0, 0, 1, 1]]]) 2025-08-26T19:55:54.5067748Z 2025-08-26T19:55:54.5067978Z >>> # Notice which sub-tensors from `a` match with the sub-tensors from 2025-08-26T19:55:54.5068411Z >>> # `a_unique_dim0`: 2025-08-26T19:55:54.5068724Z >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all() 2025-08-26T19:55:54.5069062Z tensor(True) 2025-08-26T19:55:54.5069348Z >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all() 2025-08-26T19:55:54.5069668Z tensor(True) 2025-08-26T19:55:54.5069831Z 2025-08-26T19:55:54.5070038Z >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are 2025-08-26T19:55:54.5070561Z >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of 2025-08-26T19:55:54.5070976Z >>> # them will be removed. 2025-08-26T19:55:54.5071361Z >>> (a[:, 0, :] == a[:, 1, :]).all() 2025-08-26T19:55:54.5071675Z tensor(True) 2025-08-26T19:55:54.5071941Z >>> torch.unique(a, dim=1) 2025-08-26T19:55:54.5072248Z tensor([[[0, 0, 1, 1], 2025-08-26T19:55:54.5072515Z [1, 1, 0, 0]], 2025-08-26T19:55:54.5072796Z [[1, 1, 1, 1], 2025-08-26T19:55:54.5073072Z [0, 0, 1, 1]], 2025-08-26T19:55:54.5073346Z [[0, 0, 1, 1], 2025-08-26T19:55:54.5073606Z [1, 1, 0, 0]]]) 2025-08-26T19:55:54.5073802Z 2025-08-26T19:55:54.5074093Z >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared. 2025-08-26T19:55:54.5074603Z >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and 2025-08-26T19:55:54.5075072Z >>> # `a[:, :, 3]` match each other as well. So in this case, two of the 2025-08-26T19:55:54.5075493Z >>> # sub-tensors will be removed. 2025-08-26T19:55:54.5075813Z >>> (a[:, :, 0] == a[:, :, 1]).all() 2025-08-26T19:55:54.5076126Z tensor(True) 2025-08-26T19:55:54.5076386Z >>> (a[:, :, 2] == a[:, :, 3]).all() 2025-08-26T19:55:54.5076693Z tensor(True) 2025-08-26T19:55:54.5076944Z >>> torch.unique(a, dim=2) 2025-08-26T19:55:54.5077249Z tensor([[[0, 1], 2025-08-26T19:55:54.5077507Z [0, 1], 2025-08-26T19:55:54.5077760Z [1, 0]], 2025-08-26T19:55:54.5078009Z [[1, 0], 2025-08-26T19:55:54.5078262Z [1, 0], 2025-08-26T19:55:54.5078518Z [1, 1]], 2025-08-26T19:55:54.5078785Z [[0, 1], 2025-08-26T19:55:54.5079027Z [0, 1], 2025-08-26T19:55:54.5079286Z [1, 0]]]) 2025-08-26T19:55:54.5079546Z 2025-08-26T19:55:54.5079930Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5080304Z 2025-08-26T19:55:54.5197956Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=565. 2025-08-26T19:55:54.5198837Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5199225Z 2025-08-26T19:55:54.5199389Z Load a model from a github repo or a local directory. 2025-08-26T19:55:54.5199670Z 2025-08-26T19:55:54.5199902Z Note: Loading a model is the typical use case, but this can also be used to 2025-08-26T19:55:54.5200476Z for loading other objects such as tokenizers, loss functions, etc. 2025-08-26T19:55:54.5200805Z 2025-08-26T19:55:54.5200998Z If ``source`` is 'github', ``repo_or_dir`` is expected to be 2025-08-26T19:55:54.5201461Z of the form ``repo_owner/repo_name[:ref]`` with an optional 2025-08-26T19:55:54.5201844Z ref (a tag or a branch). 2025-08-26T19:55:54.5202029Z 2025-08-26T19:55:54.5202201Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a 2025-08-26T19:55:54.5202602Z path to a local directory. 2025-08-26T19:55:54.5202783Z 2025-08-26T19:55:54.5202883Z Args: 2025-08-26T19:55:54.5203138Z repo_or_dir (str): If ``source`` is 'github', 2025-08-26T19:55:54.5203689Z this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with 2025-08-26T19:55:54.5204424Z an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified, 2025-08-26T19:55:54.5205127Z the default branch is assumed to be ``main`` if it exists, and otherwise ``master``. 2025-08-26T19:55:54.5205734Z If ``source`` is 'local' then it should be a path to a local directory. 2025-08-26T19:55:54.5206259Z model (str): the name of a callable (entrypoint) defined in the 2025-08-26T19:55:54.5206695Z repo/dir's ``hubconf.py``. 2025-08-26T19:55:54.5207114Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T19:55:54.5207626Z source (str, optional): 'github' or 'local'. Specifies how 2025-08-26T19:55:54.5208091Z ``repo_or_dir`` is to be interpreted. Default is 'github'. 2025-08-26T19:55:54.5208611Z trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``. 2025-08-26T19:55:54.5209428Z This parameter was introduced in v1.12 and helps ensuring that users 2025-08-26T19:55:54.5209924Z only run code from repos that they trust. 2025-08-26T19:55:54.5210171Z 2025-08-26T19:55:54.5210382Z - If ``False``, a prompt will ask the user whether the repo should 2025-08-26T19:55:54.5210786Z be trusted. 2025-08-26T19:55:54.5211139Z - If ``True``, the repo will be added to the trusted list and loaded 2025-08-26T19:55:54.5211674Z without requiring explicit confirmation. 2025-08-26T19:55:54.5212106Z - If ``"check"``, the repo will be checked against the list of 2025-08-26T19:55:54.5212612Z trusted repos in the cache. If it is not present in that list, the 2025-08-26T19:55:54.5213156Z behaviour will fall back onto the ``trust_repo=False`` option. 2025-08-26T19:55:54.5213668Z - If ``None``: this will raise a warning, inviting the user to set 2025-08-26T19:55:54.5214172Z ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This 2025-08-26T19:55:54.5214689Z is only present for backward compatibility and will be removed in 2025-08-26T19:55:54.5215114Z v2.0. 2025-08-26T19:55:54.5215265Z 2025-08-26T19:55:54.5215476Z Default is ``None`` and will eventually change to ``"check"`` in v2.0. 2025-08-26T19:55:54.5216030Z force_reload (bool, optional): whether to force a fresh download of 2025-08-26T19:55:54.5216572Z the github repo unconditionally. Does not have any effect if 2025-08-26T19:55:54.5217001Z ``source = 'local'``. Default is ``False``. 2025-08-26T19:55:54.5217462Z verbose (bool, optional): If ``False``, mute messages about hitting 2025-08-26T19:55:54.5218011Z local caches. Note that the message about first download cannot be 2025-08-26T19:55:54.5218523Z muted. Does not have any effect if ``source = 'local'``. 2025-08-26T19:55:54.5218908Z Default is ``True``. 2025-08-26T19:55:54.5219398Z skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit 2025-08-26T19:55:54.5220114Z specified by the ``github`` argument properly belongs to the repo owner. This will make 2025-08-26T19:55:54.5220804Z requests to the GitHub API; you can specify a non-default GitHub token by setting the 2025-08-26T19:55:54.5221393Z ``GITHUB_TOKEN`` environment variable. Default is ``False``. 2025-08-26T19:55:54.5221915Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T19:55:54.5222267Z 2025-08-26T19:55:54.5222354Z Returns: 2025-08-26T19:55:54.5222672Z The output of the ``model`` callable when called with the given 2025-08-26T19:55:54.5223084Z ``*args`` and ``**kwargs``. 2025-08-26T19:55:54.5223269Z 2025-08-26T19:55:54.5223358Z Example: 2025-08-26T19:55:54.5223621Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T19:55:54.5223980Z >>> # from a github repo 2025-08-26T19:55:54.5224278Z >>> repo = "pytorch/vision" 2025-08-26T19:55:54.5224567Z >>> model = torch.hub.load( 2025-08-26T19:55:54.5224955Z ... repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1" 2025-08-26T19:55:54.5225351Z ... ) 2025-08-26T19:55:54.5225583Z >>> # from a local directory 2025-08-26T19:55:54.5225901Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T19:55:54.5226252Z >>> # xdoctest: +SKIP 2025-08-26T19:55:54.5226673Z >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT") 2025-08-26T19:55:54.5227048Z 2025-08-26T19:55:54.5227317Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5227691Z 2025-08-26T19:55:54.5228189Z msg = Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=657. 2025-08-26T19:55:54.5229035Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5229498Z 2025-08-26T19:55:54.5229691Z Load a model from a local directory with a ``hubconf.py``. 2025-08-26T19:55:54.5229981Z 2025-08-26T19:55:54.5230066Z Args: 2025-08-26T19:55:54.5230385Z hubconf_dir (str): path to a local directory that contains a 2025-08-26T19:55:54.5230792Z ``hubconf.py``. 2025-08-26T19:55:54.5231154Z model (str): name of an entrypoint defined in the directory's 2025-08-26T19:55:54.5231549Z ``hubconf.py``. 2025-08-26T19:55:54.5231923Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T19:55:54.5232524Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T19:55:54.5232863Z 2025-08-26T19:55:54.5232963Z Returns: 2025-08-26T19:55:54.5233246Z a single model with corresponding pretrained weights. 2025-08-26T19:55:54.5233537Z 2025-08-26T19:55:54.5233625Z Example: 2025-08-26T19:55:54.5233872Z >>> # xdoctest: +SKIP("stub local path") 2025-08-26T19:55:54.5234244Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T19:55:54.5234597Z >>> model = _load_local( 2025-08-26T19:55:54.5234860Z ... path, 2025-08-26T19:55:54.5235099Z ... "resnet50", 2025-08-26T19:55:54.5235407Z ... weights="ResNet50_Weights.IMAGENET1K_V1", 2025-08-26T19:55:54.5235744Z ... ) 2025-08-26T19:55:54.5235875Z 2025-08-26T19:55:54.5236130Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5236517Z 2025-08-26T19:55:54.5237015Z msg = Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=696. 2025-08-26T19:55:54.5238110Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5238656Z Download object at the given URL to a local path. 2025-08-26T19:55:54.5238919Z 2025-08-26T19:55:54.5239005Z Args: 2025-08-26T19:55:54.5239261Z url (str): URL of the object to download 2025-08-26T19:55:54.5239743Z dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file`` 2025-08-26T19:55:54.5240448Z hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``. 2025-08-26T19:55:54.5241008Z Default: None 2025-08-26T19:55:54.5241423Z progress (bool, optional): whether or not to display a progress bar to stderr 2025-08-26T19:55:54.5241906Z Default: True 2025-08-26T19:55:54.5242086Z 2025-08-26T19:55:54.5242174Z Example: 2025-08-26T19:55:54.5242455Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T19:55:54.5242816Z >>> # xdoctest: +REQUIRES(POSIX) 2025-08-26T19:55:54.5243178Z >>> torch.hub.download_url_to_file( 2025-08-26T19:55:54.5243646Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth", 2025-08-26T19:55:54.5244112Z ... "/tmp/temporary_file", 2025-08-26T19:55:54.5244411Z ... ) 2025-08-26T19:55:54.5244554Z 2025-08-26T19:55:54.5244640Z 2025-08-26T19:55:54.5245027Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5245405Z 2025-08-26T19:55:54.5245925Z msg = Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=821. 2025-08-26T19:55:54.5246825Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5247365Z Loads the Torch serialized object at the given URL. 2025-08-26T19:55:54.5247651Z 2025-08-26T19:55:54.5247842Z If downloaded file is a zip file, it will be automatically 2025-08-26T19:55:54.5248244Z decompressed. 2025-08-26T19:55:54.5248397Z 2025-08-26T19:55:54.5248632Z If the object is already present in `model_dir`, it's deserialized and 2025-08-26T19:55:54.5249136Z returned. 2025-08-26T19:55:54.5249485Z The default value of ``model_dir`` is ``/checkpoints`` where 2025-08-26T19:55:54.5250039Z ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`. 2025-08-26T19:55:54.5250483Z 2025-08-26T19:55:54.5250585Z Args: 2025-08-26T19:55:54.5250845Z url (str): URL of the object to download 2025-08-26T19:55:54.5251278Z model_dir (str, optional): directory in which to save the object 2025-08-26T19:55:54.5251969Z map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load) 2025-08-26T19:55:54.5252720Z progress (bool, optional): whether or not to display a progress bar to stderr. 2025-08-26T19:55:54.5253208Z Default: True 2025-08-26T19:55:54.5253791Z check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention 2025-08-26T19:55:54.5254459Z ``filename-.ext`` where ```` is the first eight or more 2025-08-26T19:55:54.5255040Z digits of the SHA256 hash of the contents of the file. The hash is used to 2025-08-26T19:55:54.5255594Z ensure unique names and to verify the contents of the file. 2025-08-26T19:55:54.5256012Z Default: False 2025-08-26T19:55:54.5256525Z file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set. 2025-08-26T19:55:54.5257324Z weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects. 2025-08-26T19:55:54.5258045Z Recommended for untrusted sources. See :func:`~torch.load` for more details. 2025-08-26T19:55:54.5258433Z 2025-08-26T19:55:54.5258535Z Example: 2025-08-26T19:55:54.5258818Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T19:55:54.5259220Z >>> state_dict = torch.hub.load_state_dict_from_url( 2025-08-26T19:55:54.5259720Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth" 2025-08-26T19:55:54.5260149Z ... ) 2025-08-26T19:55:54.5260283Z 2025-08-26T19:55:54.5260380Z 2025-08-26T19:55:54.5260745Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5261139Z 2025-08-26T19:55:54.5292288Z msg = Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=375. 2025-08-26T19:55:54.5293188Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:54.5293812Z Registers the function implementation as the fallback for the given key. 2025-08-26T19:55:54.5294175Z 2025-08-26T19:55:54.5294410Z This function only works for a library with global namespace ("_"). 2025-08-26T19:55:54.5294752Z 2025-08-26T19:55:54.5294857Z Args: 2025-08-26T19:55:54.5295269Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-08-26T19:55:54.5295796Z to register a fallthrough. 2025-08-26T19:55:54.5296357Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-08-26T19:55:54.5296987Z the dispatch key that the library was created with. 2025-08-26T19:55:54.5297653Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-08-26T19:55:54.5298496Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-08-26T19:55:54.5298960Z 2025-08-26T19:55:54.5299077Z Example:: 2025-08-26T19:55:54.5299235Z 2025-08-26T19:55:54.5299349Z >>> my_lib = Library("_", "IMPL") 2025-08-26T19:55:54.5299729Z >>> def fallback_kernel(op, *args, **kwargs): 2025-08-26T19:55:54.5300107Z >>> # Handle all autocast ops generically 2025-08-26T19:55:54.5300452Z >>> # ... 2025-08-26T19:55:54.5300776Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T19:55:54.5301132Z 2025-08-26T19:55:54.5301901Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-08-26T19:55:54.5302771Z 2025-08-26T19:55:54.5302908Z my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T19:55:54.5303244Z ^ 2025-08-26T19:55:54.5373777Z msg = Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=948. 2025-08-26T19:55:54.5374653Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:54.5406837Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-08-26T19:55:54.5407499Z 2025-08-26T19:55:54.5407771Z Also sometimes known as a "meta kernel", "abstract impl". 2025-08-26T19:55:54.5408077Z 2025-08-26T19:55:54.5408346Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-08-26T19:55:54.5409040Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-08-26T19:55:54.5409642Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-08-26T19:55:54.5410181Z what the properties of the output Tensors are. 2025-08-26T19:55:54.5410442Z 2025-08-26T19:55:54.5410697Z The FakeTensor implementation has the same signature as the operator. 2025-08-26T19:55:54.5411275Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-08-26T19:55:54.5411826Z implementation, assume that all Tensor inputs to the operator are 2025-08-26T19:55:54.5412386Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-08-26T19:55:54.5412933Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-08-26T19:55:54.5413505Z The FakeTensor implementation must consist of only PyTorch operations 2025-08-26T19:55:54.5414050Z (and may not directly access the storage or data of any input or 2025-08-26T19:55:54.5414476Z intermediate Tensors). 2025-08-26T19:55:54.5414671Z 2025-08-26T19:55:54.5414825Z This API may be used as a decorator (see examples). 2025-08-26T19:55:54.5415098Z 2025-08-26T19:55:54.5415253Z For a detailed guide on custom ops, please see 2025-08-26T19:55:54.5415761Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-08-26T19:55:54.5416114Z 2025-08-26T19:55:54.5416201Z Args: 2025-08-26T19:55:54.5416559Z op_name: Operator name (along with the overload) or OpOverload object. 2025-08-26T19:55:54.5417030Z func: Fake tensor implementation. 2025-08-26T19:55:54.5417469Z lib (Optional[Library]): Library to register the fake tensor to. 2025-08-26T19:55:54.5417976Z allow_override: Flag controlling if we want to override an 2025-08-26T19:55:54.5418464Z existing registered fake impl. This is by default off, 2025-08-26T19:55:54.5418948Z and will error you're trying to register a fake impl to 2025-08-26T19:55:54.5419426Z an operator that already has a fake impl. This also only 2025-08-26T19:55:54.5419889Z applies if the custom operator was not created via 2025-08-26T19:55:54.5420367Z torch.library.custom_op, as overriding and existing fake 2025-08-26T19:55:54.5420801Z impl is already allowed. 2025-08-26T19:55:54.5421044Z 2025-08-26T19:55:54.5421134Z Examples: 2025-08-26T19:55:54.5421372Z >>> import torch 2025-08-26T19:55:54.5421641Z >>> import numpy as np 2025-08-26T19:55:54.5421942Z >>> from torch import Tensor 2025-08-26T19:55:54.5422242Z >>> 2025-08-26T19:55:54.5422569Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T19:55:54.5423106Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-08-26T19:55:54.5423674Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T19:55:54.5424211Z >>> raise NotImplementedError("Implementation goes here") 2025-08-26T19:55:54.5424602Z >>> 2025-08-26T19:55:54.5424909Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-08-26T19:55:54.5425862Z >>> def _(x, weight, bias): 2025-08-26T19:55:54.5426176Z >>> assert x.dim() == 2 2025-08-26T19:55:54.5426497Z >>> assert weight.dim() == 2 2025-08-26T19:55:54.5426827Z >>> assert bias.dim() == 1 2025-08-26T19:55:54.5427167Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T19:55:54.5427545Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T19:55:54.5427916Z >>> assert x.device == weight.device 2025-08-26T19:55:54.5428292Z >>> 2025-08-26T19:55:54.5428531Z >>> return (x @ weight.t()) + bias 2025-08-26T19:55:54.5428849Z >>> 2025-08-26T19:55:54.5429147Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-08-26T19:55:54.5429564Z >>> x = torch.randn(2, 3) 2025-08-26T19:55:54.5429873Z >>> w = torch.randn(3, 3) 2025-08-26T19:55:54.5430189Z >>> b = torch.randn(3) 2025-08-26T19:55:54.5430541Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-08-26T19:55:54.5430889Z >>> 2025-08-26T19:55:54.5431111Z >>> assert y.shape == (2, 3) 2025-08-26T19:55:54.5431408Z >>> 2025-08-26T19:55:54.5431716Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T19:55:54.5432244Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-08-26T19:55:54.5432712Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-08-26T19:55:54.5433077Z >>> x_np = x.numpy(force=True) 2025-08-26T19:55:54.5433444Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T19:55:54.5433830Z >>> return torch.tensor(res, device=x.device) 2025-08-26T19:55:54.5434157Z >>> 2025-08-26T19:55:54.5435943Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-08-26T19:55:54.5436337Z >>> def _(x): 2025-08-26T19:55:54.5436658Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T19:55:54.5437095Z >>> # Since we cannot peek at the data in an fake impl, 2025-08-26T19:55:54.5437660Z >>> # we use the ctx object to construct a new symint that 2025-08-26T19:55:54.5438085Z >>> # represents the data-dependent size. 2025-08-26T19:55:54.5438460Z >>> ctx = torch.library.get_ctx() 2025-08-26T19:55:54.5438814Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T19:55:54.5439136Z >>> shape = [nnz, x.dim()] 2025-08-26T19:55:54.5439506Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T19:55:54.5439876Z >>> return result 2025-08-26T19:55:54.5440149Z >>> 2025-08-26T19:55:54.5440449Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T19:55:54.5440837Z >>> 2025-08-26T19:55:54.5441079Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-08-26T19:55:54.5441559Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-08-26T19:55:54.5442038Z >>> trace.print_readable() 2025-08-26T19:55:54.5442335Z >>> 2025-08-26T19:55:54.5442694Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-08-26T19:55:54.5443042Z 2025-08-26T19:55:54.5443139Z 2025-08-26T19:55:54.5443787Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-08-26T19:55:54.5444457Z 2025-08-26T19:55:54.5444544Z _._ = None 2025-08-26T19:55:54.5444758Z ^ 2025-08-26T19:55:54.5445391Z msg = Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1083. 2025-08-26T19:55:54.5446294Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5446824Z Register a backward formula for this custom op. 2025-08-26T19:55:54.5447093Z 2025-08-26T19:55:54.5447302Z In order for an operator to work with autograd, you need to register 2025-08-26T19:55:54.5447867Z a backward formula: 2025-08-26T19:55:54.5448250Z 1. You must tell us how to compute gradients during the backward pass 2025-08-26T19:55:54.5448695Z by providing us a "backward" function. 2025-08-26T19:55:54.5449228Z 2. If you need any values from the forward to compute gradients, you can 2025-08-26T19:55:54.5449721Z use `setup_context` to save values for backward. 2025-08-26T19:55:54.5449979Z 2025-08-26T19:55:54.5450226Z ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``: 2025-08-26T19:55:54.5450863Z - ``grads`` is one or more gradients. The number of gradients matches 2025-08-26T19:55:54.5451305Z the number of outputs of the operator. 2025-08-26T19:55:54.5451767Z The ``ctx`` object is `the same ctx object `_ used by 2025-08-26T19:55:54.5452363Z :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the 2025-08-26T19:55:54.5452897Z same as :meth:`torch.autograd.Function.backward`. 2025-08-26T19:55:54.5453173Z 2025-08-26T19:55:54.5453408Z ``setup_context(ctx, inputs, output)`` runs during the forward pass. 2025-08-26T19:55:54.5453967Z Please save quantities needed for backward onto the ``ctx`` object via 2025-08-26T19:55:54.5454562Z either :meth:`torch.autograd.function.FunctionCtx.save_for_backward` 2025-08-26T19:55:54.5455128Z or assigning them as attributes of ``ctx``. If your custom op has 2025-08-26T19:55:54.5455670Z kwarg-only arguments, we expect the signature of ``setup_context`` 2025-08-26T19:55:54.5456199Z to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``. 2025-08-26T19:55:54.5456522Z 2025-08-26T19:55:54.5456745Z Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is, 2025-08-26T19:55:54.5457325Z they may not directly access :meth:`torch.Tensor.data_ptr` and they must 2025-08-26T19:55:54.5457918Z not depend on or mutate global state. If you need a non-traceable backward, 2025-08-26T19:55:54.5458513Z you can make it a separate custom_op that you call inside ``backward_fn``. 2025-08-26T19:55:54.5458861Z 2025-08-26T19:55:54.5459080Z If you need different autograd behavior on different devices, then we 2025-08-26T19:55:54.5459660Z recommend creating two different custom operators, one for each device 2025-08-26T19:55:54.5460247Z that needs different behavior, and switching between them at runtime. 2025-08-26T19:55:54.5460591Z 2025-08-26T19:55:54.5460693Z Examples: 2025-08-26T19:55:54.5460928Z >>> import torch 2025-08-26T19:55:54.5461198Z >>> import numpy as np 2025-08-26T19:55:54.5461500Z >>> from torch import Tensor 2025-08-26T19:55:54.5461798Z >>> 2025-08-26T19:55:54.5462148Z >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=()) 2025-08-26T19:55:54.5462591Z >>> def numpy_sin(x: Tensor) -> Tensor: 2025-08-26T19:55:54.5462939Z >>> x_np = x.cpu().numpy() 2025-08-26T19:55:54.5463258Z >>> y_np = np.sin(x_np) 2025-08-26T19:55:54.5463629Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T19:55:54.5463985Z >>> 2025-08-26T19:55:54.5464274Z >>> def setup_context(ctx, inputs, output) -> Tensor: 2025-08-26T19:55:54.5464651Z >>> x, = inputs 2025-08-26T19:55:54.5464947Z >>> ctx.save_for_backward(x) 2025-08-26T19:55:54.5465246Z >>> 2025-08-26T19:55:54.5465487Z >>> def backward(ctx, grad): 2025-08-26T19:55:54.5465803Z >>> x, = ctx.saved_tensors 2025-08-26T19:55:54.5466126Z >>> return grad * x.cos() 2025-08-26T19:55:54.5466411Z >>> 2025-08-26T19:55:54.5466663Z >>> torch.library.register_autograd( 2025-08-26T19:55:54.5467087Z ... "mylib::numpy_sin", backward, setup_context=setup_context 2025-08-26T19:55:54.5467480Z ... ) 2025-08-26T19:55:54.5467689Z >>> 2025-08-26T19:55:54.5467944Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T19:55:54.5468363Z >>> y = numpy_sin(x) 2025-08-26T19:55:54.5468728Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T19:55:54.5469144Z >>> assert torch.allclose(grad_x, x.cos()) 2025-08-26T19:55:54.5469482Z >>> 2025-08-26T19:55:54.5469737Z >>> # Example with a keyword-only arg 2025-08-26T19:55:54.5470185Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T19:55:54.5470657Z >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor: 2025-08-26T19:55:54.5471113Z >>> x_np = x.cpu().numpy() 2025-08-26T19:55:54.5471431Z >>> y_np = x_np * val 2025-08-26T19:55:54.5471792Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T19:55:54.5472145Z >>> 2025-08-26T19:55:54.5472505Z >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor: 2025-08-26T19:55:54.5473002Z >>> ctx.val = keyword_only_inputs["val"] 2025-08-26T19:55:54.5473337Z >>> 2025-08-26T19:55:54.5473565Z >>> def backward(ctx, grad): 2025-08-26T19:55:54.5473882Z >>> return grad * ctx.val 2025-08-26T19:55:54.5474178Z >>> 2025-08-26T19:55:54.5474433Z >>> torch.library.register_autograd( 2025-08-26T19:55:54.5474857Z ... "mylib::numpy_mul", backward, setup_context=setup_context 2025-08-26T19:55:54.5475239Z ... ) 2025-08-26T19:55:54.5475459Z >>> 2025-08-26T19:55:54.5475712Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T19:55:54.5476064Z >>> y = numpy_mul(x, val=3.14) 2025-08-26T19:55:54.5476444Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T19:55:54.5476922Z >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14)) 2025-08-26T19:55:54.5477217Z 2025-08-26T19:55:54.5477312Z 2025-08-26T19:55:54.5477688Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5478065Z 2025-08-26T19:55:54.5478606Z msg = Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1482. 2025-08-26T19:55:54.5479460Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:54.5480053Z Returns the computed kernel for a given operator and dispatch key. 2025-08-26T19:55:54.5480386Z 2025-08-26T19:55:54.5480615Z This function retrieves the kernel that would be executed for a given 2025-08-26T19:55:54.5481208Z operator and dispatch key combination. The returned SafeKernelFunction 2025-08-26T19:55:54.5481779Z can be used to call the kernel in a boxed fashion. The intended use 2025-08-26T19:55:54.5482324Z case for this function is to retrieve the original kernel for a given 2025-08-26T19:55:54.5482895Z dispatch key and then register another kernel to the same dispatch key 2025-08-26T19:55:54.5483403Z that calls into the original kernel for certain cases. 2025-08-26T19:55:54.5483698Z 2025-08-26T19:55:54.5483785Z Args: 2025-08-26T19:55:54.5484119Z op: Operator name (along with the overload) or OpOverload object 2025-08-26T19:55:54.5484676Z Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef. 2025-08-26T19:55:54.5485282Z dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for. 2025-08-26T19:55:54.5485866Z Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value. 2025-08-26T19:55:54.5486194Z 2025-08-26T19:55:54.5486280Z Returns: 2025-08-26T19:55:54.5486660Z torch._C._SafeKernelFunction: A safe kernel function that can be used to 2025-08-26T19:55:54.5487126Z call the kernel. 2025-08-26T19:55:54.5487307Z 2025-08-26T19:55:54.5487392Z Raises: 2025-08-26T19:55:54.5487669Z RuntimeError: If the operator does not exist. 2025-08-26T19:55:54.5487930Z 2025-08-26T19:55:54.5488033Z Example: 2025-08-26T19:55:54.5488292Z >>> # Get the CPU kernel for torch.add 2025-08-26T19:55:54.5488715Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU") 2025-08-26T19:55:54.5489279Z >>> 2025-08-26T19:55:54.5489538Z >>> # You can also use DispatchKey enum 2025-08-26T19:55:54.5490049Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU) 2025-08-26T19:55:54.5490516Z >>> 2025-08-26T19:55:54.5490762Z >>> # Or use an OpOverload directly 2025-08-26T19:55:54.5491227Z >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU") 2025-08-26T19:55:54.5491668Z >>> 2025-08-26T19:55:54.5492058Z >>> # Example: Using get_kernel in a custom op with conditional dispatch 2025-08-26T19:55:54.5492532Z >>> # Get the original kernel for torch.sin 2025-08-26T19:55:54.5493003Z >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU") 2025-08-26T19:55:54.5493432Z >>> 2025-08-26T19:55:54.5493790Z >>> # If input has negative values, use original sin, otherwise return zeros 2025-08-26T19:55:54.5494282Z >>> def conditional_sin_impl(dispatch_keys, x): 2025-08-26T19:55:54.5494641Z >>> if (x < 0).any(): 2025-08-26T19:55:54.5495029Z >>> return original_sin_kernel.call_boxed(dispatch_keys, x) 2025-08-26T19:55:54.5495430Z >>> else: 2025-08-26T19:55:54.5495696Z >>> return torch.zeros_like(x) 2025-08-26T19:55:54.5496013Z >>> 2025-08-26T19:55:54.5496278Z >>> lib = torch.library.Library("aten", "IMPL") 2025-08-26T19:55:54.5496803Z >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet 2025-08-26T19:55:54.5497374Z >>> which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T19:55:54.5497883Z >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True) 2025-08-26T19:55:54.5498287Z >>> 2025-08-26T19:55:54.5498529Z >>> # Test the conditional behavior 2025-08-26T19:55:54.5498873Z >>> x_positive = torch.tensor([1.0, 2.0]) 2025-08-26T19:55:54.5499240Z >>> x_mixed = torch.tensor([-1.0, 2.0]) 2025-08-26T19:55:54.5499585Z >>> torch.sin(x_positive) 2025-08-26T19:55:54.5499884Z tensor([0., 0.]) 2025-08-26T19:55:54.5500156Z >>> torch.sin(x_mixed) 2025-08-26T19:55:54.5500435Z tensor([-0.8415, 0.9093]) 2025-08-26T19:55:54.5500717Z 2025-08-26T19:55:54.5501336Z Original Error: SyntaxError('invalid syntax', ('', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12)) 2025-08-26T19:55:54.5501939Z 2025-08-26T19:55:54.5502142Z which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T19:55:54.5502528Z ^ 2025-08-26T19:55:54.5503126Z msg = Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1571. 2025-08-26T19:55:54.5503987Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5504598Z Given an operator and some sample arguments, tests if the operator is 2025-08-26T19:55:54.5505034Z registered correctly. 2025-08-26T19:55:54.5505220Z 2025-08-26T19:55:54.5505432Z That is, when you use the torch.library/TORCH_LIBRARY APIs to create a 2025-08-26T19:55:54.5506032Z custom op, you specified metadata (e.g. mutability info) about the custom op 2025-08-26T19:55:54.5506622Z and these APIs require that the functions you pass them satisfy certain 2025-08-26T19:55:54.5507213Z properties (e.g. no data pointer access in the fake/meta/abstract kernel) 2025-08-26T19:55:54.5507725Z ``opcheck`` tests these metadata and properties. 2025-08-26T19:55:54.5507986Z 2025-08-26T19:55:54.5508117Z Concretely, we test the following: 2025-08-26T19:55:54.5508336Z 2025-08-26T19:55:54.5508515Z - test_schema: If the schema matches the implementation of 2025-08-26T19:55:54.5509044Z the operator. For example: if the schema specifies a Tensor is mutated, 2025-08-26T19:55:54.5509606Z then we check the implementation mutates the Tensor. If the schema 2025-08-26T19:55:54.5510215Z specifies that we return a new Tensor, then we check that the 2025-08-26T19:55:54.5510763Z implementation returns a new Tensor (instead of an existing one or 2025-08-26T19:55:54.5511206Z a view of an existing one). 2025-08-26T19:55:54.5511618Z - test_autograd_registration: If the operator supports training 2025-08-26T19:55:54.5512145Z (autograd): we check that its autograd formula is registered via 2025-08-26T19:55:54.5512684Z torch.library.register_autograd or a manual registration to one 2025-08-26T19:55:54.5513270Z or more DispatchKey::Autograd keys. Any other DispatchKey-based 2025-08-26T19:55:54.5513739Z registrations may lead to undefined behavior. 2025-08-26T19:55:54.5514181Z - test_faketensor: If the operator has a FakeTensor kernel 2025-08-26T19:55:54.5514654Z (and if it is correct). The FakeTensor kernel is necessary ( 2025-08-26T19:55:54.5515174Z but not sufficient) for the operator to work with PyTorch compilation 2025-08-26T19:55:54.5515728Z APIs (torch.compile/export/FX). We check that a FakeTensor kernel 2025-08-26T19:55:54.5516265Z (also sometimes known as a meta kernel) was registered for the 2025-08-26T19:55:54.5516779Z operator and that it is correct. This test takes the result of 2025-08-26T19:55:54.5517297Z running the operator on real tensors and the result of running 2025-08-26T19:55:54.5517804Z the operator on FakeTensors and checks that they have the same 2025-08-26T19:55:54.5518282Z Tensor metadata (sizes/strides/dtype/device/etc). 2025-08-26T19:55:54.5518757Z - test_aot_dispatch_dynamic: If the operator has correct behavior 2025-08-26T19:55:54.5519270Z with PyTorch compilation APIs (torch.compile/export/FX). 2025-08-26T19:55:54.5519791Z This checks that the outputs (and gradients, if applicable) are the 2025-08-26T19:55:54.5520269Z same under eager-mode PyTorch and torch.compile. 2025-08-26T19:55:54.5520738Z This test is a superset of ``test_faketensor`` and is an e2e test; 2025-08-26T19:55:54.5521228Z other things it tests are that the operator supports 2025-08-26T19:55:54.5521734Z functionalization and that the backward pass (if it exists) also 2025-08-26T19:55:54.5522204Z supports FakeTensor and functionalization. 2025-08-26T19:55:54.5522464Z 2025-08-26T19:55:54.5522664Z For best results, please call ``opcheck`` multiple times with a 2025-08-26T19:55:54.5523170Z representative set of inputs. If your operator supports 2025-08-26T19:55:54.5523714Z autograd, please use ``opcheck`` with inputs with ``requires_grad = True``; 2025-08-26T19:55:54.5524307Z if your operator supports multiple devices (e.g. CPU and CUDA), please 2025-08-26T19:55:54.5524804Z use ``opcheck`` with inputs on all supported devices. 2025-08-26T19:55:54.5525089Z 2025-08-26T19:55:54.5525175Z Args: 2025-08-26T19:55:54.5525486Z op: The operator. Must either be a function decorated with 2025-08-26T19:55:54.5526011Z :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket 2025-08-26T19:55:54.5526566Z found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo) 2025-08-26T19:55:54.5527027Z args: The args to the operator 2025-08-26T19:55:54.5527367Z kwargs: The kwargs to the operator 2025-08-26T19:55:54.5527783Z test_utils: Tests that we should run. Default: all of them. 2025-08-26T19:55:54.5528213Z Example: ("test_schema", "test_faketensor") 2025-08-26T19:55:54.5528669Z raise_exception: If we should raise an exception on the first 2025-08-26T19:55:54.5529244Z error. If False, we will return a dict with information 2025-08-26T19:55:54.5529651Z on if each test passed or not. 2025-08-26T19:55:54.5530126Z rtol (Optional[float]): Relative tolerance for floating point comparisons. 2025-08-26T19:55:54.5530628Z If specified ``atol`` must also be specified. 2025-08-26T19:55:54.5531087Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T19:55:54.5531640Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T19:55:54.5532177Z atol (Optional[float]): Absolute tolerance for floating point comparisons. 2025-08-26T19:55:54.5532677Z If specified ``rtol`` must also be specified. 2025-08-26T19:55:54.5533133Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T19:55:54.5533628Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T19:55:54.5533962Z 2025-08-26T19:55:54.5534071Z .. warning:: 2025-08-26T19:55:54.5534212Z 2025-08-26T19:55:54.5534449Z opcheck and :func:`torch.autograd.gradcheck` test different things; 2025-08-26T19:55:54.5534997Z opcheck tests if your usage of torch.library APIs is correct while 2025-08-26T19:55:54.5535555Z :func:`torch.autograd.gradcheck` tests if your autograd formula is 2025-08-26T19:55:54.5536116Z mathematically correct. Use both to test custom ops that support 2025-08-26T19:55:54.5536570Z gradient computation. 2025-08-26T19:55:54.5536761Z 2025-08-26T19:55:54.5536848Z Example: 2025-08-26T19:55:54.5536995Z 2025-08-26T19:55:54.5537134Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:55:54.5537753Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T19:55:54.5538232Z >>> def numpy_mul(x: Tensor, y: float) -> Tensor: 2025-08-26T19:55:54.5538605Z >>> x_np = x.numpy(force=True) 2025-08-26T19:55:54.5538921Z >>> z_np = x_np * y 2025-08-26T19:55:54.5539258Z >>> return torch.from_numpy(z_np).to(x.device) 2025-08-26T19:55:54.5539599Z >>> 2025-08-26T19:55:54.5539839Z >>> @numpy_mul.register_fake 2025-08-26T19:55:54.5540139Z >>> def _(x, y): 2025-08-26T19:55:54.5540420Z >>> return torch.empty_like(x) 2025-08-26T19:55:54.5540734Z >>> 2025-08-26T19:55:54.5540998Z >>> def setup_context(ctx, inputs, output): 2025-08-26T19:55:54.5541329Z >>> y, = inputs 2025-08-26T19:55:54.5541597Z >>> ctx.y = y 2025-08-26T19:55:54.5541854Z >>> 2025-08-26T19:55:54.5542090Z >>> def backward(ctx, grad): 2025-08-26T19:55:54.5542398Z >>> return grad * ctx.y, None 2025-08-26T19:55:54.5542706Z >>> 2025-08-26T19:55:54.5543056Z >>> numpy_mul.register_autograd(backward, setup_context=setup_context) 2025-08-26T19:55:54.5543491Z >>> 2025-08-26T19:55:54.5543710Z >>> sample_inputs = [ 2025-08-26T19:55:54.5544007Z >>> (torch.randn(3), 3.14), 2025-08-26T19:55:54.5544358Z >>> (torch.randn(2, 3, device='cuda'), 2.718), 2025-08-26T19:55:54.5544760Z >>> (torch.randn(1, 10, requires_grad=True), 1.234), 2025-08-26T19:55:54.5545215Z >>> (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18), 2025-08-26T19:55:54.5545619Z >>> ] 2025-08-26T19:55:54.5545845Z >>> 2025-08-26T19:55:54.5546086Z >>> for args in sample_inputs: 2025-08-26T19:55:54.5546433Z >>> torch.library.opcheck(numpy_mul, args) 2025-08-26T19:55:54.5546693Z 2025-08-26T19:55:54.5546775Z 2025-08-26T19:55:54.5547152Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5547527Z 2025-08-26T19:55:54.5927540Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py line=1285. 2025-08-26T19:55:54.5928426Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.5929204Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args) 2025-08-26T19:55:54.5929674Z 2025-08-26T19:55:54.5929855Z Loads an object saved with :func:`torch.save` from a file. 2025-08-26T19:55:54.5930164Z 2025-08-26T19:55:54.5930400Z :func:`torch.load` uses Python's unpickling facilities but treats storages, 2025-08-26T19:55:54.5931204Z which underlie tensors, specially. They are first deserialized on the 2025-08-26T19:55:54.5931781Z CPU and are then moved to the device they were saved from. If this fails 2025-08-26T19:55:54.5932349Z (e.g. because the run time system doesn't have certain devices), an exception 2025-08-26T19:55:54.5932954Z is raised. However, storages can be dynamically remapped to an alternative 2025-08-26T19:55:54.5933492Z set of devices using the :attr:`map_location` argument. 2025-08-26T19:55:54.5933773Z 2025-08-26T19:55:54.5934135Z If :attr:`map_location` is a callable, it will be called once for each serialized 2025-08-26T19:55:54.5934744Z storage with two arguments: storage and location. The storage argument 2025-08-26T19:55:54.5935320Z will be the initial deserialization of the storage, residing on the CPU. 2025-08-26T19:55:54.5935903Z Each serialized storage has a location tag associated with it which 2025-08-26T19:55:54.5936462Z identifies the device it was saved from, and this tag is the second 2025-08-26T19:55:54.5937067Z argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'`` 2025-08-26T19:55:54.5937799Z for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors. 2025-08-26T19:55:54.5938350Z :attr:`map_location` should return either ``None`` or a storage. If 2025-08-26T19:55:54.5938939Z :attr:`map_location` returns a storage, it will be used as the final deserialized 2025-08-26T19:55:54.5939579Z object, already moved to the right device. Otherwise, :func:`torch.load` will 2025-08-26T19:55:54.5940208Z fall back to the default behavior, as if :attr:`map_location` wasn't specified. 2025-08-26T19:55:54.5940578Z 2025-08-26T19:55:54.5940817Z If :attr:`map_location` is a :class:`torch.device` object or a string containing 2025-08-26T19:55:54.5941427Z a device tag, it indicates the location where all tensors should be loaded. 2025-08-26T19:55:54.5941799Z 2025-08-26T19:55:54.5942065Z Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags 2025-08-26T19:55:54.5942675Z appearing in the file (keys), to ones that specify where to put the 2025-08-26T19:55:54.5943139Z storages (values). 2025-08-26T19:55:54.5943302Z 2025-08-26T19:55:54.5943541Z User extensions can register their own location tags and tagging and 2025-08-26T19:55:54.5944160Z deserialization methods using :func:`torch.serialization.register_package`. 2025-08-26T19:55:54.5944547Z 2025-08-26T19:55:54.5944801Z See :ref:`layout-control` for more advanced tools to manipulate a checkpoint. 2025-08-26T19:55:54.5945183Z 2025-08-26T19:55:54.5945270Z Args: 2025-08-26T19:55:54.5945724Z f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`), 2025-08-26T19:55:54.5946351Z or a string or os.PathLike object containing a file name 2025-08-26T19:55:54.5946971Z map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage 2025-08-26T19:55:54.5947527Z locations 2025-08-26T19:55:54.5947920Z pickle_module: module used for unpickling metadata and objects (has to 2025-08-26T19:55:54.5948458Z match the :attr:`pickle_module` used to serialize file) 2025-08-26T19:55:54.5948971Z weights_only: Indicates whether unpickler should be restricted to 2025-08-26T19:55:54.5949486Z loading only tensors, primitive types, dictionaries 2025-08-26T19:55:54.5950001Z and any types added via :func:`torch.serialization.add_safe_globals`. 2025-08-26T19:55:54.5950491Z See :ref:`weights-only` for more details. 2025-08-26T19:55:54.5951095Z mmap: Indicates whether the file should be mapped rather than loading all the storages into memory. 2025-08-26T19:55:54.5951908Z Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they 2025-08-26T19:55:54.5952713Z are moved to the location that they were tagged with when saving, or specified by ``map_location``. This 2025-08-26T19:55:54.5953630Z second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the 2025-08-26T19:55:54.5954427Z tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages 2025-08-26T19:55:54.5955054Z will be lazily loaded when their data is accessed. 2025-08-26T19:55:54.5955662Z pickle_load_args: (Python 3 only) optional keyword arguments passed over to 2025-08-26T19:55:54.5956257Z :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g., 2025-08-26T19:55:54.5956721Z :attr:`errors=...`. 2025-08-26T19:55:54.5956923Z 2025-08-26T19:55:54.5957033Z .. warning:: 2025-08-26T19:55:54.5957403Z :func:`torch.load()` unless `weights_only` parameter is set to `True`, 2025-08-26T19:55:54.5957935Z uses ``pickle`` module implicitly, which is known to be insecure. 2025-08-26T19:55:54.5958550Z It is possible to construct malicious pickle data which will execute arbitrary code 2025-08-26T19:55:54.5959208Z during unpickling. Never load data that could have come from an untrusted 2025-08-26T19:55:54.5959876Z source in an unsafe mode, or that could have been tampered with. **Only load data you trust**. 2025-08-26T19:55:54.5960296Z 2025-08-26T19:55:54.5960394Z .. note:: 2025-08-26T19:55:54.5960786Z When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors 2025-08-26T19:55:54.5961443Z will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')`` 2025-08-26T19:55:54.5962109Z and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint. 2025-08-26T19:55:54.5962510Z 2025-08-26T19:55:54.5962611Z .. note:: 2025-08-26T19:55:54.5963003Z By default, we decode byte strings as ``utf-8``. This is to avoid a common error 2025-08-26T19:55:54.5963594Z case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...`` 2025-08-26T19:55:54.5964147Z when loading files saved by Python 2 in Python 3. If this default 2025-08-26T19:55:54.5964743Z is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how 2025-08-26T19:55:54.5965373Z these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them 2025-08-26T19:55:54.5965974Z to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them 2025-08-26T19:55:54.5966581Z as byte arrays which can be decoded later with ``byte_array.decode(...)``. 2025-08-26T19:55:54.5966947Z 2025-08-26T19:55:54.5967035Z Example: 2025-08-26T19:55:54.5967307Z >>> # xdoctest: +SKIP("undefined filepaths") 2025-08-26T19:55:54.5967703Z >>> torch.load("tensors.pt", weights_only=True) 2025-08-26T19:55:54.5968069Z # Load all tensors onto the CPU 2025-08-26T19:55:54.5968390Z >>> torch.load( 2025-08-26T19:55:54.5968660Z ... "tensors.pt", 2025-08-26T19:55:54.5969061Z ... map_location=torch.device("cpu"), 2025-08-26T19:55:54.5969402Z ... weights_only=True, 2025-08-26T19:55:54.5969695Z ... ) 2025-08-26T19:55:54.5969976Z # Load all tensors onto the CPU, using a function 2025-08-26T19:55:54.5970331Z >>> torch.load( 2025-08-26T19:55:54.5970582Z ... "tensors.pt", 2025-08-26T19:55:54.5970910Z ... map_location=lambda storage, loc: storage, 2025-08-26T19:55:54.5971281Z ... weights_only=True, 2025-08-26T19:55:54.5971571Z ... ) 2025-08-26T19:55:54.5971805Z # Load all tensors onto GPU 1 2025-08-26T19:55:54.5972115Z >>> torch.load( 2025-08-26T19:55:54.5972377Z ... "tensors.pt", 2025-08-26T19:55:54.5972730Z ... map_location=lambda storage, loc: storage.cuda(1), 2025-08-26T19:55:54.5973111Z ... weights_only=True, 2025-08-26T19:55:54.5973435Z ... ) # type: ignore[attr-defined] 2025-08-26T19:55:54.5973859Z # Map tensors from GPU 1 to GPU 0 2025-08-26T19:55:54.5974190Z >>> torch.load( 2025-08-26T19:55:54.5974446Z ... "tensors.pt", 2025-08-26T19:55:54.5974757Z ... map_location={"cuda:1": "cuda:0"}, 2025-08-26T19:55:54.5975103Z ... weights_only=True, 2025-08-26T19:55:54.5975392Z ... ) 2025-08-26T19:55:54.5975632Z # Load tensor from io.BytesIO object 2025-08-26T19:55:54.5976174Z # Loading from a buffer setting weights_only=False, warning this can be unsafe 2025-08-26T19:55:54.5976682Z >>> with open("tensor.pt", "rb") as f: 2025-08-26T19:55:54.5977034Z ... buffer = io.BytesIO(f.read()) 2025-08-26T19:55:54.5977381Z >>> torch.load(buffer, weights_only=False) 2025-08-26T19:55:54.5977782Z # Load a module with 'ascii' encoding for unpickling 2025-08-26T19:55:54.5978305Z # Loading from a module setting weights_only=False, warning this can be unsafe 2025-08-26T19:55:54.5978888Z >>> torch.load("module.pt", encoding="ascii", weights_only=False) 2025-08-26T19:55:54.5979298Z 2025-08-26T19:55:54.5979662Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.5980052Z 2025-08-26T19:55:54.6564040Z msg = Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims_common/__init__.py line=1877. 2025-08-26T19:55:54.6565079Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.6565697Z Computes the minimum storage size to hold the given tensor geometry. 2025-08-26T19:55:54.6566036Z 2025-08-26T19:55:54.6566139Z Example 2025-08-26T19:55:54.6566342Z ======= 2025-08-26T19:55:54.6566477Z 2025-08-26T19:55:54.6566708Z This is the size of a newly allocated tensor's storage, in units of elements 2025-08-26T19:55:54.6567069Z 2025-08-26T19:55:54.6567174Z >>> t = torch.empty((10, 20)) 2025-08-26T19:55:54.6567637Z >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset()) 2025-08-26T19:55:54.6568098Z 200 2025-08-26T19:55:54.6568213Z 2025-08-26T19:55:54.6568320Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:55:54.6568664Z >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11)) 2025-08-26T19:55:54.6569097Z >>> size = compute_required_storage_length( 2025-08-26T19:55:54.6569487Z ... t2.shape, t2.stride(), t2.storage_offset() 2025-08-26T19:55:54.6569813Z ... ) 2025-08-26T19:55:54.6570049Z >>> size == t.storage().size() 2025-08-26T19:55:54.6570338Z True 2025-08-26T19:55:54.6570456Z 2025-08-26T19:55:54.6570667Z A valid tensor may have a larger storage size, but never smaller 2025-08-26T19:55:54.6570982Z 2025-08-26T19:55:54.6571091Z >>> slice = torch.empty(100)[20:40] 2025-08-26T19:55:54.6571423Z >>> slice.storage().size() 2025-08-26T19:55:54.6571702Z 100 2025-08-26T19:55:54.6571816Z 2025-08-26T19:55:54.6571941Z >>> compute_required_storage_length( 2025-08-26T19:55:54.6572329Z ... slice.shape, slice.stride(), slice.storage_offset() 2025-08-26T19:55:54.6572704Z ... ) 2025-08-26T19:55:54.6572913Z 40 2025-08-26T19:55:54.6573028Z 2025-08-26T19:55:54.6573124Z 2025-08-26T19:55:54.6573501Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.6573880Z 2025-08-26T19:55:54.7170974Z msg = Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=66. 2025-08-26T19:55:54.7171916Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:54.7172556Z Check if the current accelerator is available at runtime: it was build, all the 2025-08-26T19:55:54.7173167Z required drivers are available and at least one device is visible. 2025-08-26T19:55:54.7173667Z See :ref:`accelerator` for details. 2025-08-26T19:55:54.7173931Z 2025-08-26T19:55:54.7174216Z Returns: 2025-08-26T19:55:54.7174643Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-08-26T19:55:54.7175061Z 2025-08-26T19:55:54.7175337Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-08-26T19:55:54.7175984Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-08-26T19:55:54.7176640Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-08-26T19:55:54.7177248Z :ref:`multiprocessing-poison-fork-note`. 2025-08-26T19:55:54.7177522Z 2025-08-26T19:55:54.7177613Z Example:: 2025-08-26T19:55:54.7177759Z 2025-08-26T19:55:54.7178035Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:55:54.7178523Z 2025-08-26T19:55:54.7179218Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-08-26T19:55:54.7179909Z 2025-08-26T19:55:54.7180173Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:55:54.7180665Z ^ 2025-08-26T19:55:54.7188102Z msg = Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=212. 2025-08-26T19:55:54.7189037Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:54.7189633Z Wait for all kernels in all streams on the given device to complete. 2025-08-26T19:55:54.7189959Z 2025-08-26T19:55:54.7190045Z Args: 2025-08-26T19:55:54.7190493Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-08-26T19:55:54.7191176Z the current :ref:`accelerator` device type. If not given, 2025-08-26T19:55:54.7191737Z use :func:`torch.accelerator.current_device_index` by default. 2025-08-26T19:55:54.7192055Z 2025-08-26T19:55:54.7192388Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-08-26T19:55:54.7192823Z 2025-08-26T19:55:54.7192928Z Example:: 2025-08-26T19:55:54.7193062Z 2025-08-26T19:55:54.7193206Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:55:54.7193739Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:55:54.7194287Z >>> start_event = torch.Event(enable_timing=True) 2025-08-26T19:55:54.7194694Z >>> end_event = torch.Event(enable_timing=True) 2025-08-26T19:55:54.7195048Z >>> start_event.record() 2025-08-26T19:55:54.7195499Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-08-26T19:55:54.7195984Z >>> sum = torch.sum(tensor) 2025-08-26T19:55:54.7196300Z >>> end_event.record() 2025-08-26T19:55:54.7196610Z >>> torch.accelerator.synchronize() 2025-08-26T19:55:54.7197026Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-08-26T19:55:54.7197404Z 2025-08-26T19:55:54.7198096Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-08-26T19:55:54.7198778Z 2025-08-26T19:55:54.7199055Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:55:54.7199530Z ^ 2025-08-26T19:55:54.7477466Z msg = Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py line=434. 2025-08-26T19:55:54.7478356Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:54.7478856Z Retrieves the CUDA runtime API module. 2025-08-26T19:55:54.7479082Z 2025-08-26T19:55:54.7479086Z 2025-08-26T19:55:54.7479360Z This function initializes the CUDA runtime environment if it is not already 2025-08-26T19:55:54.7480179Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-08-26T19:55:54.7480757Z runtime API module provides access to various CUDA runtime functions. 2025-08-26T19:55:54.7481119Z 2025-08-26T19:55:54.7481205Z Args: 2025-08-26T19:55:54.7481431Z ``None`` 2025-08-26T19:55:54.7481569Z 2025-08-26T19:55:54.7481670Z Returns: 2025-08-26T19:55:54.7481943Z module: The CUDA runtime API module (_cudart). 2025-08-26T19:55:54.7482214Z 2025-08-26T19:55:54.7482299Z Raises: 2025-08-26T19:55:54.7482748Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-08-26T19:55:54.7483484Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-08-26T19:55:54.7483970Z 2025-08-26T19:55:54.7484118Z Example of CUDA operations with profiling: 2025-08-26T19:55:54.7484457Z >>> import torch 2025-08-26T19:55:54.7484771Z >>> from torch.cuda import cudart, check_error 2025-08-26T19:55:54.7485127Z >>> import os 2025-08-26T19:55:54.7485381Z >>> 2025-08-26T19:55:54.7485618Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-08-26T19:55:54.7485936Z >>> 2025-08-26T19:55:54.7486205Z >>> def perform_cuda_operations_with_streams(): 2025-08-26T19:55:54.7486583Z >>> stream = torch.cuda.Stream() 2025-08-26T19:55:54.7486924Z >>> with torch.cuda.stream(stream): 2025-08-26T19:55:54.7487296Z >>> x = torch.randn(100, 100, device='cuda') 2025-08-26T19:55:54.7487677Z >>> y = torch.randn(100, 100, device='cuda') 2025-08-26T19:55:54.7488031Z >>> z = torch.mul(x, y) 2025-08-26T19:55:54.7488324Z >>> return z 2025-08-26T19:55:54.7488578Z >>> 2025-08-26T19:55:54.7488889Z >>> torch.cuda.synchronize() 2025-08-26T19:55:54.7489246Z >>> print("====== Start nsys profiling ======") 2025-08-26T19:55:54.7489631Z >>> check_error(cudart().cudaProfilerStart()) 2025-08-26T19:55:54.7490037Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-08-26T19:55:54.7490456Z >>> result = perform_cuda_operations_with_streams() 2025-08-26T19:55:54.7490867Z >>> print("CUDA operations completed.") 2025-08-26T19:55:54.7491275Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-08-26T19:55:54.7491696Z >>> print("====== End nsys profiling ======") 2025-08-26T19:55:54.7491951Z 2025-08-26T19:55:54.7492160Z To run this example and save the profiling information, execute: 2025-08-26T19:55:54.7492867Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T19:55:54.7493353Z 2025-08-26T19:55:54.7493615Z This command profiles the CUDA operations in the provided script and saves 2025-08-26T19:55:54.7494178Z the profiling information to a file named `trace_name.prof`. 2025-08-26T19:55:54.7494730Z The `--profile-from-start off` option ensures that profiling starts only 2025-08-26T19:55:54.7495251Z after the `cudaProfilerStart` call in the script. 2025-08-26T19:55:54.7495747Z The `--csv` and `--print-summary` options format the profiling output as a 2025-08-26T19:55:54.7496238Z CSV file and print a summary, respectively. 2025-08-26T19:55:54.7496727Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-08-26T19:55:54.7497260Z overwrite of the output file if it already exists. 2025-08-26T19:55:54.7497632Z 2025-08-26T19:55:54.7498424Z Original Error: SyntaxError('invalid syntax', ('', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2)) 2025-08-26T19:55:54.7499202Z 2025-08-26T19:55:54.7499558Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T19:55:54.7500128Z ^ 2025-08-26T19:55:54.7651817Z msg = Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=101. 2025-08-26T19:55:54.7652890Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.7653291Z 2025-08-26T19:55:54.7653526Z Append the given callback function to this ``Future``, which will be run 2025-08-26T19:55:54.7654100Z when the ``Future`` is completed. Multiple callbacks can be added to 2025-08-26T19:55:54.7654650Z the same ``Future``, but the order in which they will be executed cannot 2025-08-26T19:55:54.7655250Z be guaranteed (to enforce a certain order consider chaining: 2025-08-26T19:55:54.7655769Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which 2025-08-26T19:55:54.7656313Z is the reference to this ``Future``. The callback function can use the 2025-08-26T19:55:54.7656866Z :meth:`value` method to get the value. Note that if this ``Future`` is 2025-08-26T19:55:54.7657422Z already completed, the given callback will be run immediately inline. 2025-08-26T19:55:54.7657787Z 2025-08-26T19:55:54.7657985Z If the ``Future``'s value contains tensors that reside on GPUs, the 2025-08-26T19:55:54.7658529Z callback might be invoked while the async kernels that are populating 2025-08-26T19:55:54.7659106Z those tensors haven't yet finished executing on the device. However, the 2025-08-26T19:55:54.7659677Z callback will be invoked with some dedicated streams set as current 2025-08-26T19:55:54.7660207Z (fetched from a global pool) which will be synchronized with those 2025-08-26T19:55:54.7660771Z kernels. Hence any operation performed by the callback on these tensors 2025-08-26T19:55:54.7661336Z will be scheduled on the device after the kernels complete. In other 2025-08-26T19:55:54.7661870Z words, as long as the callback doesn't switch streams, it can safely 2025-08-26T19:55:54.7662415Z manipulate the result without any additional synchronization. This is 2025-08-26T19:55:54.7662940Z similar to the non-blocking behavior of :meth:`wait`. 2025-08-26T19:55:54.7663230Z 2025-08-26T19:55:54.7663446Z Similarly, if the callback returns a value that contains tensors that 2025-08-26T19:55:54.7663981Z reside on a GPU, it can do so even if the kernels that are producing 2025-08-26T19:55:54.7664520Z these tensors are still running on the device, as long as the callback 2025-08-26T19:55:54.7665062Z didn't change streams during its execution. If one wants to change 2025-08-26T19:55:54.7665604Z streams, one must be careful to re-synchronize them with the original 2025-08-26T19:55:54.7666165Z streams, that is, those that were current when the callback was invoked. 2025-08-26T19:55:54.7666506Z 2025-08-26T19:55:54.7666604Z Args: 2025-08-26T19:55:54.7666928Z callback(``Callable``): a ``Callable`` that takes this ``Future`` as 2025-08-26T19:55:54.7667377Z the only argument. 2025-08-26T19:55:54.7667615Z 2025-08-26T19:55:54.7667705Z Returns: 2025-08-26T19:55:54.7668000Z A new ``Future`` object that holds the return value of the 2025-08-26T19:55:54.7668481Z ``callback`` and will be marked as completed when the given 2025-08-26T19:55:54.7668871Z ``callback`` finishes. 2025-08-26T19:55:54.7669060Z 2025-08-26T19:55:54.7669252Z .. note:: Note that if the callback function throws, either 2025-08-26T19:55:54.7669757Z through the original future being completed with an exception and 2025-08-26T19:55:54.7670291Z calling ``fut.wait()``, or through other code in the callback, the 2025-08-26T19:55:54.7670809Z future returned by ``then`` will be marked appropriately with the 2025-08-26T19:55:54.7671343Z encountered error. However, if this callback later completes 2025-08-26T19:55:54.7671887Z additional futures, those futures are not marked as completed with 2025-08-26T19:55:54.7672442Z an error and the user is responsible for handling completion/waiting 2025-08-26T19:55:54.7672892Z on those futures independently. 2025-08-26T19:55:54.7673108Z 2025-08-26T19:55:54.7673201Z Example:: 2025-08-26T19:55:54.7673338Z 2025-08-26T19:55:54.7673555Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T19:55:54.7673924Z >>> def callback(fut): 2025-08-26T19:55:54.7674252Z ... print(f"RPC return value is {fut.wait()}.") 2025-08-26T19:55:54.7674618Z >>> fut = torch.futures.Future() 2025-08-26T19:55:54.7675016Z >>> # The inserted callback will print the return value when 2025-08-26T19:55:54.7675442Z >>> # receiving the response from "worker1" 2025-08-26T19:55:54.7675793Z >>> cb_fut = fut.then(callback) 2025-08-26T19:55:54.7676099Z >>> chain_cb_fut = cb_fut.then( 2025-08-26T19:55:54.7676517Z ... lambda x : print(f"Chained cb done. {x.wait()}") 2025-08-26T19:55:54.7676876Z ... ) 2025-08-26T19:55:54.7677101Z >>> fut.set_result(5) 2025-08-26T19:55:54.7677366Z RPC return value is 5. 2025-08-26T19:55:54.7677648Z Chained cb done. None 2025-08-26T19:55:54.7677831Z 2025-08-26T19:55:54.7678087Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.7678468Z 2025-08-26T19:55:54.7679045Z msg = Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=211. 2025-08-26T19:55:54.7679969Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.7680354Z 2025-08-26T19:55:54.7680575Z Set the result for this ``Future``, which will mark this ``Future`` as 2025-08-26T19:55:54.7681111Z completed and trigger all attached callbacks. Note that a ``Future`` 2025-08-26T19:55:54.7681576Z cannot be marked completed twice. 2025-08-26T19:55:54.7681798Z 2025-08-26T19:55:54.7682019Z If the result contains tensors that reside on GPUs, this method can be 2025-08-26T19:55:54.7682578Z called even if the asynchronous kernels that are populating those 2025-08-26T19:55:54.7683119Z tensors haven't yet completed running on the device, provided that the 2025-08-26T19:55:54.7683692Z streams on which those kernels were enqueued are set as the current ones 2025-08-26T19:55:54.7684263Z when this method is called. Put simply, it's safe to call this method 2025-08-26T19:55:54.7684817Z immediately after launching those kernels, without any additional 2025-08-26T19:55:54.7685390Z synchronization, as long as one doesn't change streams in between. This 2025-08-26T19:55:54.7685955Z method will record events on all the relevant current streams and will 2025-08-26T19:55:54.7686507Z use them to ensure proper scheduling for all the consumers of this 2025-08-26T19:55:54.7686924Z ``Future``. 2025-08-26T19:55:54.7687050Z 2025-08-26T19:55:54.7687149Z Args: 2025-08-26T19:55:54.7687422Z result (object): the result object of this ``Future``. 2025-08-26T19:55:54.7687714Z 2025-08-26T19:55:54.7687806Z Example:: 2025-08-26T19:55:54.7687941Z 2025-08-26T19:55:54.7688090Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T19:55:54.7688463Z >>> import threading 2025-08-26T19:55:54.7688718Z >>> import time 2025-08-26T19:55:54.7689065Z >>> def slow_set_future(fut, value): 2025-08-26T19:55:54.7689399Z ... time.sleep(0.5) 2025-08-26T19:55:54.7689688Z ... fut.set_result(value) 2025-08-26T19:55:54.7689990Z >>> fut = torch.futures.Future() 2025-08-26T19:55:54.7690310Z >>> t = threading.Thread( 2025-08-26T19:55:54.7690606Z ... target=slow_set_future, 2025-08-26T19:55:54.7690924Z ... args=(fut, torch.ones(2) * 3) 2025-08-26T19:55:54.7691221Z ... ) 2025-08-26T19:55:54.7691430Z >>> t.start() 2025-08-26T19:55:54.7691674Z >>> print(fut.wait()) 2025-08-26T19:55:54.7691950Z tensor([3., 3.]) 2025-08-26T19:55:54.7692184Z >>> t.join() 2025-08-26T19:55:54.7692337Z 2025-08-26T19:55:54.7692594Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.7692985Z 2025-08-26T19:55:54.7772088Z msg = Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/mps/__init__.py line=145. 2025-08-26T19:55:54.7773008Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.7773765Z Compiles compute shader from source and allows one to invoke kernels 2025-08-26T19:55:54.7774268Z defined there from the comfort of Python runtime 2025-08-26T19:55:54.7774628Z Example:: 2025-08-26T19:55:54.7774778Z 2025-08-26T19:55:54.7774919Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS) 2025-08-26T19:55:54.7775300Z >>> lib = torch.mps.compile_shader( 2025-08-26T19:55:54.7776004Z ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }" 2025-08-26T19:55:54.7776590Z ... ) 2025-08-26T19:55:54.7776855Z >>> x = torch.zeros(16, device="mps") 2025-08-26T19:55:54.7777195Z >>> lib.full(x, 3.14) 2025-08-26T19:55:54.7777469Z 2025-08-26T19:55:54.7777833Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.7778227Z 2025-08-26T19:55:54.7953156Z msg = Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=202. 2025-08-26T19:55:54.7954042Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.7954608Z Return the sum of each row of the given sparse tensor. 2025-08-26T19:55:54.7954883Z 2025-08-26T19:55:54.7955126Z Returns the sum of each row of the sparse tensor :attr:`input` in the given 2025-08-26T19:55:54.7955691Z dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions, 2025-08-26T19:55:54.7956223Z reduce over all of them. When sum over all ``sparse_dim``, this method 2025-08-26T19:55:54.7956718Z returns a dense tensor instead of a sparse tensor. 2025-08-26T19:55:54.7956999Z 2025-08-26T19:55:54.7957260Z All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output 2025-08-26T19:55:54.7957849Z tensor having :attr:`dim` fewer dimensions than :attr:`input`. 2025-08-26T19:55:54.7958160Z 2025-08-26T19:55:54.7958400Z During backward, only gradients at ``nnz`` locations of :attr:`input` 2025-08-26T19:55:54.7958980Z will propagate back. Note that the gradients of :attr:`input` is coalesced. 2025-08-26T19:55:54.7959354Z 2025-08-26T19:55:54.7959438Z Args: 2025-08-26T19:55:54.7959694Z input (Tensor): the input sparse tensor 2025-08-26T19:55:54.7960217Z dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce 2025-08-26T19:55:54.7960707Z over all dims. 2025-08-26T19:55:54.7961150Z dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor. 2025-08-26T19:55:54.7961665Z Default: dtype of :attr:`input`. 2025-08-26T19:55:54.7961893Z 2025-08-26T19:55:54.7962004Z Example:: 2025-08-26T19:55:54.7962136Z 2025-08-26T19:55:54.7962238Z >>> nnz = 3 2025-08-26T19:55:54.7962471Z >>> dims = [5, 5, 2, 3] 2025-08-26T19:55:54.7962827Z >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)), 2025-08-26T19:55:54.7963305Z torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz) 2025-08-26T19:55:54.7963748Z >>> V = torch.randn(nnz, dims[2], dims[3]) 2025-08-26T19:55:54.7964084Z >>> size = torch.Size(dims) 2025-08-26T19:55:54.7964442Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:55:54.7964836Z >>> S = torch.sparse_coo_tensor(I, V, size) 2025-08-26T19:55:54.7965171Z >>> S 2025-08-26T19:55:54.7965406Z tensor(indices=tensor([[2, 0, 3], 2025-08-26T19:55:54.7965737Z [2, 4, 1]]), 2025-08-26T19:55:54.7966104Z values=tensor([[[-0.6438, -1.6467, 1.4004], 2025-08-26T19:55:54.7966475Z [ 0.3411, 0.0918, -0.2312]], 2025-08-26T19:55:54.7966704Z 2025-08-26T19:55:54.7966831Z [[ 0.5348, 0.0634, -2.0494], 2025-08-26T19:55:54.7967169Z [-0.7125, -1.0646, 2.1844]], 2025-08-26T19:55:54.7967551Z 2025-08-26T19:55:54.7967665Z [[ 0.1276, 0.1874, -0.6334], 2025-08-26T19:55:54.7968018Z [-1.9682, -0.5340, 0.7483]]]), 2025-08-26T19:55:54.7968407Z size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo) 2025-08-26T19:55:54.7968671Z 2025-08-26T19:55:54.7968950Z # when sum over only part of sparse_dims, return a sparse tensor 2025-08-26T19:55:54.7969393Z >>> torch.sparse.sum(S, [1, 3]) 2025-08-26T19:55:54.7969736Z tensor(indices=tensor([[0, 2, 3]]), 2025-08-26T19:55:54.7970167Z values=tensor([[-1.4512, 0.4073], 2025-08-26T19:55:54.7970513Z [-0.8901, 0.2017], 2025-08-26T19:55:54.7970832Z [-0.3183, -1.7539]]), 2025-08-26T19:55:54.7971203Z size=(5, 2), nnz=3, layout=torch.sparse_coo) 2025-08-26T19:55:54.7971456Z 2025-08-26T19:55:54.7971626Z # when sum over all sparse dim, return a dense tensor 2025-08-26T19:55:54.7972020Z # with summed dims squeezed 2025-08-26T19:55:54.7972337Z >>> torch.sparse.sum(S, [0, 1, 3]) 2025-08-26T19:55:54.7972666Z tensor([-2.6596, -1.1450]) 2025-08-26T19:55:54.7972953Z 2025-08-26T19:55:54.7973328Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.7973710Z 2025-08-26T19:55:54.7974290Z msg = Cannot scrape callname=as_sparse_gradcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=550. 2025-08-26T19:55:54.7975209Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:54.7975788Z Decorate function, to extend gradcheck for sparse tensors. 2025-08-26T19:55:54.7976098Z 2025-08-26T19:55:54.7976315Z Decorator for torch.autograd.gradcheck or its functools.partial 2025-08-26T19:55:54.7976875Z variants that extends the gradcheck function with support to input 2025-08-26T19:55:54.7977394Z functions that operate on or/and return sparse tensors. 2025-08-26T19:55:54.7977685Z 2025-08-26T19:55:54.7977898Z The specified gradcheck function itself is guaranteed to operate 2025-08-26T19:55:54.7978338Z on strided tensors only. 2025-08-26T19:55:54.7978534Z 2025-08-26T19:55:54.7978624Z For example: 2025-08-26T19:55:54.7978765Z 2025-08-26T19:55:54.7979020Z >>> gradcheck = torch.sparse.as_sparse_gradcheck(torch.autograd.gradcheck) 2025-08-26T19:55:54.7979461Z >>> x = ( 2025-08-26T19:55:54.7979759Z ... torch.tensor([[0, 1], [2, 3]], dtype=torch.float64) 2025-08-26T19:55:54.7980143Z ... .to_sparse_coo() 2025-08-26T19:55:54.7980440Z ... .requires_grad_(True) 2025-08-26T19:55:54.7980720Z ... ) 2025-08-26T19:55:54.7980983Z >>> gradcheck(lambda x: x.to_sparse_csr(), x) 2025-08-26T19:55:54.7981324Z True 2025-08-26T19:55:54.7981536Z 2025-08-26T19:55:54.7981899Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:54.7982287Z 2025-08-26T19:55:55.7763163Z msg = Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=39. 2025-08-26T19:55:55.7764362Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:55.7764772Z 2025-08-26T19:55:55.7764997Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-08-26T19:55:55.7765596Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-08-26T19:55:55.7766148Z pushes the map into PyTorch operations called by ``func``, effectively 2025-08-26T19:55:55.7766632Z vectorizing those operations. 2025-08-26T19:55:55.7766828Z 2025-08-26T19:55:55.7767063Z vmap is useful for handling batch dimensions: one can write a function 2025-08-26T19:55:55.7767614Z ``func`` that runs on examples and then lift it to a function that can 2025-08-26T19:55:55.7768150Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-08-26T19:55:55.7768670Z compute batched gradients when composed with autograd. 2025-08-26T19:55:55.7769258Z 2025-08-26T19:55:55.7769382Z .. note:: 2025-08-26T19:55:55.7769707Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-08-26T19:55:55.7770144Z convenience. Use whichever one you'd like. 2025-08-26T19:55:55.7770404Z 2025-08-26T19:55:55.7770489Z Args: 2025-08-26T19:55:55.7770833Z func (function): A Python function that takes one or more arguments. 2025-08-26T19:55:55.7771292Z Must return one or more Tensors. 2025-08-26T19:55:55.7771816Z in_dims (int or nested structure): Specifies which dimension of the 2025-08-26T19:55:55.7772325Z inputs should be mapped over. ``in_dims`` should have a 2025-08-26T19:55:55.7772825Z structure like the inputs. If the ``in_dim`` for a particular 2025-08-26T19:55:55.7773535Z input is None, then that indicates there is no map dimension. 2025-08-26T19:55:55.7774002Z Default: 0. 2025-08-26T19:55:55.7774342Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-08-26T19:55:55.7775211Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-08-26T19:55:55.7775969Z it should have one element per output. Default: 0. 2025-08-26T19:55:55.7776435Z randomness (str): Specifies whether the randomness in this 2025-08-26T19:55:55.7776950Z vmap should be the same or different across batches. If 'different', 2025-08-26T19:55:55.7777492Z the randomness for each batch will be different. If 'same', the 2025-08-26T19:55:55.7778054Z randomness will be the same across batches. If 'error', any calls to 2025-08-26T19:55:55.7778613Z random functions will error. Default: 'error'. WARNING: this flag 2025-08-26T19:55:55.7779163Z only applies to random PyTorch operations and does not apply to 2025-08-26T19:55:55.7779618Z Python's random module or numpy randomness. 2025-08-26T19:55:55.7780106Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-08-26T19:55:55.7780695Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-08-26T19:55:55.7781306Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-08-26T19:55:55.7781956Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-08-26T19:55:55.7782363Z 2025-08-26T19:55:55.7782453Z Returns: 2025-08-26T19:55:55.7782773Z Returns a new "batched" function. It takes the same inputs as 2025-08-26T19:55:55.7783277Z ``func``, except each input has an extra dimension at the index 2025-08-26T19:55:55.7783782Z specified by ``in_dims``. It takes returns the same outputs as 2025-08-26T19:55:55.7784275Z ``func``, except each output has an extra dimension at the index 2025-08-26T19:55:55.7784744Z specified by ``out_dims``. 2025-08-26T19:55:55.7784946Z 2025-08-26T19:55:55.7785034Z .. warning: 2025-08-26T19:55:55.7785371Z :func:`vmap` works best with functional-style code. Please do not 2025-08-26T19:55:55.7785880Z perform any side-effects in ``func``, with the exception of 2025-08-26T19:55:55.7786437Z in-place PyTorch operations. Examples of side-effects include mutating 2025-08-26T19:55:55.7787034Z Python data structures and assigning values to variables not captured 2025-08-26T19:55:55.7787480Z in ``func``. 2025-08-26T19:55:55.7787621Z 2025-08-26T19:55:55.7787874Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-08-26T19:55:55.7788449Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-08-26T19:55:55.7789025Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-08-26T19:55:55.7789377Z 2025-08-26T19:55:55.7789500Z >>> torch.dot # [D], [D] -> [] 2025-08-26T19:55:55.7789923Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-08-26T19:55:55.7790373Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T19:55:55.7790720Z >>> batched_dot(x, y) 2025-08-26T19:55:55.7791027Z 2025-08-26T19:55:55.7791258Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-08-26T19:55:55.7791730Z model authoring experience. 2025-08-26T19:55:55.7791914Z 2025-08-26T19:55:55.7792041Z >>> batch_size, feature_size = 3, 5 2025-08-26T19:55:55.7792429Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T19:55:55.7792813Z >>> 2025-08-26T19:55:55.7793041Z >>> def model(feature_vec): 2025-08-26T19:55:55.7793371Z >>> # Very simple linear model with activation 2025-08-26T19:55:55.7793800Z >>> return feature_vec.dot(weights).relu() 2025-08-26T19:55:55.7794135Z >>> 2025-08-26T19:55:55.7794411Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T19:55:55.7794805Z >>> result = torch.vmap(model)(examples) 2025-08-26T19:55:55.7795034Z 2025-08-26T19:55:55.7795288Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-08-26T19:55:55.7795909Z or impossible to batch. One example is higher-order gradient computation. 2025-08-26T19:55:55.7796509Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-08-26T19:55:55.7797094Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-08-26T19:55:55.7797689Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-08-26T19:55:55.7798304Z we can vectorize the whole computation, computing the Jacobian in a single 2025-08-26T19:55:55.7798773Z call to ``autograd.grad``. 2025-08-26T19:55:55.7798951Z 2025-08-26T19:55:55.7799049Z >>> # Setup 2025-08-26T19:55:55.7799286Z >>> N = 5 2025-08-26T19:55:55.7799509Z >>> f = lambda x: x**2 2025-08-26T19:55:55.7799810Z >>> x = torch.randn(N, requires_grad=True) 2025-08-26T19:55:55.7800137Z >>> y = f(x) 2025-08-26T19:55:55.7800383Z >>> I_N = torch.eye(N) 2025-08-26T19:55:55.7800636Z >>> 2025-08-26T19:55:55.7800869Z >>> # Sequential approach 2025-08-26T19:55:55.7801415Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-08-26T19:55:55.7801888Z >>> for v in I_N.unbind()] 2025-08-26T19:55:55.7802233Z >>> jacobian = torch.stack(jacobian_rows) 2025-08-26T19:55:55.7802560Z >>> 2025-08-26T19:55:55.7802802Z >>> # vectorized gradient computation 2025-08-26T19:55:55.7803129Z >>> def get_vjp(v): 2025-08-26T19:55:55.7803408Z >>> return torch.autograd.grad(y, x, v) 2025-08-26T19:55:55.7803771Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-08-26T19:55:55.7804001Z 2025-08-26T19:55:55.7804289Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-08-26T19:55:55.7812665Z 2025-08-26T19:55:55.7812855Z >>> torch.dot # [D], [D] -> [] 2025-08-26T19:55:55.7813213Z >>> batched_dot = torch.vmap( 2025-08-26T19:55:55.7813540Z ... torch.vmap(torch.dot) 2025-08-26T19:55:55.7813860Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-08-26T19:55:55.7814249Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-08-26T19:55:55.7814658Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-08-26T19:55:55.7814901Z 2025-08-26T19:55:55.7815162Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-08-26T19:55:55.7815694Z the dimension that each inputs are batched along as 2025-08-26T19:55:55.7815962Z 2025-08-26T19:55:55.7816072Z >>> torch.dot # [N], [N] -> [] 2025-08-26T19:55:55.7816509Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-08-26T19:55:55.7816998Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T19:55:55.7817339Z >>> batched_dot( 2025-08-26T19:55:55.7817576Z ... x, y 2025-08-26T19:55:55.7817918Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-08-26T19:55:55.7818242Z 2025-08-26T19:55:55.7818507Z If there are multiple inputs each of which is batched along different dimensions, 2025-08-26T19:55:55.7819105Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-08-26T19:55:55.7819551Z 2025-08-26T19:55:55.7819673Z >>> torch.dot # [D], [D] -> [] 2025-08-26T19:55:55.7820118Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-08-26T19:55:55.7820614Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T19:55:55.7820957Z >>> batched_dot( 2025-08-26T19:55:55.7821209Z ... x, y 2025-08-26T19:55:55.7821537Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-08-26T19:55:55.7821866Z 2025-08-26T19:55:55.7822175Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-08-26T19:55:55.7822658Z matching the shape of the input: 2025-08-26T19:55:55.7822861Z 2025-08-26T19:55:55.7823017Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-08-26T19:55:55.7823389Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T19:55:55.7823730Z >>> input = {"x": x, "y": y} 2025-08-26T19:55:55.7824110Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-08-26T19:55:55.7824518Z >>> batched_dot(input) 2025-08-26T19:55:55.7824697Z 2025-08-26T19:55:55.7824985Z By default, the output is batched along the first dimension. However, it can be batched 2025-08-26T19:55:55.7825504Z along any dimension by using ``out_dims`` 2025-08-26T19:55:55.7825750Z 2025-08-26T19:55:55.7825847Z >>> f = lambda x: x**2 2025-08-26T19:55:55.7826127Z >>> x = torch.randn(2, 5) 2025-08-26T19:55:55.7826488Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-08-26T19:55:55.7826856Z >>> batched_pow(x) # [5, 2] 2025-08-26T19:55:55.7827061Z 2025-08-26T19:55:55.7827361Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-08-26T19:55:55.7827884Z accept kwargs 2025-08-26T19:55:55.7828021Z 2025-08-26T19:55:55.7828137Z >>> x = torch.randn([2, 5]) 2025-08-26T19:55:55.7828418Z >>> def fn(x, scale=4.): 2025-08-26T19:55:55.7828710Z >>> return x * scale 2025-08-26T19:55:55.7828979Z >>> 2025-08-26T19:55:55.7829220Z >>> batched_pow = torch.vmap(fn) 2025-08-26T19:55:55.7829575Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-08-26T19:55:55.7830070Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-08-26T19:55:55.7830432Z 2025-08-26T19:55:55.7830544Z .. note:: 2025-08-26T19:55:55.7830898Z vmap does not provide general autobatching or handle variable-length 2025-08-26T19:55:55.7831350Z sequences out of the box. 2025-08-26T19:55:55.7831539Z 2025-08-26T19:55:55.7831801Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:55.7832194Z 2025-08-26T19:55:55.7832723Z msg = Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=306. 2025-08-26T19:55:55.7833602Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:55.7834236Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-08-26T19:55:55.7834810Z input(s) specified by ``argnums``. This operator can be nested to 2025-08-26T19:55:55.7835247Z compute higher-order gradients. 2025-08-26T19:55:55.7835460Z 2025-08-26T19:55:55.7835545Z Args: 2025-08-26T19:55:55.7835885Z func (Callable): A Python function that takes one or more arguments. 2025-08-26T19:55:55.7836493Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-08-26T19:55:55.7837162Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-08-26T19:55:55.7837997Z ``(output, aux)``. 2025-08-26T19:55:55.7838474Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-08-26T19:55:55.7839097Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-08-26T19:55:55.7839656Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-08-26T19:55:55.7840317Z auxiliary objects: ``(output, aux)``. Default: False. 2025-08-26T19:55:55.7840602Z 2025-08-26T19:55:55.7840689Z Returns: 2025-08-26T19:55:55.7841118Z Function to compute gradients with respect to its inputs. By default, the output of 2025-08-26T19:55:55.7841777Z the function is the gradient tensor(s) with respect to the first argument. 2025-08-26T19:55:55.7842420Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-08-26T19:55:55.7843164Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-08-26T19:55:55.7843685Z respect to each ``argnums`` value is returned. 2025-08-26T19:55:55.7843955Z 2025-08-26T19:55:55.7844063Z Example of using ``grad``: 2025-08-26T19:55:55.7844265Z 2025-08-26T19:55:55.7844371Z >>> # xdoctest: +SKIP 2025-08-26T19:55:55.7844679Z >>> from torch.func import grad 2025-08-26T19:55:55.7845000Z >>> x = torch.randn([]) 2025-08-26T19:55:55.7845329Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-08-26T19:55:55.7845704Z >>> assert torch.allclose(cos_x, x.cos()) 2025-08-26T19:55:55.7846041Z >>> 2025-08-26T19:55:55.7846265Z >>> # Second-order gradients 2025-08-26T19:55:55.7846632Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-08-26T19:55:55.7847044Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-08-26T19:55:55.7847291Z 2025-08-26T19:55:55.7847555Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-08-26T19:55:55.7847934Z 2025-08-26T19:55:55.7848046Z >>> # xdoctest: +SKIP 2025-08-26T19:55:55.7848344Z >>> from torch.func import grad, vmap 2025-08-26T19:55:55.7848696Z >>> batch_size, feature_size = 3, 5 2025-08-26T19:55:55.7849098Z >>> 2025-08-26T19:55:55.7849348Z >>> def model(weights, feature_vec): 2025-08-26T19:55:55.7849706Z >>> # Very simple linear model with activation 2025-08-26T19:55:55.7850080Z >>> assert feature_vec.dim() == 1 2025-08-26T19:55:55.7850447Z >>> return feature_vec.dot(weights).relu() 2025-08-26T19:55:55.7850786Z >>> 2025-08-26T19:55:55.7851042Z >>> def compute_loss(weights, example, target): 2025-08-26T19:55:55.7851408Z >>> y = model(weights, example) 2025-08-26T19:55:55.7851771Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-08-26T19:55:55.7852114Z >>> 2025-08-26T19:55:55.7852405Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T19:55:55.7852866Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T19:55:55.7853260Z >>> targets = torch.randn(batch_size) 2025-08-26T19:55:55.7853619Z >>> inputs = (weights, examples, targets) 2025-08-26T19:55:55.7854087Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-08-26T19:55:55.7854547Z ... *inputs 2025-08-26T19:55:55.7854796Z ... ) 2025-08-26T19:55:55.7854928Z 2025-08-26T19:55:55.7855118Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-08-26T19:55:55.7855414Z 2025-08-26T19:55:55.7855529Z >>> # xdoctest: +SKIP 2025-08-26T19:55:55.7855821Z >>> from torch.func import grad 2025-08-26T19:55:55.7856163Z >>> def my_loss_func(y, y_pred): 2025-08-26T19:55:55.7856523Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-08-26T19:55:55.7856894Z >>> loss = loss_per_sample.mean() 2025-08-26T19:55:55.7857248Z >>> return loss, (y_pred, loss_per_sample) 2025-08-26T19:55:55.7857630Z >>> 2025-08-26T19:55:55.7857915Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-08-26T19:55:55.7858300Z >>> y_true = torch.rand(4) 2025-08-26T19:55:55.7858634Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-08-26T19:55:55.7858998Z >>> out = fn(y_true, y_preds) 2025-08-26T19:55:55.7859463Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-08-26T19:55:55.7859917Z 2025-08-26T19:55:55.7860027Z .. note:: 2025-08-26T19:55:55.7860329Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-08-26T19:55:55.7860634Z 2025-08-26T19:55:55.7860785Z Case 1: Using ``torch.no_grad`` inside a function: 2025-08-26T19:55:55.7861064Z 2025-08-26T19:55:55.7861168Z >>> # xdoctest: +SKIP 2025-08-26T19:55:55.7861465Z >>> def f(x): 2025-08-26T19:55:55.7861751Z >>> with torch.no_grad(): 2025-08-26T19:55:55.7862133Z >>> c = x ** 2 2025-08-26T19:55:55.7862432Z >>> return x - c 2025-08-26T19:55:55.7862619Z 2025-08-26T19:55:55.7862830Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-08-26T19:55:55.7863150Z 2025-08-26T19:55:55.7863354Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-08-26T19:55:55.7863659Z 2025-08-26T19:55:55.7863776Z >>> # xdoctest: +SKIP 2025-08-26T19:55:55.7864080Z >>> with torch.no_grad(): 2025-08-26T19:55:55.7864395Z >>> grad(f)(x) 2025-08-26T19:55:55.7864573Z 2025-08-26T19:55:55.7864813Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-08-26T19:55:55.7865390Z outer one. This is because ``grad`` is a "function transform": its result 2025-08-26T19:55:55.7865949Z should not depend on the result of a context manager outside of ``f``. 2025-08-26T19:55:55.7866303Z 2025-08-26T19:55:55.7866386Z 2025-08-26T19:55:55.7866766Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:55.7867141Z 2025-08-26T19:55:57.7101107Z msg = Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py line=397. 2025-08-26T19:55:57.7102123Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:57.7102714Z Register a FakeTensor implementation for this custom op. 2025-08-26T19:55:57.7103010Z 2025-08-26T19:55:57.7103276Z This is necessary to get the operator to work efficiently with torch.compile. 2025-08-26T19:55:57.7103652Z 2025-08-26T19:55:57.7103890Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-08-26T19:55:57.7104464Z specifies the behavior of this operator on Tensors that carry no data. 2025-08-26T19:55:57.7104982Z Given some input Tensors with certain properties 2025-08-26T19:55:57.7105529Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-08-26T19:55:57.7106024Z the output Tensors are. 2025-08-26T19:55:57.7106215Z 2025-08-26T19:55:57.7106424Z Please see :func:`torch.library.register_fake` for more details. 2025-08-26T19:55:57.7106760Z 2025-08-26T19:55:57.7106847Z Args: 2025-08-26T19:55:57.7107159Z fn (Callable): The function to register as the FakeTensor 2025-08-26T19:55:57.7107565Z implementation. 2025-08-26T19:55:57.7107751Z 2025-08-26T19:55:57.7107853Z Examples: 2025-08-26T19:55:57.7108088Z >>> import torch 2025-08-26T19:55:57.7108380Z >>> import numpy as np 2025-08-26T19:55:57.7108700Z >>> from torch import Tensor 2025-08-26T19:55:57.7109010Z >>> 2025-08-26T19:55:57.7109336Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T19:55:57.7109878Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-08-26T19:55:57.7110401Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T19:55:57.7110845Z >>> return (x @ weight.t()) + bias 2025-08-26T19:55:57.7111160Z >>> 2025-08-26T19:55:57.7111412Z >>> @linear.register_fake 2025-08-26T19:55:57.7111737Z >>> def _(x, weight, bias): 2025-08-26T19:55:57.7112060Z >>> assert x.dim() == 2 2025-08-26T19:55:57.7112625Z >>> assert weight.dim() == 2 2025-08-26T19:55:57.7112971Z >>> assert bias.dim() == 1 2025-08-26T19:55:57.7113333Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T19:55:57.7113725Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T19:55:57.7114101Z >>> assert x.device == weight.device 2025-08-26T19:55:57.7114501Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-08-26T19:55:57.7114889Z >>> 2025-08-26T19:55:57.7115232Z >>> x = torch.randn(2, 2) 2025-08-26T19:55:57.7115567Z >>> weight = torch.randn(2, 2) 2025-08-26T19:55:57.7115888Z >>> bias = torch.randn(2) 2025-08-26T19:55:57.7116247Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:55:57.7116710Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-08-26T19:55:57.7117175Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:55:57.7117681Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-08-26T19:55:57.7118149Z >>> 2025-08-26T19:55:57.7118472Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T19:55:57.7118981Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-08-26T19:55:57.7119425Z >>> def nonzero(x: Tensor) -> Tensor: 2025-08-26T19:55:57.7119760Z >>> x_np = x.cpu().numpy() 2025-08-26T19:55:57.7120125Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T19:55:57.7120520Z >>> return torch.tensor(res, device=x.device) 2025-08-26T19:55:57.7120862Z >>> 2025-08-26T19:55:57.7121102Z >>> @nonzero.register_fake 2025-08-26T19:55:57.7121415Z >>> def _(x): 2025-08-26T19:55:57.7121739Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T19:55:57.7122187Z >>> # Since we cannot peek at the data in an abstract impl, 2025-08-26T19:55:57.7122638Z >>> # we use the ctx object to construct a new symint that 2025-08-26T19:55:57.7123056Z >>> # represents the data-dependent size. 2025-08-26T19:55:57.7123428Z >>> ctx = torch.library.get_ctx() 2025-08-26T19:55:57.7123790Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T19:55:57.7124123Z >>> shape = [nnz, x.dim()] 2025-08-26T19:55:57.7124497Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T19:55:57.7124875Z >>> return result 2025-08-26T19:55:57.7125163Z >>> 2025-08-26T19:55:57.7125414Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-08-26T19:55:57.7125793Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:55:57.7126206Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-08-26T19:55:57.7126622Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:55:57.7127025Z >>> assert torch.allclose(out, x.nonzero()) 2025-08-26T19:55:57.7127271Z 2025-08-26T19:55:57.7127357Z 2025-08-26T19:55:57.7128023Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-08-26T19:55:57.7128687Z 2025-08-26T19:55:57.7128773Z _._ = None 2025-08-26T19:55:57.7129076Z ^ 2025-08-26T19:55:57.7246946Z msg = Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_profile.py line=94. 2025-08-26T19:55:57.7247978Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.7248378Z 2025-08-26T19:55:57.7248615Z Registers a fake kernel based on the given operator profiles. This fake 2025-08-26T19:55:57.7249287Z kernel registration will override any existing fake kernel registrations. 2025-08-26T19:55:57.7249657Z 2025-08-26T19:55:57.7249886Z The input is a dictionary mapping operator names to a set of operator 2025-08-26T19:55:57.7250648Z profiles, which we will use to generate fake kernels. The operator profiles 2025-08-26T19:55:57.7251209Z are a record of the input and output tensor metadata. Based on this 2025-08-26T19:55:57.7251787Z information we will match a given input to the recorded profile, and return 2025-08-26T19:55:57.7252394Z an output with the same metadata as in the recorded profile. If a profile 2025-08-26T19:55:57.7252901Z doesn't exist then an exception will be thrown. 2025-08-26T19:55:57.7253158Z 2025-08-26T19:55:57.7253483Z The fake kernel generation is considered unsafe because it relies on the 2025-08-26T19:55:57.7254080Z rigid, pre-defined operator profiles that do not account for potential 2025-08-26T19:55:57.7254696Z variations in output behavior. Specifically, the generated kernels assume a 2025-08-26T19:55:57.7255370Z fixed relationship between input and output ranks. However, in reality, it's 2025-08-26T19:55:57.7256015Z possible that data-dependent operations may produce outputs of different 2025-08-26T19:55:57.7256598Z ranks even when given inputs of the same rank. The generated fake kernels 2025-08-26T19:55:57.7257170Z are inflexible and unable to accommodate these nuances, making them 2025-08-26T19:55:57.7257609Z potentially unsafe. 2025-08-26T19:55:57.7257761Z 2025-08-26T19:55:57.7257860Z Args: 2025-08-26T19:55:57.7258191Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-08-26T19:55:57.7258751Z name to a set of operator profiles from which we will generate fake 2025-08-26T19:55:57.7259166Z kernels. 2025-08-26T19:55:57.7259304Z 2025-08-26T19:55:57.7259405Z Examples: 2025-08-26T19:55:57.7259529Z 2025-08-26T19:55:57.7259729Z >>> # Example: Registering an op-profile from draft-export 2025-08-26T19:55:57.7260099Z >>> import torch 2025-08-26T19:55:57.7260424Z >>> from torch.export._draft_export import draft_export 2025-08-26T19:55:57.7260794Z >>> 2025-08-26T19:55:57.7261116Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-08-26T19:55:57.7261535Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T19:55:57.7261883Z >>> return x + y 2025-08-26T19:55:57.7262137Z >>> 2025-08-26T19:55:57.7262363Z >>> class M(torch.nn.Module): 2025-08-26T19:55:57.7262682Z >>> def forward(self, a, b): 2025-08-26T19:55:57.7263047Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-08-26T19:55:57.7263411Z >>> return res 2025-08-26T19:55:57.7263655Z >>> 2025-08-26T19:55:57.7263953Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-08-26T19:55:57.7264330Z >>> 2025-08-26T19:55:57.7264756Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-08-26T19:55:57.7265311Z >>> decomp = ep.run_decompositions() 2025-08-26T19:55:57.7265541Z 2025-08-26T19:55:57.7265545Z 2025-08-26T19:55:57.7265800Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.7266193Z 2025-08-26T19:55:57.7327555Z msg = Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=96. 2025-08-26T19:55:57.7329047Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.7329697Z Create a custom operator whose implementation is backed by 1+ triton kernels. 2025-08-26T19:55:57.7330072Z 2025-08-26T19:55:57.7330295Z This is a more structured way of using triton kernels with PyTorch. 2025-08-26T19:55:57.7330887Z Prefer using triton kernels with no ``torch.library`` custom operator wrappers 2025-08-26T19:55:57.7331529Z (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because 2025-08-26T19:55:57.7332134Z that is simpler; 2025-08-26T19:55:57.7332545Z only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you 2025-08-26T19:55:57.7333146Z want to create an operator that behaves like PyTorch built-in operators. 2025-08-26T19:55:57.7333805Z For example, you may use a ``torch.library`` wrapper API to define the 2025-08-26T19:55:57.7334351Z behavior of the triton kernel when passed a tensor subclass or under 2025-08-26T19:55:57.7334790Z a TorchDispatchMode. 2025-08-26T19:55:57.7334959Z 2025-08-26T19:55:57.7335227Z Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op` 2025-08-26T19:55:57.7335691Z when the implementation 2025-08-26T19:55:57.7336286Z consists of 1+ triton kernels. :func:`torch.library.custom_op` treats 2025-08-26T19:55:57.7337083Z custom operators as opaque (:func:`torch.compile` and 2025-08-26T19:55:57.7338128Z :func:`torch.export.export` will never trace into them), but ``triton_op`` 2025-08-26T19:55:57.7338726Z makes the implementation visible to these subsystems, allowing them 2025-08-26T19:55:57.7339198Z to optimize the triton kernel(s). 2025-08-26T19:55:57.7339416Z 2025-08-26T19:55:57.7339614Z Note that ``fn`` must only consist of calls to PyTorch-understood 2025-08-26T19:55:57.7340161Z operators and triton kernels. Any triton kernels called inside ``fn`` 2025-08-26T19:55:57.7340715Z must be wrapped in a call to :func:`torch.library.wrap_triton`. 2025-08-26T19:55:57.7341025Z 2025-08-26T19:55:57.7341124Z Args: 2025-08-26T19:55:57.7341582Z name (str): A name for the custom op that looks like "{namespace}::{name}", 2025-08-26T19:55:57.7342148Z e.g. "mylib::my_linear". The name is used as the op's stable identifier 2025-08-26T19:55:57.7342671Z in PyTorch subsystems (e.g. torch.export, FX graphs). 2025-08-26T19:55:57.7343209Z To avoid name collisions, please use your project name as the namespace; 2025-08-26T19:55:57.7343830Z e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace. 2025-08-26T19:55:57.7344451Z mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates. 2025-08-26T19:55:57.7345106Z This MUST be accurate, otherwise, the behavior is undefined. If "unknown", 2025-08-26T19:55:57.7345753Z it pessimistically assumes that all inputs to the operator are being mutated. 2025-08-26T19:55:57.7346345Z schema (None | str): A schema string for the operator. If None 2025-08-26T19:55:57.7346874Z (recommended) we'll infer a schema for the operator from its type 2025-08-26T19:55:57.7347409Z annotations. We recommend letting us infer a schema unless you 2025-08-26T19:55:57.7347868Z have a specific reason not to. 2025-08-26T19:55:57.7348256Z Example: "(Tensor x, int y) -> (Tensor, Tensor)". 2025-08-26T19:55:57.7348519Z 2025-08-26T19:55:57.7348628Z Example:: 2025-08-26T19:55:57.7348763Z 2025-08-26T19:55:57.7348916Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:55:57.7349262Z >>> import torch 2025-08-26T19:55:57.7349590Z >>> from torch.library import triton_op, wrap_triton 2025-08-26T19:55:57.7349959Z >>> 2025-08-26T19:55:57.7350186Z >>> import triton 2025-08-26T19:55:57.7350469Z >>> from triton import language as tl 2025-08-26T19:55:57.7350794Z >>> 2025-08-26T19:55:57.7351017Z >>> @triton.jit 2025-08-26T19:55:57.7351281Z >>> def add_kernel( 2025-08-26T19:55:57.7351542Z >>> in_ptr0, 2025-08-26T19:55:57.7351798Z >>> in_ptr1, 2025-08-26T19:55:57.7352056Z >>> out_ptr, 2025-08-26T19:55:57.7352314Z >>> n_elements, 2025-08-26T19:55:57.7352597Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T19:55:57.7352911Z >>> ): 2025-08-26T19:55:57.7353164Z >>> pid = tl.program_id(axis=0) 2025-08-26T19:55:57.7353507Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T19:55:57.7353879Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T19:55:57.7354264Z >>> mask = offsets < n_elements 2025-08-26T19:55:57.7354617Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T19:55:57.7355545Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T19:55:57.7355884Z >>> output = x + y 2025-08-26T19:55:57.7356223Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T19:55:57.7356578Z >>> 2025-08-26T19:55:57.7356846Z >>> @triton_op("mylib::add", mutates_args={}) 2025-08-26T19:55:57.7357275Z >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: 2025-08-26T19:55:57.7357703Z >>> output = torch.empty_like(x) 2025-08-26T19:55:57.7358156Z >>> n_elements = output.numel() 2025-08-26T19:55:57.7358475Z >>> 2025-08-26T19:55:57.7358690Z >>> def grid(meta): 2025-08-26T19:55:57.7359057Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T19:55:57.7359441Z >>> 2025-08-26T19:55:57.7359758Z >>> # NB: we need to wrap the triton kernel in a call to wrap_triton 2025-08-26T19:55:57.7360252Z >>> wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16) 2025-08-26T19:55:57.7360671Z >>> return output 2025-08-26T19:55:57.7360948Z >>> 2025-08-26T19:55:57.7361178Z >>> @torch.compile 2025-08-26T19:55:57.7361440Z >>> def f(x, y): 2025-08-26T19:55:57.7361713Z >>> return add(x, y) 2025-08-26T19:55:57.7361993Z >>> 2025-08-26T19:55:57.7362242Z >>> x = torch.randn(3, device="cuda") 2025-08-26T19:55:57.7362583Z >>> y = torch.randn(3, device="cuda") 2025-08-26T19:55:57.7362904Z >>> 2025-08-26T19:55:57.7363121Z >>> z = f(x, y) 2025-08-26T19:55:57.7363400Z >>> assert torch.allclose(z, x + y) 2025-08-26T19:55:57.7363625Z 2025-08-26T19:55:57.7363707Z 2025-08-26T19:55:57.7364083Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.7364469Z 2025-08-26T19:55:57.7365013Z msg = Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=296. 2025-08-26T19:55:57.7365914Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.7366503Z Allows capture of a triton kernel into a graph via make_fx or 2025-08-26T19:55:57.7366930Z non-strict ``torch.export``. 2025-08-26T19:55:57.7367130Z 2025-08-26T19:55:57.7367317Z These technologies perform Dispatcher-based tracing (via 2025-08-26T19:55:57.7367831Z ``__torch_dispatch__``) and cannot see calls to raw triton kernels. 2025-08-26T19:55:57.7368363Z The ``wrap_triton`` API wraps a triton kernel into a callable that 2025-08-26T19:55:57.7368890Z can actually be traced into a graph. 2025-08-26T19:55:57.7369122Z 2025-08-26T19:55:57.7369349Z Please use this API together with :func:`torch.library.triton_op`. 2025-08-26T19:55:57.7369679Z 2025-08-26T19:55:57.7369770Z Examples: 2025-08-26T19:55:57.7369918Z 2025-08-26T19:55:57.7370018Z >>> # xdoctest: +SKIP 2025-08-26T19:55:57.7370311Z >>> import torch 2025-08-26T19:55:57.7370580Z >>> import triton 2025-08-26T19:55:57.7370864Z >>> from triton import language as tl 2025-08-26T19:55:57.7371284Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T19:55:57.7371719Z >>> from torch.library import wrap_triton 2025-08-26T19:55:57.7372052Z >>> 2025-08-26T19:55:57.7372259Z >>> @triton.jit 2025-08-26T19:55:57.7372519Z >>> def add_kernel( 2025-08-26T19:55:57.7372791Z >>> in_ptr0, 2025-08-26T19:55:57.7373057Z >>> in_ptr1, 2025-08-26T19:55:57.7373304Z >>> out_ptr, 2025-08-26T19:55:57.7373569Z >>> n_elements, 2025-08-26T19:55:57.7373872Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T19:55:57.7374189Z >>> ): 2025-08-26T19:55:57.7374428Z >>> pid = tl.program_id(axis=0) 2025-08-26T19:55:57.7374772Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T19:55:57.7375156Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T19:55:57.7375656Z >>> mask = offsets < n_elements 2025-08-26T19:55:57.7375998Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T19:55:57.7376384Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T19:55:57.7376737Z >>> output = x + y 2025-08-26T19:55:57.7377078Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T19:55:57.7377435Z >>> 2025-08-26T19:55:57.7377648Z >>> def add(x, y): 2025-08-26T19:55:57.7378015Z >>> output = torch.empty_like(x) 2025-08-26T19:55:57.7378364Z >>> n_elements = output.numel() 2025-08-26T19:55:57.7378681Z >>> 2025-08-26T19:55:57.7378901Z >>> def grid_fn(meta): 2025-08-26T19:55:57.7379282Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T19:55:57.7379672Z >>> 2025-08-26T19:55:57.7380004Z >>> wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16) 2025-08-26T19:55:57.7380424Z >>> return output 2025-08-26T19:55:57.7380703Z >>> 2025-08-26T19:55:57.7380955Z >>> x = torch.randn(3, device="cuda") 2025-08-26T19:55:57.7381310Z >>> y = torch.randn(3, device="cuda") 2025-08-26T19:55:57.7381640Z >>> gm = make_fx(add)(x, y) 2025-08-26T19:55:57.7381956Z >>> print(gm.code) 2025-08-26T19:55:57.7382253Z >>> # def forward(self, x_1, y_1): 2025-08-26T19:55:57.7382727Z >>> # empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False) 2025-08-26T19:55:57.7383333Z >>> # triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation( 2025-08-26T19:55:57.7383846Z >>> # kernel_idx = 0, constant_args_idx = 0, 2025-08-26T19:55:57.7384220Z >>> # grid = [(1, 1, 1)], kwargs = { 2025-08-26T19:55:57.7384612Z >>> # 'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like, 2025-08-26T19:55:57.7385019Z >>> # 'n_elements': 3, 'BLOCK_SIZE': 16 2025-08-26T19:55:57.7385363Z >>> # }) 2025-08-26T19:55:57.7385632Z >>> # return empty_like 2025-08-26T19:55:57.7385832Z 2025-08-26T19:55:57.7385925Z 2025-08-26T19:55:57.7386303Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.7386679Z 2025-08-26T19:55:57.8247712Z msg = Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=286. 2025-08-26T19:55:57.8248702Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.8249155Z 2025-08-26T19:55:57.8249378Z Test if two objects are equal, and print an error message if test fails. 2025-08-26T19:55:57.8249718Z 2025-08-26T19:55:57.8249906Z The test is performed with ``actual == desired``. 2025-08-26T19:55:57.8250222Z 2025-08-26T19:55:57.8250326Z Parameters 2025-08-26T19:55:57.8250551Z ---------- 2025-08-26T19:55:57.8250824Z test_string : str 2025-08-26T19:55:57.8251271Z The message supplied to AssertionError. 2025-08-26T19:55:57.8251915Z actual : object 2025-08-26T19:55:57.8252254Z The object to test for equality against `desired`. 2025-08-26T19:55:57.8252625Z desired : object 2025-08-26T19:55:57.8252879Z The expected result. 2025-08-26T19:55:57.8253053Z 2025-08-26T19:55:57.8253156Z Examples 2025-08-26T19:55:57.8253354Z -------- 2025-08-26T19:55:57.8253597Z >>> np.testing.print_assert_equal( 2025-08-26T19:55:57.8254007Z ... "Test XYZ of func xyz", [0, 1], [0, 1] 2025-08-26T19:55:57.8254462Z ... ) # doctest: +SKIP 2025-08-26T19:55:57.8254750Z >>> np.testing.print_assert_equal( 2025-08-26T19:55:57.8255337Z ... "Test XYZ of func xyz", [0, 1], [0, 2] 2025-08-26T19:55:57.8255908Z ... ) # doctest: +SKIP 2025-08-26T19:55:57.8256190Z Traceback (most recent call last): 2025-08-26T19:55:57.8256476Z ... 2025-08-26T19:55:57.8256724Z AssertionError: Test XYZ of func xyz failed 2025-08-26T19:55:57.8257272Z ACTUAL: 2025-08-26T19:55:57.8257487Z [0, 1] 2025-08-26T19:55:57.8257688Z DESIRED: 2025-08-26T19:55:57.8257904Z [0, 2] 2025-08-26T19:55:57.8258034Z 2025-08-26T19:55:57.8258039Z 2025-08-26T19:55:57.8258300Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.8258684Z 2025-08-26T19:55:57.8259470Z msg = Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=331. 2025-08-26T19:55:57.8260790Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.8261547Z 2025-08-26T19:55:57.8261761Z Raises an AssertionError if two items are not equal up to desired 2025-08-26T19:55:57.8262188Z precision. 2025-08-26T19:55:57.8262316Z 2025-08-26T19:55:57.8262518Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T19:55:57.8262985Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T19:55:57.8263491Z instead of this function for more consistent floating point 2025-08-26T19:55:57.8263899Z comparisons. 2025-08-26T19:55:57.8264058Z 2025-08-26T19:55:57.8264397Z The test verifies that the elements of `actual` and `desired` satisfy. 2025-08-26T19:55:57.8264770Z 2025-08-26T19:55:57.8264972Z ``abs(desired-actual) < float64(1.5 * 10**(-decimal))`` 2025-08-26T19:55:57.8265503Z 2025-08-26T19:55:57.8265950Z That is a looser test than originally documented, but agrees with what the 2025-08-26T19:55:57.8266578Z actual implementation in `assert_array_almost_equal` did up to rounding 2025-08-26T19:55:57.8267185Z vagaries. An exception is raised at conflicting values. For ndarrays this 2025-08-26T19:55:57.8267673Z delegates to assert_array_almost_equal 2025-08-26T19:55:57.8267895Z 2025-08-26T19:55:57.8267986Z Parameters 2025-08-26T19:55:57.8268211Z ---------- 2025-08-26T19:55:57.8268435Z actual : array_like 2025-08-26T19:55:57.8268690Z The object to check. 2025-08-26T19:55:57.8268952Z desired : array_like 2025-08-26T19:55:57.8269213Z The expected object. 2025-08-26T19:55:57.8269483Z decimal : int, optional 2025-08-26T19:55:57.8269766Z Desired precision, default is 7. 2025-08-26T19:55:57.8270069Z err_msg : str, optional 2025-08-26T19:55:57.8270390Z The error message to be printed in case of failure. 2025-08-26T19:55:57.8270763Z verbose : bool, optional 2025-08-26T19:55:57.8271152Z If True, the conflicting values are appended to the error message. 2025-08-26T19:55:57.8271479Z 2025-08-26T19:55:57.8271563Z Raises 2025-08-26T19:55:57.8271772Z ------ 2025-08-26T19:55:57.8271999Z AssertionError 2025-08-26T19:55:57.8272345Z If actual and desired are not equal up to specified precision. 2025-08-26T19:55:57.8272656Z 2025-08-26T19:55:57.8272741Z See Also 2025-08-26T19:55:57.8272952Z -------- 2025-08-26T19:55:57.8273316Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:55:57.8279566Z relative and/or absolute precision. 2025-08-26T19:55:57.8280042Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:55:57.8280387Z 2025-08-26T19:55:57.8280476Z Examples 2025-08-26T19:55:57.8280695Z -------- 2025-08-26T19:55:57.8280997Z >>> from torch._numpy.testing import assert_almost_equal 2025-08-26T19:55:57.8281408Z >>> assert_almost_equal(2.3333333333333, 2.33333334) 2025-08-26T19:55:57.8281844Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10) 2025-08-26T19:55:57.8282263Z Traceback (most recent call last): 2025-08-26T19:55:57.8282570Z ... 2025-08-26T19:55:57.8282784Z AssertionError: 2025-08-26T19:55:57.8283065Z Arrays are not almost equal to 10 decimals 2025-08-26T19:55:57.8283402Z ACTUAL: 2.3333333333333 2025-08-26T19:55:57.8283672Z DESIRED: 2.33333334 2025-08-26T19:55:57.8283825Z 2025-08-26T19:55:57.8283926Z >>> assert_almost_equal( 2025-08-26T19:55:57.8284314Z ... np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9 2025-08-26T19:55:57.8284756Z ... ) 2025-08-26T19:55:57.8285051Z Traceback (most recent call last): 2025-08-26T19:55:57.8285349Z ... 2025-08-26T19:55:57.8285566Z AssertionError: 2025-08-26T19:55:57.8285835Z Arrays are not almost equal to 9 decimals 2025-08-26T19:55:57.8286145Z 2025-08-26T19:55:57.8286384Z Mismatched elements: 1 / 2 (50%) 2025-08-26T19:55:57.8286721Z Max absolute difference: 6.666699636781459e-09 2025-08-26T19:55:57.8287104Z Max relative difference: 2.8571569790287484e-09 2025-08-26T19:55:57.8287478Z x: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T19:55:57.8287942Z y: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T19:55:57.8288208Z 2025-08-26T19:55:57.8288213Z 2025-08-26T19:55:57.8288470Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.8288944Z 2025-08-26T19:55:57.8289539Z msg = Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=457. 2025-08-26T19:55:57.8290510Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.8290899Z 2025-08-26T19:55:57.8291126Z Raises an AssertionError if two items are not equal up to significant 2025-08-26T19:55:57.8291560Z digits. 2025-08-26T19:55:57.8291690Z 2025-08-26T19:55:57.8291873Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T19:55:57.8292349Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T19:55:57.8292851Z instead of this function for more consistent floating point 2025-08-26T19:55:57.8293250Z comparisons. 2025-08-26T19:55:57.8293426Z 2025-08-26T19:55:57.8293611Z Given two numbers, check that they are approximately equal. 2025-08-26T19:55:57.8294143Z Approximately equal is defined as the number of significant digits 2025-08-26T19:55:57.8294576Z that agree. 2025-08-26T19:55:57.8294703Z 2025-08-26T19:55:57.8294794Z Parameters 2025-08-26T19:55:57.8295017Z ---------- 2025-08-26T19:55:57.8295239Z actual : scalar 2025-08-26T19:55:57.8295493Z The object to check. 2025-08-26T19:55:57.8295747Z desired : scalar 2025-08-26T19:55:57.8295996Z The expected object. 2025-08-26T19:55:57.8296277Z significant : int, optional 2025-08-26T19:55:57.8296580Z Desired precision, default is 7. 2025-08-26T19:55:57.8296887Z err_msg : str, optional 2025-08-26T19:55:57.8297211Z The error message to be printed in case of failure. 2025-08-26T19:55:57.8297581Z verbose : bool, optional 2025-08-26T19:55:57.8297965Z If True, the conflicting values are appended to the error message. 2025-08-26T19:55:57.8298294Z 2025-08-26T19:55:57.8298377Z Raises 2025-08-26T19:55:57.8298581Z ------ 2025-08-26T19:55:57.8298795Z AssertionError 2025-08-26T19:55:57.8299138Z If actual and desired are not equal up to specified precision. 2025-08-26T19:55:57.8299450Z 2025-08-26T19:55:57.8299536Z See Also 2025-08-26T19:55:57.8299747Z -------- 2025-08-26T19:55:57.8300112Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:55:57.8300694Z relative and/or absolute precision. 2025-08-26T19:55:57.8301143Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:55:57.8301487Z 2025-08-26T19:55:57.8301574Z Examples 2025-08-26T19:55:57.8301787Z -------- 2025-08-26T19:55:57.8302032Z >>> np.testing.assert_approx_equal( 2025-08-26T19:55:57.8302346Z ... 0.12345677777777e-20, 0.1234567e-20 2025-08-26T19:55:57.8302666Z ... ) # doctest: +SKIP 2025-08-26T19:55:57.8302949Z >>> np.testing.assert_approx_equal( 2025-08-26T19:55:57.8303258Z ... 0.12345670e-20, 2025-08-26T19:55:57.8303519Z ... 0.12345671e-20, # doctest: +SKIP 2025-08-26T19:55:57.8303841Z ... significant=8, 2025-08-26T19:55:57.8304089Z ... ) 2025-08-26T19:55:57.8304330Z >>> np.testing.assert_approx_equal( 2025-08-26T19:55:57.8304626Z ... 0.12345670e-20, 2025-08-26T19:55:57.8304897Z ... 0.12345672e-20, # doctest: +SKIP 2025-08-26T19:55:57.8305217Z ... significant=8, 2025-08-26T19:55:57.8305469Z ... ) 2025-08-26T19:55:57.8305754Z Traceback (most recent call last): 2025-08-26T19:55:57.8306057Z ... 2025-08-26T19:55:57.8306274Z AssertionError: 2025-08-26T19:55:57.8306558Z Items are not equal to 8 significant digits: 2025-08-26T19:55:57.8306887Z ACTUAL: 1.234567e-21 2025-08-26T19:55:57.8307145Z DESIRED: 1.2345672e-21 2025-08-26T19:55:57.8307304Z 2025-08-26T19:55:57.8307480Z the evaluated condition that raises the exception is 2025-08-26T19:55:57.8307754Z 2025-08-26T19:55:57.8307964Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1) 2025-08-26T19:55:57.8308411Z True 2025-08-26T19:55:57.8308540Z 2025-08-26T19:55:57.8308544Z 2025-08-26T19:55:57.8308800Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.8309191Z 2025-08-26T19:55:57.8309831Z msg = Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=744. 2025-08-26T19:55:57.8310777Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.8311183Z 2025-08-26T19:55:57.8311397Z Raises an AssertionError if two array_like objects are not equal. 2025-08-26T19:55:57.8311741Z 2025-08-26T19:55:57.8311951Z Given two array_like objects, check that the shape is equal and all 2025-08-26T19:55:57.8312515Z elements of these objects are equal (but see the Notes for the special 2025-08-26T19:55:57.8313076Z handling of a scalar). An exception is raised at shape mismatch or 2025-08-26T19:55:57.8313624Z conflicting values. In contrast to the standard usage in numpy, NaNs 2025-08-26T19:55:57.8314196Z are compared like numbers, no assertion is raised if both objects have 2025-08-26T19:55:57.8314654Z NaNs in the same positions. 2025-08-26T19:55:57.8314838Z 2025-08-26T19:55:57.8315081Z The usual caution for verifying equality with floating point numbers is 2025-08-26T19:55:57.8315522Z advised. 2025-08-26T19:55:57.8315641Z 2025-08-26T19:55:57.8315731Z Parameters 2025-08-26T19:55:57.8315958Z ---------- 2025-08-26T19:55:57.8316217Z x : array_like 2025-08-26T19:55:57.8316606Z The actual object to check. 2025-08-26T19:55:57.8316887Z y : array_like 2025-08-26T19:55:57.8317141Z The desired, expected object. 2025-08-26T19:55:57.8317453Z err_msg : str, optional 2025-08-26T19:55:57.8317910Z The error message to be printed in case of failure. 2025-08-26T19:55:57.8318603Z verbose : bool, optional 2025-08-26T19:55:57.8319076Z If True, the conflicting values are appended to the error message. 2025-08-26T19:55:57.8319511Z strict : bool, optional 2025-08-26T19:55:57.8319898Z If True, raise an AssertionError when either the shape or the data 2025-08-26T19:55:57.8320394Z type of the array_like objects does not match. The special 2025-08-26T19:55:57.8320910Z handling for scalars mentioned in the Notes section is disabled. 2025-08-26T19:55:57.8321247Z 2025-08-26T19:55:57.8321332Z Raises 2025-08-26T19:55:57.8321542Z ------ 2025-08-26T19:55:57.8321846Z AssertionError 2025-08-26T19:55:57.8322120Z If actual and desired objects are not equal. 2025-08-26T19:55:57.8322384Z 2025-08-26T19:55:57.8322471Z See Also 2025-08-26T19:55:57.8322687Z -------- 2025-08-26T19:55:57.8323056Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:55:57.8323540Z relative and/or absolute precision. 2025-08-26T19:55:57.8324003Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:55:57.8324332Z 2025-08-26T19:55:57.8324428Z Notes 2025-08-26T19:55:57.8324630Z ----- 2025-08-26T19:55:57.8324930Z When one of `x` and `y` is a scalar and the other is array_like, the 2025-08-26T19:55:57.8325467Z function checks that each element of the array_like object is equal to 2025-08-26T19:55:57.8326044Z the scalar. This behaviour can be disabled with the `strict` parameter. 2025-08-26T19:55:57.8326391Z 2025-08-26T19:55:57.8326490Z Examples 2025-08-26T19:55:57.8326687Z -------- 2025-08-26T19:55:57.8326948Z The first assert does not raise an exception: 2025-08-26T19:55:57.8327311Z 2025-08-26T19:55:57.8327427Z >>> np.testing.assert_array_equal( 2025-08-26T19:55:57.8327793Z ... [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan] 2025-08-26T19:55:57.8328128Z ... ) 2025-08-26T19:55:57.8328257Z 2025-08-26T19:55:57.8328489Z Use `assert_allclose` or one of the nulp (number of floating point values) 2025-08-26T19:55:57.8329030Z functions for these cases instead: 2025-08-26T19:55:57.8329241Z 2025-08-26T19:55:57.8329366Z >>> np.testing.assert_allclose( 2025-08-26T19:55:57.8329833Z ... [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0 2025-08-26T19:55:57.8330233Z ... ) 2025-08-26T19:55:57.8330362Z 2025-08-26T19:55:57.8330571Z As mentioned in the Notes section, `assert_array_equal` has special 2025-08-26T19:55:57.8331128Z handling for scalars. Here the test checks that each value in `x` is 3: 2025-08-26T19:55:57.8331473Z 2025-08-26T19:55:57.8331593Z >>> x = np.full((2, 5), fill_value=3) 2025-08-26T19:55:57.8331914Z >>> np.testing.assert_array_equal(x, 3) 2025-08-26T19:55:57.8332151Z 2025-08-26T19:55:57.8332366Z Use `strict` to raise an AssertionError when comparing a scalar with an 2025-08-26T19:55:57.8332794Z array: 2025-08-26T19:55:57.8332910Z 2025-08-26T19:55:57.8333077Z >>> np.testing.assert_array_equal(x, 3, strict=True) 2025-08-26T19:55:57.8333463Z Traceback (most recent call last): 2025-08-26T19:55:57.8333752Z ... 2025-08-26T19:55:57.8333971Z AssertionError: 2025-08-26T19:55:57.8334214Z Arrays are not equal 2025-08-26T19:55:57.8334470Z 2025-08-26T19:55:57.8334695Z (shapes (2, 5), () mismatch) 2025-08-26T19:55:57.8334991Z x: torch.ndarray([[3, 3, 3, 3, 3], 2025-08-26T19:55:57.8335295Z [3, 3, 3, 3, 3]]) 2025-08-26T19:55:57.8335560Z y: torch.ndarray(3) 2025-08-26T19:55:57.8335751Z 2025-08-26T19:55:57.8335980Z The `strict` parameter also ensures that the array data types match: 2025-08-26T19:55:57.8336323Z 2025-08-26T19:55:57.8336424Z >>> x = np.array([2, 2, 2]) 2025-08-26T19:55:57.8336738Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32) 2025-08-26T19:55:57.8337144Z >>> np.testing.assert_array_equal(x, y, strict=True) 2025-08-26T19:55:57.8337702Z Traceback (most recent call last): 2025-08-26T19:55:57.8338009Z ... 2025-08-26T19:55:57.8338228Z AssertionError: 2025-08-26T19:55:57.8338478Z Arrays are not equal 2025-08-26T19:55:57.8338717Z 2025-08-26T19:55:57.8339002Z (dtypes dtype("int64"), dtype("float32") mismatch) 2025-08-26T19:55:57.8339372Z x: torch.ndarray([2, 2, 2]) 2025-08-26T19:55:57.8339666Z y: torch.ndarray([2., 2., 2.]) 2025-08-26T19:55:57.8339857Z 2025-08-26T19:55:57.8340113Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.8340501Z 2025-08-26T19:55:57.8341100Z msg = Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=851. 2025-08-26T19:55:57.8342080Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.8342564Z 2025-08-26T19:55:57.8342795Z Raises an AssertionError if two objects are not equal up to desired 2025-08-26T19:55:57.8343228Z precision. 2025-08-26T19:55:57.8343354Z 2025-08-26T19:55:57.8343535Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T19:55:57.8344014Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T19:55:57.8344513Z instead of this function for more consistent floating point 2025-08-26T19:55:57.8344923Z comparisons. 2025-08-26T19:55:57.8345083Z 2025-08-26T19:55:57.8345341Z The test verifies identical shapes and that the elements of ``actual`` and 2025-08-26T19:55:57.8345793Z ``desired`` satisfy. 2025-08-26T19:55:57.8345960Z 2025-08-26T19:55:57.8346093Z ``abs(desired-actual) < 1.5 * 10**(-decimal)`` 2025-08-26T19:55:57.8346350Z 2025-08-26T19:55:57.8346581Z That is a looser test than originally documented, but agrees with what the 2025-08-26T19:55:57.8347187Z actual implementation did up to rounding vagaries. An exception is raised 2025-08-26T19:55:57.8347837Z at shape mismatch or conflicting values. In contrast to the standard usage 2025-08-26T19:55:57.8348428Z in numpy, NaNs are compared like numbers, no assertion is raised if both 2025-08-26T19:55:57.8348906Z objects have NaNs in the same positions. 2025-08-26T19:55:57.8349134Z 2025-08-26T19:55:57.8349238Z Parameters 2025-08-26T19:55:57.8349457Z ---------- 2025-08-26T19:55:57.8349663Z x : array_like 2025-08-26T19:55:57.8349908Z The actual object to check. 2025-08-26T19:55:57.8350194Z y : array_like 2025-08-26T19:55:57.8350506Z The desired, expected object. 2025-08-26T19:55:57.8350816Z decimal : int, optional 2025-08-26T19:55:57.8351102Z Desired precision, default is 6. 2025-08-26T19:55:57.8351425Z err_msg : str, optional 2025-08-26T19:55:57.8351741Z The error message to be printed in case of failure. 2025-08-26T19:55:57.8352121Z verbose : bool, optional 2025-08-26T19:55:57.8352515Z If True, the conflicting values are appended to the error message. 2025-08-26T19:55:57.8352841Z 2025-08-26T19:55:57.8352940Z Raises 2025-08-26T19:55:57.8353149Z ------ 2025-08-26T19:55:57.8353359Z AssertionError 2025-08-26T19:55:57.8353711Z If actual and desired are not equal up to specified precision. 2025-08-26T19:55:57.8354025Z 2025-08-26T19:55:57.8354130Z See Also 2025-08-26T19:55:57.8354343Z -------- 2025-08-26T19:55:57.8354700Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:55:57.8355204Z relative and/or absolute precision. 2025-08-26T19:55:57.8355673Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:55:57.8356004Z 2025-08-26T19:55:57.8356105Z Examples 2025-08-26T19:55:57.8356307Z -------- 2025-08-26T19:55:57.8356568Z the first assert does not raise an exception 2025-08-26T19:55:57.8356822Z 2025-08-26T19:55:57.8357079Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan]) 2025-08-26T19:55:57.8357457Z 2025-08-26T19:55:57.8357592Z >>> np.testing.assert_array_almost_equal( 2025-08-26T19:55:57.8357971Z ... [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5 2025-08-26T19:55:57.8358334Z ... ) 2025-08-26T19:55:57.8358574Z Traceback (most recent call last): 2025-08-26T19:55:57.8358874Z ... 2025-08-26T19:55:57.8359084Z AssertionError: 2025-08-26T19:55:57.8359357Z Arrays are not almost equal to 5 decimals 2025-08-26T19:55:57.8359684Z 2025-08-26T19:55:57.8359921Z Mismatched elements: 1 / 3 (33.3%) 2025-08-26T19:55:57.8360248Z Max absolute difference: 5.999999999994898e-05 2025-08-26T19:55:57.8360624Z Max relative difference: 2.5713661239633743e-05 2025-08-26T19:55:57.8361043Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T19:55:57.8361486Z y: torch.ndarray([1.0000, 2.3334, nan], dtype=float64) 2025-08-26T19:55:57.8361762Z 2025-08-26T19:55:57.8361896Z >>> np.testing.assert_array_almost_equal( 2025-08-26T19:55:57.8362297Z ... [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5 2025-08-26T19:55:57.8362643Z ... ) 2025-08-26T19:55:57.8362877Z Traceback (most recent call last): 2025-08-26T19:55:57.8363182Z ... 2025-08-26T19:55:57.8363388Z AssertionError: 2025-08-26T19:55:57.8363710Z Arrays are not almost equal to 5 decimals 2025-08-26T19:55:57.8364036Z 2025-08-26T19:55:57.8364276Z x and y nan location mismatch: 2025-08-26T19:55:57.8364624Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T19:55:57.8365065Z y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64) 2025-08-26T19:55:57.8365339Z 2025-08-26T19:55:57.8365359Z 2025-08-26T19:55:57.8365615Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.8365989Z 2025-08-26T19:55:57.8366628Z msg = Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=1848. 2025-08-26T19:55:57.8367611Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:57.8368265Z Context manager that resets warning registry for catching warnings 2025-08-26T19:55:57.8368594Z 2025-08-26T19:55:57.8368914Z Warnings can be slippery, because, whenever a warning is triggered, Python 2025-08-26T19:55:57.8369524Z adds a ``__warningregistry__`` member to the *calling* module. This makes 2025-08-26T19:55:57.8370128Z it impossible to retrigger the warning in this module, whatever you put in 2025-08-26T19:55:57.8370747Z the warnings filters. This context manager accepts a sequence of `modules` 2025-08-26T19:55:57.8371320Z as a keyword argument to its constructor and: 2025-08-26T19:55:57.8371584Z 2025-08-26T19:55:57.8371816Z * stores and removes any ``__warningregistry__`` entries in given `modules` 2025-08-26T19:55:57.8372263Z on entry; 2025-08-26T19:55:57.8372597Z * resets ``__warningregistry__`` to its previous state on exit. 2025-08-26T19:55:57.8372901Z 2025-08-26T19:55:57.8373146Z This makes it possible to trigger any warning afresh inside the context 2025-08-26T19:55:57.8373677Z manager without disturbing the state of warnings outside. 2025-08-26T19:55:57.8373991Z 2025-08-26T19:55:57.8374231Z For compatibility with Python 3.0, please consider all arguments to be 2025-08-26T19:55:57.8374688Z keyword-only. 2025-08-26T19:55:57.8374833Z 2025-08-26T19:55:57.8374934Z Parameters 2025-08-26T19:55:57.8375153Z ---------- 2025-08-26T19:55:57.8375396Z record : bool, optional 2025-08-26T19:55:57.8375773Z Specifies whether warnings should be captured by a custom 2025-08-26T19:55:57.8376375Z implementation of ``warnings.showwarning()`` and be appended to a list 2025-08-26T19:55:57.8376950Z returned by the context manager. Otherwise None is returned by the 2025-08-26T19:55:57.8377506Z context manager. The objects appended to the list are arguments whose 2025-08-26T19:55:57.8378030Z attributes mirror the arguments to ``showwarning()``. 2025-08-26T19:55:57.8378435Z modules : sequence, optional 2025-08-26T19:55:57.8378868Z Sequence of modules for which to reset warnings registry on entry and 2025-08-26T19:55:57.8379401Z restore on exit. To work correctly, all 'ignore' filters should 2025-08-26T19:55:57.8379829Z filter by one of these modules. 2025-08-26T19:55:57.8380052Z 2025-08-26T19:55:57.8380141Z Examples 2025-08-26T19:55:57.8380360Z -------- 2025-08-26T19:55:57.8380573Z >>> import warnings 2025-08-26T19:55:57.8380927Z >>> with np.testing.clear_and_catch_warnings( # doctest: +SKIP 2025-08-26T19:55:57.8381356Z ... modules=[np.core.fromnumeric] 2025-08-26T19:55:57.8381670Z ... ): 2025-08-26T19:55:57.8381903Z ... warnings.simplefilter("always") 2025-08-26T19:55:57.8382361Z ... warnings.filterwarnings("ignore", module="np.core.fromnumeric") 2025-08-26T19:55:57.8382886Z ... # do something that raises a warning but ignore those in 2025-08-26T19:55:57.8383351Z ... # np.core.fromnumeric 2025-08-26T19:55:57.8383626Z 2025-08-26T19:55:57.8384003Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:57.8384388Z 2025-08-26T19:55:58.0455930Z msg = Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py line=354. 2025-08-26T19:55:58.0456911Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.0457528Z Applies a 1D convolution over a quantized input signal composed of 2025-08-26T19:55:58.0458000Z several quantized input planes. 2025-08-26T19:55:58.0458235Z 2025-08-26T19:55:58.0458452Z For details on input arguments, parameters, and implementation see 2025-08-26T19:55:58.0458901Z :class:`~torch.nn.Conv1d`. 2025-08-26T19:55:58.0459110Z 2025-08-26T19:55:58.0459214Z .. note:: 2025-08-26T19:55:58.0459554Z Only `zeros` is supported for the :attr:`padding_mode` argument. 2025-08-26T19:55:58.0459879Z 2025-08-26T19:55:58.0460149Z .. note:: 2025-08-26T19:55:58.0460454Z Only `torch.quint8` is supported for the input data type. 2025-08-26T19:55:58.0460764Z 2025-08-26T19:55:58.0460768Z 2025-08-26T19:55:58.0460859Z Attributes: 2025-08-26T19:55:58.0461243Z weight (Tensor): packed tensor derived from the learnable weight 2025-08-26T19:55:58.0461693Z parameter. 2025-08-26T19:55:58.0462045Z scale (Tensor): scalar for the output scale 2025-08-26T19:55:58.0462479Z zero_point (Tensor): scalar for the output zero point 2025-08-26T19:55:58.0462880Z 2025-08-26T19:55:58.0463037Z See :class:`~torch.nn.Conv1d` for other attributes. 2025-08-26T19:55:58.0463305Z 2025-08-26T19:55:58.0463415Z Examples:: 2025-08-26T19:55:58.0463554Z 2025-08-26T19:55:58.0463720Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE) 2025-08-26T19:55:58.0464118Z >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2) 2025-08-26T19:55:58.0464498Z >>> input = torch.randn(20, 16, 100) 2025-08-26T19:55:58.0464847Z >>> # quantize input to quint8 2025-08-26T19:55:58.0465175Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.0465577Z >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0, 2025-08-26T19:55:58.0466059Z ... dtype=torch.quint8) 2025-08-26T19:55:58.0466420Z >>> output = m(q_input) 2025-08-26T19:55:58.0466608Z 2025-08-26T19:55:58.0466709Z 2025-08-26T19:55:58.0467087Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.0467467Z 2025-08-26T19:55:58.0685139Z msg = Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12. 2025-08-26T19:55:58.0686086Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.0686614Z A quantized long short-term memory (LSTM). 2025-08-26T19:55:58.0686862Z 2025-08-26T19:55:58.0687162Z For the description and the argument types, please, refer to :class:`~torch.nn.LSTM` 2025-08-26T19:55:58.0687581Z 2025-08-26T19:55:58.0687685Z Attributes: 2025-08-26T19:55:58.0687943Z layers : instances of the `_LSTMLayer` 2025-08-26T19:55:58.0688192Z 2025-08-26T19:55:58.0688286Z .. note:: 2025-08-26T19:55:58.0688639Z To access the weights and biases, you need to access them per layer. 2025-08-26T19:55:58.0689242Z See examples in :class:`~torch.ao.nn.quantizable.LSTM` 2025-08-26T19:55:58.0689558Z 2025-08-26T19:55:58.0689664Z Examples:: 2025-08-26T19:55:58.0689903Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.0690200Z >>> custom_module_config = { 2025-08-26T19:55:58.0690557Z ... 'float_to_observed_custom_module_class': { 2025-08-26T19:55:58.0690947Z ... nn.LSTM: nn.quantizable.LSTM, 2025-08-26T19:55:58.0691265Z ... }, 2025-08-26T19:55:58.0691563Z ... 'observed_to_quantized_custom_module_class': { 2025-08-26T19:55:58.0692114Z ... nn.quantizable.LSTM: nn.quantized.LSTM, 2025-08-26T19:55:58.0692472Z ... } 2025-08-26T19:55:58.0692692Z ... } 2025-08-26T19:55:58.0693056Z >>> tq.prepare(model, prepare_custom_module_class=custom_module_config) 2025-08-26T19:55:58.0693624Z >>> tq.convert(model, convert_custom_module_class=custom_module_config) 2025-08-26T19:55:58.0694053Z 2025-08-26T19:55:58.0694416Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.0694801Z 2025-08-26T19:55:58.1454554Z msg = Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-08-26T19:55:58.1455797Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.1456197Z 2025-08-26T19:55:58.1456466Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-08-26T19:55:58.1457278Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-08-26T19:55:58.1457893Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-08-26T19:55:58.1458371Z input by the user. 2025-08-26T19:55:58.1458745Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-08-26T19:55:58.1459262Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-08-26T19:55:58.1459546Z 2025-08-26T19:55:58.1459644Z Note:: 2025-08-26T19:55:58.1460202Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-08-26T19:55:58.1460652Z 2025-08-26T19:55:58.1460742Z Args: 2025-08-26T19:55:58.1460971Z model (nn.Module): 2025-08-26T19:55:58.1461373Z The model whose layers will be sparsified. The layers that needs to be 2025-08-26T19:55:58.1461982Z sparsified should be added separately using the register_layer() function 2025-08-26T19:55:58.1462481Z aggregate_fn (Optional, Callable): 2025-08-26T19:55:58.1462957Z default aggregate_fn that is used if not specified while registering the layer. 2025-08-26T19:55:58.1463518Z specifies how inputs should be aggregated over time. 2025-08-26T19:55:58.1464097Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-08-26T19:55:58.1464606Z Example 2025-08-26T19:55:58.1464917Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-08-26T19:55:58.1465338Z reduce_fn (Optional, Callable): 2025-08-26T19:55:58.1465823Z default reduce_fn that is used if not specified while registering the layer. 2025-08-26T19:55:58.1466514Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-08-26T19:55:58.1467022Z calling agg_fn() on all inputs. 2025-08-26T19:55:58.1467337Z Example 2025-08-26T19:55:58.1467706Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-08-26T19:55:58.1468150Z mask_fn (Optional, Callable): 2025-08-26T19:55:58.1468698Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-08-26T19:55:58.1469384Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-08-26T19:55:58.1469873Z register_layer(). 2025-08-26T19:55:58.1470435Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-08-26T19:55:58.1471008Z arguments. 2025-08-26T19:55:58.1471285Z features (Optional, list): 2025-08-26T19:55:58.1471644Z default selected features to sparsify. 2025-08-26T19:55:58.1472166Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-08-26T19:55:58.1472664Z For example, 2025-08-26T19:55:58.1473179Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-08-26T19:55:58.1473674Z feature_dim (Optional, int): 2025-08-26T19:55:58.1474187Z default dimension of input features. Again, features along this dim will be chosen 2025-08-26T19:55:58.1474710Z for sparsification. 2025-08-26T19:55:58.1475030Z sparse_config (Dict): 2025-08-26T19:55:58.1475449Z Default configuration for the mask_fn. This config will be passed 2025-08-26T19:55:58.1475911Z with the mask_fn() 2025-08-26T19:55:58.1476125Z 2025-08-26T19:55:58.1476212Z Example: 2025-08-26T19:55:58.1476437Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.1476705Z >>> model = SomeModel() 2025-08-26T19:55:58.1477138Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-08-26T19:55:58.1477618Z >>> # Initialize aggregate_fn 2025-08-26T19:55:58.1477926Z >>> def agg_fn(x, y): 2025-08-26T19:55:58.1478222Z >>> return x + y 2025-08-26T19:55:58.1495801Z >>> 2025-08-26T19:55:58.1496140Z >>> # Initialize reduce_fn 2025-08-26T19:55:58.1496736Z >>> def reduce_fn(x): 2025-08-26T19:55:58.1497134Z >>> return torch.mean(x, dim=0) 2025-08-26T19:55:58.1497435Z >>> 2025-08-26T19:55:58.1497662Z >>> # Initialize mask_fn 2025-08-26T19:55:58.1497956Z >>> def mask_fn(data): 2025-08-26T19:55:58.1498268Z >>> return torch.eye(data.shape).to(data.device) 2025-08-26T19:55:58.1498624Z >>> 2025-08-26T19:55:58.1498832Z >>> 2025-08-26T19:55:58.1499201Z >>> act_sparsifier.register_layer( 2025-08-26T19:55:58.1499526Z ... model.some_layer, 2025-08-26T19:55:58.1499824Z ... aggregate_fn=agg_fn, 2025-08-26T19:55:58.1500127Z ... reduce_fn=reduce_fn, 2025-08-26T19:55:58.1500426Z ... mask_fn=mask_fn, 2025-08-26T19:55:58.1500685Z ... ) 2025-08-26T19:55:58.1500899Z >>> 2025-08-26T19:55:58.1501129Z >>> # start training process 2025-08-26T19:55:58.1501429Z >>> for _ in [...]: 2025-08-26T19:55:58.1501676Z >>> # epoch starts 2025-08-26T19:55:58.1502018Z >>> # model.forward(), compute_loss() and model.backwards() 2025-08-26T19:55:58.1502408Z >>> # epoch ends 2025-08-26T19:55:58.1502674Z >>> act_sparsifier.step() 2025-08-26T19:55:58.1502970Z >>> # end training process 2025-08-26T19:55:58.1503271Z >>> sparsifier.squash_mask() 2025-08-26T19:55:58.1503484Z 2025-08-26T19:55:58.1503743Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.1504121Z 2025-08-26T19:55:58.1505027Z msg = Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91. 2025-08-26T19:55:58.1506271Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.1506658Z 2025-08-26T19:55:58.1506882Z Abstract method that needs to be implemented by the child class. 2025-08-26T19:55:58.1507468Z The expected return type should is a dictionary of name to schedule_param value 2025-08-26T19:55:58.1508128Z The returned values will be updated in sparsifier when the scheduler step() function 2025-08-26T19:55:58.1508624Z is called. 2025-08-26T19:55:58.1508749Z 2025-08-26T19:55:58.1508852Z Example: 2025-08-26T19:55:58.1509079Z >>> def get_schedule_param(self): 2025-08-26T19:55:58.1509399Z ... new_param = {} 2025-08-26T19:55:58.1509745Z ... for name in self.sparsifier.data_groups.keys(): 2025-08-26T19:55:58.1510136Z ... new_param[name] = ( 2025-08-26T19:55:58.1510546Z ... self.sparsifier.data_groups[name][self.schedule_param] * 0.5 2025-08-26T19:55:58.1510975Z ... ) 2025-08-26T19:55:58.1511225Z ... return new_param 2025-08-26T19:55:58.1511406Z 2025-08-26T19:55:58.1511766Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param] 2025-08-26T19:55:58.1512395Z would be halved 2025-08-26T19:55:58.1512536Z 2025-08-26T19:55:58.1512794Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.1513187Z 2025-08-26T19:55:58.1867304Z msg = Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229. 2025-08-26T19:55:58.1868436Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.1869035Z Squashes the sparse masks into the appropriate tensors. 2025-08-26T19:55:58.1869327Z 2025-08-26T19:55:58.1869544Z If either the `params_to_keep` or `params_to_keep_per_layer` is set, 2025-08-26T19:55:58.1870076Z the module will have a `sparse_params` dict attached to it. 2025-08-26T19:55:58.1870395Z 2025-08-26T19:55:58.1870483Z Args: 2025-08-26T19:55:58.1870817Z params_to_keep: List of keys to save in the module or a dict 2025-08-26T19:55:58.1871438Z representing the modules and keys that will have 2025-08-26T19:55:58.1871850Z sparsity parameters saved 2025-08-26T19:55:58.1872315Z params_to_keep_per_layer: Dict to specify the params that should be 2025-08-26T19:55:58.1872816Z saved for specific layers. The keys in the dict 2025-08-26T19:55:58.1873267Z should be the module fqn, while the values should 2025-08-26T19:55:58.1873799Z be a list of strings with the names of the variables 2025-08-26T19:55:58.1874218Z to save in the `sparse_params` 2025-08-26T19:55:58.1874473Z 2025-08-26T19:55:58.1874565Z Examples: 2025-08-26T19:55:58.1874897Z >>> # xdoctest: +SKIP("locals are undefined") 2025-08-26T19:55:58.1875273Z >>> # Don't save any sparse params 2025-08-26T19:55:58.1875615Z >>> sparsifier.squash_mask() 2025-08-26T19:55:58.1875994Z >>> hasattr(model.submodule1, "sparse_params") 2025-08-26T19:55:58.1876346Z False 2025-08-26T19:55:58.1876487Z 2025-08-26T19:55:58.1876640Z >>> # Keep sparse params per layer 2025-08-26T19:55:58.1876977Z >>> sparsifier.squash_mask( 2025-08-26T19:55:58.1877319Z ... params_to_keep_per_layer={ 2025-08-26T19:55:58.1877686Z ... "submodule1.linear1": ("foo", "bar"), 2025-08-26T19:55:58.1878077Z ... "submodule2.linear42": ("baz",), 2025-08-26T19:55:58.1878420Z ... } 2025-08-26T19:55:58.1878650Z ... ) 2025-08-26T19:55:58.1878961Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T19:55:58.1879338Z {'foo': 42, 'bar': 24} 2025-08-26T19:55:58.1879702Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T19:55:58.1880064Z {'baz': 0.1} 2025-08-26T19:55:58.1880242Z 2025-08-26T19:55:58.1880368Z >>> # Keep sparse params for all layers 2025-08-26T19:55:58.1880794Z >>> sparsifier.squash_mask(params_to_keep=("foo", "bar")) 2025-08-26T19:55:58.1881252Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T19:55:58.1881617Z {'foo': 42, 'bar': 24} 2025-08-26T19:55:58.1881975Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T19:55:58.1882352Z {'foo': 42, 'bar': 24} 2025-08-26T19:55:58.1882545Z 2025-08-26T19:55:58.1882758Z >>> # Keep some sparse params for all layers, and specific ones for 2025-08-26T19:55:58.1883181Z >>> # some other layers 2025-08-26T19:55:58.1883501Z >>> sparsifier.squash_mask( 2025-08-26T19:55:58.1883844Z ... params_to_keep=("foo", "bar"), 2025-08-26T19:55:58.1884282Z ... params_to_keep_per_layer={"submodule2.linear42": ("baz",)}, 2025-08-26T19:55:58.1884685Z ... ) 2025-08-26T19:55:58.1885072Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T19:55:58.1885455Z {'foo': 42, 'bar': 24} 2025-08-26T19:55:58.1885822Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T19:55:58.1886217Z {'foo': 42, 'bar': 24, 'baz': 0.1} 2025-08-26T19:55:58.1886513Z 2025-08-26T19:55:58.1886899Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.1887289Z 2025-08-26T19:55:58.2934496Z msg = Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181. 2025-08-26T19:55:58.2935596Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.2936003Z 2025-08-26T19:55:58.2936262Z Config object that specifies the supported data types passed as arguments to 2025-08-26T19:55:58.2936891Z quantize ops in the reference model spec, for input and output activations, 2025-08-26T19:55:58.2937629Z weights, and biases. 2025-08-26T19:55:58.2937993Z 2025-08-26T19:55:58.2938171Z For example, consider the following reference model: 2025-08-26T19:55:58.2938447Z 2025-08-26T19:55:58.2938610Z quant1 - [dequant1 - fp32_linear - quant2] - dequant2 2025-08-26T19:55:58.2938894Z 2025-08-26T19:55:58.2939114Z The pattern in the square brackets refers to the reference pattern of 2025-08-26T19:55:58.2939696Z statically quantized linear. Setting the input dtype as `torch.quint8` 2025-08-26T19:55:58.2940295Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument 2025-08-26T19:55:58.2940984Z to the first quantize op (quant1). Similarly, setting the output dtype as 2025-08-26T19:55:58.2941555Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to 2025-08-26T19:55:58.2942023Z the second quantize op (quant2). 2025-08-26T19:55:58.2942241Z 2025-08-26T19:55:58.2942462Z Note that the dtype here does not refer to the interface dtypes of the 2025-08-26T19:55:58.2943028Z op. For example, the "input dtype" here is not the dtype of the input 2025-08-26T19:55:58.2943568Z tensor passed to the quantized linear op. Though it can still be the 2025-08-26T19:55:58.2944113Z same as the interface dtype, this is not always the case, e.g. the 2025-08-26T19:55:58.2944656Z interface dtype is fp32 in dynamic quantization but the "input dtype" 2025-08-26T19:55:58.2945216Z specified in the DTypeConfig would still be quint8. The semantics of 2025-08-26T19:55:58.2945774Z dtypes here are the same as the semantics of the dtypes specified in 2025-08-26T19:55:58.2946193Z the observers. 2025-08-26T19:55:58.2946343Z 2025-08-26T19:55:58.2946555Z These dtypes are matched against the ones specified in the user's 2025-08-26T19:55:58.2947106Z QConfig. If there is a match, and the QConfig satisfies the constraints 2025-08-26T19:55:58.2947673Z specified in the DTypeConfig (if any), then we will quantize the given 2025-08-26T19:55:58.2948236Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and 2025-08-26T19:55:58.2948699Z the pattern will not be quantized. 2025-08-26T19:55:58.2948921Z 2025-08-26T19:55:58.2949029Z Example usage:: 2025-08-26T19:55:58.2949169Z 2025-08-26T19:55:58.2949289Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:55:58.2949604Z >>> dtype_config1 = DTypeConfig( 2025-08-26T19:55:58.2949918Z ... input_dtype=torch.quint8, 2025-08-26T19:55:58.2950245Z ... output_dtype=torch.quint8, 2025-08-26T19:55:58.2950571Z ... weight_dtype=torch.qint8, 2025-08-26T19:55:58.2950894Z ... bias_dtype=torch.float) 2025-08-26T19:55:58.2951097Z 2025-08-26T19:55:58.2951208Z >>> dtype_config2 = DTypeConfig( 2025-08-26T19:55:58.2951553Z ... input_dtype=DTypeWithConstraints( 2025-08-26T19:55:58.2951898Z ... dtype=torch.quint8, 2025-08-26T19:55:58.2952211Z ... quant_min_lower_bound=0, 2025-08-26T19:55:58.2952531Z ... quant_max_upper_bound=255, 2025-08-26T19:55:58.2952837Z ... ), 2025-08-26T19:55:58.2953183Z ... output_dtype=DTypeWithConstraints( 2025-08-26T19:55:58.2953536Z ... dtype=torch.quint8, 2025-08-26T19:55:58.2953837Z ... quant_min_lower_bound=0, 2025-08-26T19:55:58.2954170Z ... quant_max_upper_bound=255, 2025-08-26T19:55:58.2954480Z ... ), 2025-08-26T19:55:58.2954748Z ... weight_dtype=DTypeWithConstraints( 2025-08-26T19:55:58.2955082Z ... dtype=torch.qint8, 2025-08-26T19:55:58.2955421Z ... quant_min_lower_bound=-128, 2025-08-26T19:55:58.2955764Z ... quant_max_upper_bound=127, 2025-08-26T19:55:58.2956074Z ... ), 2025-08-26T19:55:58.2956310Z ... bias_dtype=torch.float) 2025-08-26T19:55:58.2956656Z 2025-08-26T19:55:58.2956768Z >>> dtype_config1.input_dtype 2025-08-26T19:55:58.2957069Z torch.quint8 2025-08-26T19:55:58.2957211Z 2025-08-26T19:55:58.2957329Z >>> dtype_config2.input_dtype 2025-08-26T19:55:58.2957626Z torch.quint8 2025-08-26T19:55:58.2957767Z 2025-08-26T19:55:58.2957908Z >>> dtype_config2.input_dtype_with_constraints 2025-08-26T19:55:58.2958763Z DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None) 2025-08-26T19:55:58.2959442Z 2025-08-26T19:55:58.2959698Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.2960074Z 2025-08-26T19:55:58.4080130Z msg = Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24. 2025-08-26T19:55:58.4081440Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.4081836Z 2025-08-26T19:55:58.4082169Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into 2025-08-26T19:55:58.4082900Z with their models. The class works with all traceable GraphModules to help diagnose issues, 2025-08-26T19:55:58.4083641Z though the requirements on the type of model more-so depends on the specific report the user 2025-08-26T19:55:58.4084401Z is trying to generate. With respect to the reports, the ModelReport class is initialized with 2025-08-26T19:55:58.4085112Z a set of Detector classes, each of which generate reports on quantization configuration 2025-08-26T19:55:58.4085610Z issues a use might have. 2025-08-26T19:55:58.4085794Z 2025-08-26T19:55:58.4085927Z Currently supports generating reports on: 2025-08-26T19:55:58.4086407Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module) 2025-08-26T19:55:58.4087040Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules) 2025-08-26T19:55:58.4087737Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules) 2025-08-26T19:55:58.4088380Z - Suggestions for outlier detection for all layers (Graph Modules) 2025-08-26T19:55:58.4088709Z 2025-08-26T19:55:58.4089184Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver) 2025-08-26T19:55:58.4090112Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport 2025-08-26T19:55:58.4090999Z class compiles the report generated by each Detector class into a single report to return to the user. It also 2025-08-26T19:55:58.4091727Z has the capability to remove all the observers it inserted as well. 2025-08-26T19:55:58.4092056Z 2025-08-26T19:55:58.4092357Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule 2025-08-26T19:55:58.4092766Z 2025-08-26T19:55:58.4093150Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class 2025-08-26T19:55:58.4093980Z Make sure that these are all unique types of detectors [do not have more than 1 of the same class] 2025-08-26T19:55:58.4094431Z 2025-08-26T19:55:58.4094723Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors. 2025-08-26T19:55:58.4095453Z This set is generated by calling the get_detector_name() of each detector 2025-08-26T19:55:58.4095804Z 2025-08-26T19:55:58.4096158Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest 2025-08-26T19:55:58.4096935Z The purpose of this is to keep track of what observers were inserted for each detector, so that they 2025-08-26T19:55:58.4097500Z can be removed at the end if desired 2025-08-26T19:55:58.4097737Z 2025-08-26T19:55:58.4098063Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not 2025-08-26T19:55:58.4098752Z This is to ensure we only insert observers once with the ModelReport instance 2025-08-26T19:55:58.4099109Z 2025-08-26T19:55:58.4099378Z * :attr:`_removed_observers` A boolean to track if we have removed observers already 2025-08-26T19:55:58.4100173Z The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport 2025-08-26T19:55:58.4100913Z instance. This also allows the functionality where we can generate the report multiple times 2025-08-26T19:55:58.4101615Z as long as we haven't removed the observers yet. 2025-08-26T19:55:58.4101887Z 2025-08-26T19:55:58.4101970Z Note: 2025-08-26T19:55:58.4102397Z This class was initially designed to work with the Fx Graph Mode workflow in mind. However, 2025-08-26T19:55:58.4103153Z full functionality is available as long as there is a traceable GraphModule that is being used. 2025-08-26T19:55:58.4103968Z One method to get a traceable GraphModule without going through the Fx workflow is to use 2025-08-26T19:55:58.4104502Z the QuantizationTracer class. 2025-08-26T19:55:58.4104727Z 2025-08-26T19:55:58.4104836Z General Flow for Fx workflow: 2025-08-26T19:55:58.4105437Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model 2025-08-26T19:55:58.4106088Z 2.) Prepare your model with prepare_fx 2025-08-26T19:55:58.4106559Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers 2025-08-26T19:55:58.4107045Z 4.) Calibrate your model with data 2025-08-26T19:55:58.4107619Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers 2025-08-26T19:55:58.4108194Z Optional 2025-08-26T19:55:58.4108586Z 6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance 2025-08-26T19:55:58.4109240Z 7.) To help in parsing report information and debugging, view report info as a: 2025-08-26T19:55:58.4109708Z - Table 2025-08-26T19:55:58.4109948Z - Histogram 2025-08-26T19:55:58.4110191Z - Line plot 2025-08-26T19:55:58.4110656Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions 2025-08-26T19:55:58.4111114Z 2025-08-26T19:55:58.4111231Z Example (with QuantizationTracer): 2025-08-26T19:55:58.4111558Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.4111843Z >>> # get the necessary qconfig 2025-08-26T19:55:58.4112169Z >>> config = PrepareCustomConfig() 2025-08-26T19:55:58.4112559Z >>> skipped_module_names, skipped_module_classes = ( 2025-08-26T19:55:58.4112996Z ... get_skipped_module_name_and_classes(config, False) 2025-08-26T19:55:58.4113367Z ... ) 2025-08-26T19:55:58.4113486Z 2025-08-26T19:55:58.4113617Z >>> # initialize our model and get GraphModule 2025-08-26T19:55:58.4113971Z >>> model = SomeModel() 2025-08-26T19:55:58.4114416Z >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes) 2025-08-26T19:55:58.4114975Z >>> graph_module = GraphModule(model, tracer.trace(model)) 2025-08-26T19:55:58.4115265Z 2025-08-26T19:55:58.4115433Z >>> # get our set of detectors and ModelReport instance 2025-08-26T19:55:58.4115800Z >>> detector_set = set( 2025-08-26T19:55:58.4116070Z ... [ 2025-08-26T19:55:58.4116348Z ... DynamicStaticDetector(tolerance=0.5), 2025-08-26T19:55:58.4116800Z ... InputWeightEqualizationDetector(ratio_threshold=0.7), 2025-08-26T19:55:58.4117238Z ... ] 2025-08-26T19:55:58.4117458Z ... ) 2025-08-26T19:55:58.4117799Z >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set) 2025-08-26T19:55:58.4118135Z 2025-08-26T19:55:58.4118307Z >>> # now we insert the observers and calibrate the model 2025-08-26T19:55:58.4118836Z >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration() 2025-08-26T19:55:58.4119367Z >>> for i in range(num_callibration_batches): 2025-08-26T19:55:58.4119753Z >>> example_input = get_callibration_input() 2025-08-26T19:55:58.4120151Z >>> tracer_model_with_observers(example_input) 2025-08-26T19:55:58.4120400Z 2025-08-26T19:55:58.4120663Z >>> # finally we generate the reports and optionally remove the observers we inserted 2025-08-26T19:55:58.4121210Z >>> reports = tracer_reporter.generate_model_report( 2025-08-26T19:55:58.4121599Z ... remove_inserted_observers=True 2025-08-26T19:55:58.4121917Z ... ) 2025-08-26T19:55:58.4122073Z 2025-08-26T19:55:58.4122310Z >>> # Optional: we can generate the qconfig mapping based on the suggestions 2025-08-26T19:55:58.4122818Z >>> qconfigs = model_report.generate_qconfig_mapping() 2025-08-26T19:55:58.4123107Z 2025-08-26T19:55:58.4123356Z >>> # Optional: we can generate the equalization mapping based on the suggestions 2025-08-26T19:55:58.4123921Z >>> qconfigs = model_report.generate_equalization_mapping() 2025-08-26T19:55:58.4124217Z 2025-08-26T19:55:58.4124579Z >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired 2025-08-26T19:55:58.4125213Z >>> model_report_visualizer = tracer_reporter.generate_visualizer() 2025-08-26T19:55:58.4125543Z 2025-08-26T19:55:58.4125547Z 2025-08-26T19:55:58.4125805Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.4126194Z 2025-08-26T19:55:58.4166144Z msg = Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301. 2025-08-26T19:55:58.4167451Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.4167847Z 2025-08-26T19:55:58.4168125Z Takes in optional filter values and generates two tables with desired information. 2025-08-26T19:55:58.4168766Z 2025-08-26T19:55:58.4169219Z The generated tables are presented in both a list-of-lists format 2025-08-26T19:55:58.4169546Z 2025-08-26T19:55:58.4169775Z The reason for the two tables are that they handle different things: 2025-08-26T19:55:58.4170264Z 1.) the first table handles all tensor level information 2025-08-26T19:55:58.4170767Z 2.) the second table handles and displays all channel based information 2025-08-26T19:55:58.4171118Z 2025-08-26T19:55:58.4171441Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T19:55:58.4172230Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T19:55:58.4173081Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T19:55:58.4173745Z 2025-08-26T19:55:58.4173951Z Tensor table columns: 2025-08-26T19:55:58.4174539Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:55:58.4175006Z ---- --------- --------- --------- --------- --------- 2025-08-26T19:55:58.4175293Z 2025-08-26T19:55:58.4175409Z Per-Channel table columns: 2025-08-26T19:55:58.4175823Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:55:58.4176340Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T19:55:58.4176627Z 2025-08-26T19:55:58.4176710Z Args: 2025-08-26T19:55:58.4177389Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T19:55:58.4178173Z contain this filter substring 2025-08-26T19:55:58.4178570Z Default = "", results in all the features being printed 2025-08-26T19:55:58.4179128Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:55:58.4179765Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:55:58.4180154Z 2025-08-26T19:55:58.4180267Z Returns a dictionary with two keys: 2025-08-26T19:55:58.4180661Z (Dict[str, Tuple[List, List]]) A dict containing two keys: 2025-08-26T19:55:58.4181086Z "tensor_level_info", "channel_level_info" 2025-08-26T19:55:58.4181426Z Each key maps to a tuple with: 2025-08-26T19:55:58.4181771Z A list of the headers of each table 2025-08-26T19:55:58.4182190Z A list of lists containing the table information row by row 2025-08-26T19:55:58.4182671Z The 0th index row will contain the headers of the columns 2025-08-26T19:55:58.4183084Z The rest of the rows will contain data 2025-08-26T19:55:58.4183392Z 2025-08-26T19:55:58.4183483Z Example Use: 2025-08-26T19:55:58.4183746Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:58.4184140Z >>> mod_report_visualizer.generate_filtered_tables( 2025-08-26T19:55:58.4184606Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:55:58.4185298Z ... ) # generates table with per_channel_min info for all modules in block 1 of the model 2025-08-26T19:55:58.4185712Z 2025-08-26T19:55:58.4186056Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.4186445Z 2025-08-26T19:55:58.4187375Z msg = Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399. 2025-08-26T19:55:58.4188686Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.4189078Z 2025-08-26T19:55:58.4189366Z Takes in optional filter values and prints out formatted tables of the information. 2025-08-26T19:55:58.4189764Z 2025-08-26T19:55:58.4190122Z The reason for the two tables printed out instead of one large one are that they handle different things: 2025-08-26T19:55:58.4190748Z 1.) the first table handles all tensor level information 2025-08-26T19:55:58.4191250Z 2.) the second table handles and displays all channel based information 2025-08-26T19:55:58.4191600Z 2025-08-26T19:55:58.4191927Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T19:55:58.4192723Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T19:55:58.4193546Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T19:55:58.4194027Z 2025-08-26T19:55:58.4194127Z Tensor table columns: 2025-08-26T19:55:58.4194493Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:55:58.4194965Z ---- --------- --------- --------- --------- --------- 2025-08-26T19:55:58.4195234Z 2025-08-26T19:55:58.4195355Z Per-Channel table columns: 2025-08-26T19:55:58.4195538Z 2025-08-26T19:55:58.4195759Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:55:58.4196270Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T19:55:58.4196565Z 2025-08-26T19:55:58.4196649Z Args: 2025-08-26T19:55:58.4197043Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T19:55:58.4197551Z contain this filter substring 2025-08-26T19:55:58.4197928Z Default = "", results in all the features being printed 2025-08-26T19:55:58.4198484Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:55:58.4199203Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:55:58.4199580Z 2025-08-26T19:55:58.4199691Z Example Use: 2025-08-26T19:55:58.4199965Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:58.4200374Z >>> mod_report_visualizer.generate_table_visualization( 2025-08-26T19:55:58.4200862Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:55:58.4201271Z ... ) 2025-08-26T19:55:58.4201600Z >>> # prints out neatly formatted table with per_channel_min info 2025-08-26T19:55:58.4202038Z >>> # for all modules in block 1 of the model 2025-08-26T19:55:58.4202291Z 2025-08-26T19:55:58.4202546Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.4202938Z 2025-08-26T19:55:58.4203893Z msg = Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564. 2025-08-26T19:55:58.4205241Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.4205640Z 2025-08-26T19:55:58.4205883Z Takes in a feature and optional module_filter and plots of the desired data. 2025-08-26T19:55:58.4206241Z 2025-08-26T19:55:58.4206531Z For per channel features, it averages the value across the channels and plots a point 2025-08-26T19:55:58.4207204Z per module. The reason for this is that for models with hundreds of channels, it can 2025-08-26T19:55:58.4207917Z be hard to differentiate one channel line from another, and so the point of generating 2025-08-26T19:55:58.4208606Z a single average point per module is to give a sense of general trends that encourage 2025-08-26T19:55:58.4209190Z further deep dives. 2025-08-26T19:55:58.4209341Z 2025-08-26T19:55:58.4209439Z Note: 2025-08-26T19:55:58.4209822Z Only features in the report that have tensor value data are plottable by this class 2025-08-26T19:55:58.4210390Z When the tensor information is plotted, it will plot: 2025-08-26T19:55:58.4210819Z idx as the x val, feature value as the y_val 2025-08-26T19:55:58.4211244Z When the channel information is plotted, it will plot: 2025-08-26T19:55:58.4211802Z the first idx of each module as the x val, feature value as the y_val [for each channel] 2025-08-26T19:55:58.4212414Z The reason for this is that we want to be able to compare values across the 2025-08-26T19:55:58.4213010Z channels for same layer, and it will be hard if values are staggered by idx 2025-08-26T19:55:58.4213551Z This means each module is represented by only 1 x value 2025-08-26T19:55:58.4213927Z Args: 2025-08-26T19:55:58.4214268Z feature_filter (str): Filters the features presented to only those that 2025-08-26T19:55:58.4214733Z contain this filter substring 2025-08-26T19:55:58.4215217Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:55:58.4215864Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:55:58.4216238Z 2025-08-26T19:55:58.4216342Z Example Use: 2025-08-26T19:55:58.4216605Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:58.4217021Z >>> mod_report_visualizer.generate_plot_visualization( 2025-08-26T19:55:58.4217506Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:55:58.4217917Z ... ) 2025-08-26T19:55:58.4218217Z >>> # outputs line plot of per_channel_min information for all 2025-08-26T19:55:58.4218711Z >>> # modules in block1 of model each channel gets it's own line, 2025-08-26T19:55:58.4219201Z >>> # and it's plotted across the in-order modules on the x-axis 2025-08-26T19:55:58.4219493Z 2025-08-26T19:55:58.4219762Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.4220134Z 2025-08-26T19:55:58.4221101Z msg = Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643. 2025-08-26T19:55:58.4222462Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.4222858Z 2025-08-26T19:55:58.4223139Z Takes in a feature and optional module_filter and plots the histogram of desired data. 2025-08-26T19:55:58.4223557Z 2025-08-26T19:55:58.4223641Z Note: 2025-08-26T19:55:58.4224031Z Only features in the report that have tensor value data can be viewed as a histogram 2025-08-26T19:55:58.4224703Z If you want to plot a histogram from all the channel values of a specific feature for 2025-08-26T19:55:58.4225338Z a specific model, make sure to specify both the model and the feature properly 2025-08-26T19:55:58.4225967Z in the filters and you should be able to see a distribution of the channel data 2025-08-26T19:55:58.4226353Z 2025-08-26T19:55:58.4226437Z Args: 2025-08-26T19:55:58.4226826Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T19:55:58.4227367Z contain this filter substring 2025-08-26T19:55:58.4227741Z Default = "", results in all the features being printed 2025-08-26T19:55:58.4228292Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:55:58.4228933Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:55:58.4229538Z num_bins (int, optional): The number of bins to create the histogram with 2025-08-26T19:55:58.4230125Z Default = 10, the values will be split into 10 equal sized bins 2025-08-26T19:55:58.4230452Z 2025-08-26T19:55:58.4230542Z Example Use: 2025-08-26T19:55:58.4230779Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.4231265Z >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization( 2025-08-26T19:55:58.4231886Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:55:58.4232301Z ... ) 2025-08-26T19:55:58.4232706Z # outputs histogram of per_channel_min information for all modules in block1 of model 2025-08-26T19:55:58.4233375Z information is gathered across all channels for all modules in block 1 for the 2025-08-26T19:55:58.4233986Z per_channel_min and is displayed in a histogram of equally sized bins 2025-08-26T19:55:58.4234326Z 2025-08-26T19:55:58.4234580Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.4234964Z 2025-08-26T19:55:58.5618074Z msg = Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py line=734. 2025-08-26T19:55:58.5619037Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.5619821Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler. 2025-08-26T19:55:58.5620521Z Label will only appear if CPU activity tracing is enabled. 2025-08-26T19:55:58.5620824Z 2025-08-26T19:55:58.5620972Z It is useful when tracing the code profile. 2025-08-26T19:55:58.5621216Z 2025-08-26T19:55:58.5621302Z Args: 2025-08-26T19:55:58.5621572Z name (str): Label assigned to the block of code. 2025-08-26T19:55:58.5622021Z node_id (int): ID of node, for distributed profiling. Unset in 2025-08-26T19:55:58.5622439Z non-distributed cases. 2025-08-26T19:55:58.5622631Z 2025-08-26T19:55:58.5622718Z Example: 2025-08-26T19:55:58.5623048Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER) 2025-08-26T19:55:58.5623488Z >>> x = torch.randn((1, 1), requires_grad=True) 2025-08-26T19:55:58.5623905Z >>> with torch.autograd.profiler.profile() as prof: 2025-08-26T19:55:58.5624279Z ... y = x**2 2025-08-26T19:55:58.5624626Z ... with torch.autograd.profiler.record_function( 2025-08-26T19:55:58.5625195Z ... "label-z" 2025-08-26T19:55:58.5625488Z ... ): # label the block 2025-08-26T19:55:58.5625792Z ... z = y**3 2025-08-26T19:55:58.5626057Z ... y.backward() 2025-08-26T19:55:58.5626343Z >>> # xdoctest: +IGNORE_WANT 2025-08-26T19:55:58.5626693Z >>> # NOTE: some columns were removed for brevity 2025-08-26T19:55:58.5627154Z >>> print(prof.key_averages().table(sort_by="self_cpu_time_total")) 2025-08-26T19:55:58.5627680Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T19:55:58.5628192Z Name Self CPU total % CPU time avg Number of Calls 2025-08-26T19:55:58.5628702Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T19:55:58.5629162Z pow 60.77% 47.470us 3 2025-08-26T19:55:58.5629557Z mul 21.73% 25.465us 2 2025-08-26T19:55:58.5630042Z PowBackward0 12.03% 121.891us 1 2025-08-26T19:55:58.5630594Z torch::autograd::AccumulateGrad 2.70% 6.324us 1 2025-08-26T19:55:58.5631092Z label-z 2.13% 12.421us 1 2025-08-26T19:55:58.5631579Z torch::autograd::GraphRoot 0.64% 1.503us 1 2025-08-26T19:55:58.5632093Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T19:55:58.5632627Z Self CPU time total: 234.344us 2025-08-26T19:55:58.5632958Z CUDA time total: 0.000us 2025-08-26T19:55:58.5633152Z 2025-08-26T19:55:58.5633264Z 2025-08-26T19:55:58.5633645Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.5634020Z 2025-08-26T19:55:58.7349869Z msg = Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py line=721. 2025-08-26T19:55:58.7350882Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:55:58.7351270Z 2025-08-26T19:55:58.7351544Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-08-26T19:55:58.7352243Z The submesh created consists of the dimensions and the communicators indicated by 2025-08-26T19:55:58.7352737Z ``mesh_dim_names`` 2025-08-26T19:55:58.7352888Z 2025-08-26T19:55:58.7352988Z Args: 2025-08-26T19:55:58.7353350Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-08-26T19:55:58.7353907Z mesh dimension of the DeviceMesh to create the submesh for. 2025-08-26T19:55:58.7354303Z Returns: 2025-08-26T19:55:58.7354534Z A :class:`DeviceMesh` object 2025-08-26T19:55:58.7354728Z 2025-08-26T19:55:58.7355015Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-08-26T19:55:58.7355528Z In the first example: 2025-08-26T19:55:58.7355957Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-08-26T19:55:58.7356588Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-08-26T19:55:58.7357195Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-08-26T19:55:58.7357763Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-08-26T19:55:58.7358347Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-08-26T19:55:58.7358925Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-08-26T19:55:58.7359276Z 2025-08-26T19:55:58.7359395Z In the second example: 2025-08-26T19:55:58.7359844Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-08-26T19:55:58.7360497Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-08-26T19:55:58.7361312Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-08-26T19:55:58.7361975Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-08-26T19:55:58.7362360Z 2025-08-26T19:55:58.7362479Z Example:: 2025-08-26T19:55:58.7362604Z 2025-08-26T19:55:58.7362721Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T19:55:58.7363096Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-08-26T19:55:58.7363482Z >>> 2025-08-26T19:55:58.7363808Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-08-26T19:55:58.7364277Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-08-26T19:55:58.7364778Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T19:55:58.7365265Z >>> tp_mesh = mesh_2d["tp"] 2025-08-26T19:55:58.7365561Z >>> dp_mesh = mesh_2d["dp"] 2025-08-26T19:55:58.7365908Z >>> 2025-08-26T19:55:58.7366122Z >>> # Initialize a 3D mesh. 2025-08-26T19:55:58.7366605Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-08-26T19:55:58.7367326Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-08-26T19:55:58.7367881Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-08-26T19:55:58.7368209Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-08-26T19:55:58.7368442Z 2025-08-26T19:55:58.7369329Z Original Error: SyntaxError('positional argument follows keyword argument', ('', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83)) 2025-08-26T19:55:58.7370150Z 2025-08-26T19:55:58.7370401Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T19:55:58.7370904Z ^ 2025-08-26T19:55:58.7701942Z msg = Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2710. 2025-08-26T19:55:58.7702979Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.7703365Z 2025-08-26T19:55:58.7703635Z Send or Receive a batch of tensors asynchronously and return a list of requests. 2025-08-26T19:55:58.7704006Z 2025-08-26T19:55:58.7704254Z Process each of the operations in ``p2p_op_list`` and return the corresponding 2025-08-26T19:55:58.7704839Z requests. NCCL, Gloo, and UCC backend are currently supported. 2025-08-26T19:55:58.7705162Z 2025-08-26T19:55:58.7705246Z Args: 2025-08-26T19:55:58.7705600Z p2p_op_list: A list of point-to-point operations(type of each operator is 2025-08-26T19:55:58.7706187Z ``torch.distributed.P2POp``). The order of the isend/irecv in the list 2025-08-26T19:55:58.7706747Z matters and it needs to match with corresponding isend/irecv on the 2025-08-26T19:55:58.7707184Z remote end. 2025-08-26T19:55:58.7707330Z 2025-08-26T19:55:58.7707427Z Returns: 2025-08-26T19:55:58.7707802Z A list of distributed request objects returned by calling the corresponding 2025-08-26T19:55:58.7708266Z op in the op_list. 2025-08-26T19:55:58.7708528Z 2025-08-26T19:55:58.7708660Z Examples: 2025-08-26T19:55:58.7708935Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T19:55:58.7709453Z >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank 2025-08-26T19:55:58.7710337Z >>> recv_tensor = torch.randn(2, dtype=torch.float32) 2025-08-26T19:55:58.7710851Z >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size) 2025-08-26T19:55:58.7711295Z >>> recv_op = dist.P2POp( 2025-08-26T19:55:58.7711688Z ... dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size 2025-08-26T19:55:58.7712091Z ... ) 2025-08-26T19:55:58.7712345Z >>> reqs = batch_isend_irecv([send_op, recv_op]) 2025-08-26T19:55:58.7712831Z >>> for req in reqs: 2025-08-26T19:55:58.7713099Z >>> req.wait() 2025-08-26T19:55:58.7713341Z >>> recv_tensor 2025-08-26T19:55:58.7713597Z tensor([2, 3]) # Rank 0 2025-08-26T19:55:58.7713886Z tensor([0, 1]) # Rank 1 2025-08-26T19:55:58.7714068Z 2025-08-26T19:55:58.7714347Z .. note:: Note that when this API is used with the NCCL PG backend, users must set 2025-08-26T19:55:58.7714948Z the current GPU device with `torch.cuda.set_device`, otherwise it will 2025-08-26T19:55:58.7715398Z lead to unexpected hang issues. 2025-08-26T19:55:58.7715628Z 2025-08-26T19:55:58.7715840Z In addition, if this API is the first collective call in the ``group`` 2025-08-26T19:55:58.7716407Z passed to ``dist.P2POp``, all ranks of the ``group`` must participate in 2025-08-26T19:55:58.7716986Z this API call; otherwise, the behavior is undefined. If this API call is 2025-08-26T19:55:58.7717552Z not the first collective call in the ``group``, batched P2P operations 2025-08-26T19:55:58.7718168Z involving only a subset of ranks of the ``group`` are allowed. 2025-08-26T19:55:58.7718491Z 2025-08-26T19:55:58.7718746Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.7719135Z 2025-08-26T19:55:58.7719756Z msg = Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2842. 2025-08-26T19:55:58.7720728Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.7721114Z 2025-08-26T19:55:58.7721492Z Reduces the tensor data across all machines in a way that all get the final result. 2025-08-26T19:55:58.7721890Z 2025-08-26T19:55:58.7722135Z After the call ``tensor`` is going to be bitwise identical in all processes. 2025-08-26T19:55:58.7722489Z 2025-08-26T19:55:58.7722604Z Complex tensors are supported. 2025-08-26T19:55:58.7722816Z 2025-08-26T19:55:58.7722903Z Args: 2025-08-26T19:55:58.7723236Z tensor (Tensor): Input and output of the collective. The function 2025-08-26T19:55:58.7723676Z operates in-place. 2025-08-26T19:55:58.7723970Z op (optional): One of the values from 2025-08-26T19:55:58.7724330Z ``torch.distributed.ReduceOp`` 2025-08-26T19:55:58.7724770Z enum. Specifies an operation used for element-wise reductions. 2025-08-26T19:55:58.7725343Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:55:58.7725823Z the default process group will be used. 2025-08-26T19:55:58.7726277Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T19:55:58.7726704Z 2025-08-26T19:55:58.7726837Z Returns: 2025-08-26T19:55:58.7727172Z Async work handle, if async_op is set to True. 2025-08-26T19:55:58.7727627Z None, if not async_op or if not part of the group 2025-08-26T19:55:58.7728057Z 2025-08-26T19:55:58.7728232Z Examples: 2025-08-26T19:55:58.7728672Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T19:55:58.7729152Z >>> # All tensors below are of torch.int64 type. 2025-08-26T19:55:58.7729527Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:55:58.7729870Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T19:55:58.7730340Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T19:55:58.7730785Z >>> tensor 2025-08-26T19:55:58.7731041Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T19:55:58.7731374Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T19:55:58.7731732Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T19:55:58.7732071Z >>> tensor 2025-08-26T19:55:58.7732325Z tensor([4, 6], device='cuda:0') # Rank 0 2025-08-26T19:55:58.7732652Z tensor([4, 6], device='cuda:1') # Rank 1 2025-08-26T19:55:58.7732883Z 2025-08-26T19:55:58.7733024Z >>> # All tensors below are of torch.cfloat type. 2025-08-26T19:55:58.7733401Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:55:58.7733806Z >>> tensor = torch.tensor( 2025-08-26T19:55:58.7734141Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T19:55:58.7734511Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T19:55:58.7734787Z >>> tensor 2025-08-26T19:55:58.7735070Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T19:55:58.7735470Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T19:55:58.7735848Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T19:55:58.7736185Z >>> tensor 2025-08-26T19:55:58.7736462Z tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0 2025-08-26T19:55:58.7736859Z tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1 2025-08-26T19:55:58.7737107Z 2025-08-26T19:55:58.7737112Z 2025-08-26T19:55:58.7737526Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.7737917Z 2025-08-26T19:55:58.7738566Z msg = Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3202. 2025-08-26T19:55:58.7739616Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.7740019Z 2025-08-26T19:55:58.7740248Z Gathers picklable objects from the whole group in a single process. 2025-08-26T19:55:58.7740606Z 2025-08-26T19:55:58.7740844Z Similar to :func:`gather`, but Python objects can be passed in. Note that the 2025-08-26T19:55:58.7741364Z object must be picklable in order to be gathered. 2025-08-26T19:55:58.7741627Z 2025-08-26T19:55:58.7741727Z Args: 2025-08-26T19:55:58.7742053Z obj (Any): Input object. Must be picklable. 2025-08-26T19:55:58.7742518Z object_gather_list (list[Any]): Output list. On the ``dst`` rank, it 2025-08-26T19:55:58.7743047Z should be correctly sized as the size of the group for this 2025-08-26T19:55:58.7743579Z collective and will contain the output. Must be ``None`` on non-dst 2025-08-26T19:55:58.7744022Z ranks. (default is ``None``) 2025-08-26T19:55:58.7744571Z dst (int, optional): Destination rank on global process group (regardless of ``group`` argument). 2025-08-26T19:55:58.7745223Z (If both ``dst`` and ``group_dst`` are None, default is global rank 0) 2025-08-26T19:55:58.7745789Z group: (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:55:58.7746341Z the default process group will be used. Default is ``None``. 2025-08-26T19:55:58.7746989Z group_dst (int, optional): Destination rank on ``group``. Invalid to specify both ``dst`` and ``group_dst`` 2025-08-26T19:55:58.7747468Z 2025-08-26T19:55:58.7747557Z Returns: 2025-08-26T19:55:58.7747868Z None. On the ``dst`` rank, ``object_gather_list`` will contain the 2025-08-26T19:55:58.7748282Z output of the collective. 2025-08-26T19:55:58.7748474Z 2025-08-26T19:55:58.7748697Z .. note:: Note that this API differs slightly from the gather collective 2025-08-26T19:55:58.7749251Z since it does not provide an async_op handle and thus will be a blocking 2025-08-26T19:55:58.7749692Z call. 2025-08-26T19:55:58.7749812Z 2025-08-26T19:55:58.7750062Z .. note:: For NCCL-based processed groups, internal tensor representations 2025-08-26T19:55:58.7750637Z of objects must be moved to the GPU device before communication takes 2025-08-26T19:55:58.7751114Z place. In this case, the device used is given by 2025-08-26T19:55:58.7751601Z ``torch.cuda.current_device()`` and it is the user's responsibility to 2025-08-26T19:55:58.7752156Z ensure that this is set so that each rank has an individual GPU, via 2025-08-26T19:55:58.7752602Z ``torch.cuda.set_device()``. 2025-08-26T19:55:58.7752799Z 2025-08-26T19:55:58.7752887Z .. warning:: 2025-08-26T19:55:58.7753265Z Object collectives have a number of serious performance and scalability 2025-08-26T19:55:58.7753811Z limitations. See :ref:`object_collectives` for details. 2025-08-26T19:55:58.7754103Z 2025-08-26T19:55:58.7754205Z .. warning:: 2025-08-26T19:55:58.7754579Z :func:`gather_object` uses ``pickle`` module implicitly, which is 2025-08-26T19:55:58.7755126Z known to be insecure. It is possible to construct malicious pickle data 2025-08-26T19:55:58.7755695Z which will execute arbitrary code during unpickling. Only call this 2025-08-26T19:55:58.7756150Z function with data you trust. 2025-08-26T19:55:58.7756355Z 2025-08-26T19:55:58.7756455Z .. warning:: 2025-08-26T19:55:58.7756797Z Calling :func:`gather_object` with GPU tensors is not well supported 2025-08-26T19:55:58.7757376Z and inefficient as it incurs GPU -> CPU transfer since tensors would be 2025-08-26T19:55:58.7757913Z pickled. Please consider using :func:`gather` instead. 2025-08-26T19:55:58.7758196Z 2025-08-26T19:55:58.7758302Z Example:: 2025-08-26T19:55:58.7758560Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T19:55:58.7759002Z >>> # Note: Process group initialization omitted on each rank. 2025-08-26T19:55:58.7759425Z >>> import torch.distributed as dist 2025-08-26T19:55:58.7759763Z >>> # Assumes world_size of 3. 2025-08-26T19:55:58.7760180Z >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object 2025-08-26T19:55:58.7760590Z >>> output = [None for _ in gather_objects] 2025-08-26T19:55:58.7760933Z >>> dist.gather_object( 2025-08-26T19:55:58.7761238Z ... gather_objects[dist.get_rank()], 2025-08-26T19:55:58.7761611Z ... output if dist.get_rank() == 0 else None, 2025-08-26T19:55:58.7761941Z ... dst=0 2025-08-26T19:55:58.7762177Z ... ) 2025-08-26T19:55:58.7762398Z >>> # On rank 0 2025-08-26T19:55:58.7762637Z >>> output 2025-08-26T19:55:58.7762907Z ['foo', 12, {1: 2}] 2025-08-26T19:55:58.7763077Z 2025-08-26T19:55:58.7763333Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.7763710Z 2025-08-26T19:55:58.7770615Z msg = Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3798. 2025-08-26T19:55:58.7771599Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.7771993Z 2025-08-26T19:55:58.7772149Z Gathers tensors from the whole group in a list. 2025-08-26T19:55:58.7772405Z 2025-08-26T19:55:58.7772553Z Complex and uneven sized tensors are supported. 2025-08-26T19:55:58.7772843Z 2025-08-26T19:55:58.7772928Z Args: 2025-08-26T19:55:58.7773238Z tensor_list (list[Tensor]): Output list. It should contain 2025-08-26T19:55:58.7773766Z correctly-sized tensors to be used for output of the collective. 2025-08-26T19:55:58.7774239Z Uneven sized tensors are supported. 2025-08-26T19:55:58.7774657Z tensor (Tensor): Tensor to be broadcast from current process. 2025-08-26T19:55:58.7775210Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:55:58.7775699Z the default process group will be used. 2025-08-26T19:55:58.7776147Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T19:55:58.7776465Z 2025-08-26T19:55:58.7776553Z Returns: 2025-08-26T19:55:58.7776816Z Async work handle, if async_op is set to True. 2025-08-26T19:55:58.7777225Z None, if not async_op or if not part of the group 2025-08-26T19:55:58.7777481Z 2025-08-26T19:55:58.7777578Z Examples: 2025-08-26T19:55:58.7777847Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T19:55:58.7778230Z >>> # All tensors below are of torch.int64 dtype. 2025-08-26T19:55:58.7778600Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:55:58.7778953Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T19:55:58.7779285Z >>> tensor_list = [ 2025-08-26T19:55:58.7779653Z ... torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2) 2025-08-26T19:55:58.7780074Z ... ] 2025-08-26T19:55:58.7780290Z >>> tensor_list 2025-08-26T19:55:58.7780648Z [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0 2025-08-26T19:55:58.7781161Z [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1 2025-08-26T19:55:58.7781793Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T19:55:58.7782241Z >>> tensor 2025-08-26T19:55:58.7782499Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T19:55:58.7782836Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T19:55:58.7783183Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T19:55:58.7783503Z >>> tensor_list 2025-08-26T19:55:58.7783852Z [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0 2025-08-26T19:55:58.7784367Z [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1 2025-08-26T19:55:58.7784695Z 2025-08-26T19:55:58.7784840Z >>> # All tensors below are of torch.cfloat dtype. 2025-08-26T19:55:58.7785221Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:55:58.7785547Z >>> tensor_list = [ 2025-08-26T19:55:58.7785928Z ... torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2) 2025-08-26T19:55:58.7786386Z ... ] 2025-08-26T19:55:58.7786602Z >>> tensor_list 2025-08-26T19:55:58.7787006Z [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0 2025-08-26T19:55:58.7787631Z [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1 2025-08-26T19:55:58.7788094Z >>> tensor = torch.tensor( 2025-08-26T19:55:58.7788447Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T19:55:58.7788818Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T19:55:58.7789092Z >>> tensor 2025-08-26T19:55:58.7789439Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T19:55:58.7789838Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T19:55:58.7790217Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T19:55:58.7790544Z >>> tensor_list 2025-08-26T19:55:58.7790926Z [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0 2025-08-26T19:55:58.7791546Z [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1 2025-08-26T19:55:58.7791926Z 2025-08-26T19:55:58.7791930Z 2025-08-26T19:55:58.7792189Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.7792574Z 2025-08-26T19:55:58.7829982Z msg = Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4504. 2025-08-26T19:55:58.7831320Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.7831707Z 2025-08-26T19:55:58.7831982Z Split input tensor and then scatter the split list to all processes in a group. 2025-08-26T19:55:58.7832363Z 2025-08-26T19:55:58.7832644Z Later the received tensors are concatenated from all the processes in the group 2025-08-26T19:55:58.7833147Z and returned as a single output tensor. 2025-08-26T19:55:58.7833390Z 2025-08-26T19:55:58.7833501Z Complex tensors are supported. 2025-08-26T19:55:58.7833710Z 2025-08-26T19:55:58.7833790Z Args: 2025-08-26T19:55:58.7834078Z output (Tensor): Gathered concatenated output tensor. 2025-08-26T19:55:58.7834475Z input (Tensor): Input tensor to scatter. 2025-08-26T19:55:58.7834937Z output_split_sizes: (list[Int], optional): Output split sizes for dim 0 2025-08-26T19:55:58.7835497Z if specified None or empty, dim 0 of ``output`` tensor must divide 2025-08-26T19:55:58.7835939Z equally by ``world_size``. 2025-08-26T19:55:58.7836355Z input_split_sizes: (list[Int], optional): Input split sizes for dim 0 2025-08-26T19:55:58.7836902Z if specified None or empty, dim 0 of ``input`` tensor must divide 2025-08-26T19:55:58.7837332Z equally by ``world_size``. 2025-08-26T19:55:58.7837917Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:55:58.7838406Z the default process group will be used. 2025-08-26T19:55:58.7838939Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T19:55:58.7839272Z 2025-08-26T19:55:58.7839358Z Returns: 2025-08-26T19:55:58.7839629Z Async work handle, if async_op is set to True. 2025-08-26T19:55:58.7840061Z None, if not async_op or if not part of the group. 2025-08-26T19:55:58.7840320Z 2025-08-26T19:55:58.7840431Z .. warning:: 2025-08-26T19:55:58.7840728Z `all_to_all_single` is experimental and subject to change. 2025-08-26T19:55:58.7841027Z 2025-08-26T19:55:58.7841113Z Examples: 2025-08-26T19:55:58.7841459Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T19:55:58.7841857Z >>> input = torch.arange(4) + rank * 4 2025-08-26T19:55:58.7842174Z >>> input 2025-08-26T19:55:58.7842440Z tensor([0, 1, 2, 3]) # Rank 0 2025-08-26T19:55:58.7842751Z tensor([4, 5, 6, 7]) # Rank 1 2025-08-26T19:55:58.7843090Z tensor([8, 9, 10, 11]) # Rank 2 2025-08-26T19:55:58.7843581Z tensor([12, 13, 14, 15]) # Rank 3 2025-08-26T19:55:58.7844151Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T19:55:58.7844841Z >>> dist.all_to_all_single(output, input) 2025-08-26T19:55:58.7845197Z >>> output 2025-08-26T19:55:58.7845439Z tensor([0, 4, 8, 12]) # Rank 0 2025-08-26T19:55:58.7845744Z tensor([1, 5, 9, 13]) # Rank 1 2025-08-26T19:55:58.7846059Z tensor([2, 6, 10, 14]) # Rank 2 2025-08-26T19:55:58.7846369Z tensor([3, 7, 11, 15]) # Rank 3 2025-08-26T19:55:58.7846570Z 2025-08-26T19:55:58.7846754Z >>> # Essentially, it is similar to following operation: 2025-08-26T19:55:58.7847258Z >>> scatter_list = list(input.chunk(world_size)) 2025-08-26T19:55:58.7847664Z >>> gather_list = list(output.chunk(world_size)) 2025-08-26T19:55:58.7848034Z >>> for i in range(world_size): 2025-08-26T19:55:58.7848486Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i) 2025-08-26T19:55:58.7848921Z 2025-08-26T19:55:58.7849043Z >>> # Another example with uneven split 2025-08-26T19:55:58.7849374Z >>> input 2025-08-26T19:55:58.7849673Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T19:55:58.7850120Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T19:55:58.7850572Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T19:55:58.7851010Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T19:55:58.7851399Z >>> input_splits 2025-08-26T19:55:58.7851687Z [2, 2, 1, 1] # Rank 0 2025-08-26T19:55:58.7852064Z [3, 2, 2, 2] # Rank 1 2025-08-26T19:55:58.7852421Z [2, 1, 1, 1] # Rank 2 2025-08-26T19:55:58.7852788Z [2, 2, 2, 1] # Rank 3 2025-08-26T19:55:58.7853130Z >>> output_splits 2025-08-26T19:55:58.7853418Z [2, 3, 2, 2] # Rank 0 2025-08-26T19:55:58.7853779Z [2, 2, 1, 2] # Rank 1 2025-08-26T19:55:58.7854147Z [1, 2, 1, 2] # Rank 2 2025-08-26T19:55:58.7854597Z [1, 2, 1, 1] # Rank 3 2025-08-26T19:55:58.7854935Z >>> output = ... 2025-08-26T19:55:58.7855310Z >>> dist.all_to_all_single(output, input, output_splits, input_splits) 2025-08-26T19:55:58.7855722Z >>> output 2025-08-26T19:55:58.7856034Z tensor([ 0, 1, 10, 11, 12, 20, 21, 30, 31]) # Rank 0 2025-08-26T19:55:58.7856479Z tensor([ 2, 3, 13, 14, 22, 32, 33]) # Rank 1 2025-08-26T19:55:58.7856926Z tensor([ 4, 15, 16, 23, 34, 35]) # Rank 2 2025-08-26T19:55:58.7857355Z tensor([ 5, 17, 18, 24, 36]) # Rank 3 2025-08-26T19:55:58.7857690Z 2025-08-26T19:55:58.7857697Z 2025-08-26T19:55:58.7857859Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T19:55:58.7858249Z >>> input = torch.tensor( 2025-08-26T19:55:58.7858584Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T19:55:58.7858945Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T19:55:58.7859208Z >>> input 2025-08-26T19:55:58.7859526Z tensor([1+1j, 2+2j, 3+3j, 4+4j]) # Rank 0 2025-08-26T19:55:58.7859998Z tensor([5+5j, 6+6j, 7+7j, 8+8j]) # Rank 1 2025-08-26T19:55:58.7860485Z tensor([9+9j, 10+10j, 11+11j, 12+12j]) # Rank 2 2025-08-26T19:55:58.7860965Z tensor([13+13j, 14+14j, 15+15j, 16+16j]) # Rank 3 2025-08-26T19:55:58.7861421Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T19:55:58.7861808Z >>> dist.all_to_all_single(output, input) 2025-08-26T19:55:58.7862139Z >>> output 2025-08-26T19:55:58.7862451Z tensor([1+1j, 5+5j, 9+9j, 13+13j]) # Rank 0 2025-08-26T19:55:58.7862969Z tensor([2+2j, 6+6j, 10+10j, 14+14j]) # Rank 1 2025-08-26T19:55:58.7863452Z tensor([3+3j, 7+7j, 11+11j, 15+15j]) # Rank 2 2025-08-26T19:55:58.7863932Z tensor([4+4j, 8+8j, 12+12j, 16+16j]) # Rank 3 2025-08-26T19:55:58.7864228Z 2025-08-26T19:55:58.7864499Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.7864873Z 2025-08-26T19:55:58.7865554Z msg = Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4646. 2025-08-26T19:55:58.7866514Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.7866899Z 2025-08-26T19:55:58.7867270Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list. 2025-08-26T19:55:58.7867782Z 2025-08-26T19:55:58.7867897Z Complex tensors are supported. 2025-08-26T19:55:58.7868108Z 2025-08-26T19:55:58.7868191Z Args: 2025-08-26T19:55:58.7868540Z output_tensor_list (list[Tensor]): List of tensors to be gathered one 2025-08-26T19:55:58.7868972Z per rank. 2025-08-26T19:55:58.7869340Z input_tensor_list (list[Tensor]): List of tensors to scatter one per rank. 2025-08-26T19:55:58.7869935Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:55:58.7870424Z the default process group will be used. 2025-08-26T19:55:58.7870873Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T19:55:58.7871189Z 2025-08-26T19:55:58.7871274Z Returns: 2025-08-26T19:55:58.7871539Z Async work handle, if async_op is set to True. 2025-08-26T19:55:58.7871943Z None, if not async_op or if not part of the group. 2025-08-26T19:55:58.7872200Z 2025-08-26T19:55:58.7872308Z .. warning:: 2025-08-26T19:55:58.7872580Z `all_to_all` is experimental and subject to change. 2025-08-26T19:55:58.7872853Z 2025-08-26T19:55:58.7872940Z Examples: 2025-08-26T19:55:58.7873186Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T19:55:58.7873533Z >>> input = torch.arange(4) + rank * 4 2025-08-26T19:55:58.7873867Z >>> input = list(input.chunk(4)) 2025-08-26T19:55:58.7874156Z >>> input 2025-08-26T19:55:58.7874463Z [tensor([0]), tensor([1]), tensor([2]), tensor([3])] # Rank 0 2025-08-26T19:55:58.7874926Z [tensor([4]), tensor([5]), tensor([6]), tensor([7])] # Rank 1 2025-08-26T19:55:58.7875389Z [tensor([8]), tensor([9]), tensor([10]), tensor([11])] # Rank 2 2025-08-26T19:55:58.7875840Z [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3 2025-08-26T19:55:58.7876323Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T19:55:58.7876747Z >>> dist.all_to_all(output, input) 2025-08-26T19:55:58.7877063Z >>> output 2025-08-26T19:55:58.7877390Z [tensor([0]), tensor([4]), tensor([8]), tensor([12])] # Rank 0 2025-08-26T19:55:58.7877854Z [tensor([1]), tensor([5]), tensor([9]), tensor([13])] # Rank 1 2025-08-26T19:55:58.7878315Z [tensor([2]), tensor([6]), tensor([10]), tensor([14])] # Rank 2 2025-08-26T19:55:58.7878773Z [tensor([3]), tensor([7]), tensor([11]), tensor([15])] # Rank 3 2025-08-26T19:55:58.7879055Z 2025-08-26T19:55:58.7879234Z >>> # Essentially, it is similar to following operation: 2025-08-26T19:55:58.7892015Z >>> scatter_list = input 2025-08-26T19:55:58.7892342Z >>> gather_list = output 2025-08-26T19:55:58.7892661Z >>> for i in range(world_size): 2025-08-26T19:55:58.7893097Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i) 2025-08-26T19:55:58.7893461Z 2025-08-26T19:55:58.7893550Z >>> input 2025-08-26T19:55:58.7893851Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T19:55:58.7894306Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T19:55:58.7894830Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T19:55:58.7895277Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T19:55:58.7895667Z >>> input_splits 2025-08-26T19:55:58.7895985Z [2, 2, 1, 1] # Rank 0 2025-08-26T19:55:58.7896552Z [3, 2, 2, 2] # Rank 1 2025-08-26T19:55:58.7897121Z [2, 1, 1, 1] # Rank 2 2025-08-26T19:55:58.7897562Z [2, 2, 2, 1] # Rank 3 2025-08-26T19:55:58.7898029Z >>> output_splits 2025-08-26T19:55:58.7898371Z [2, 3, 2, 2] # Rank 0 2025-08-26T19:55:58.7898732Z [2, 2, 1, 2] # Rank 1 2025-08-26T19:55:58.7899115Z [1, 2, 1, 2] # Rank 2 2025-08-26T19:55:58.7899495Z [1, 2, 1, 1] # Rank 3 2025-08-26T19:55:58.7899881Z >>> input = list(input.split(input_splits)) 2025-08-26T19:55:58.7900218Z >>> input 2025-08-26T19:55:58.7900551Z [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])] # Rank 0 2025-08-26T19:55:58.7901092Z [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1 2025-08-26T19:55:58.7901632Z [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])] # Rank 2 2025-08-26T19:55:58.7902168Z [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])] # Rank 3 2025-08-26T19:55:58.7902582Z >>> output = ... 2025-08-26T19:55:58.7902856Z >>> dist.all_to_all(output, input) 2025-08-26T19:55:58.7903168Z >>> output 2025-08-26T19:55:58.7903513Z [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])] # Rank 0 2025-08-26T19:55:58.7904039Z [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])] # Rank 1 2025-08-26T19:55:58.7904696Z [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])] # Rank 2 2025-08-26T19:55:58.7905241Z [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])] # Rank 3 2025-08-26T19:55:58.7905572Z 2025-08-26T19:55:58.7905751Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T19:55:58.7906142Z >>> input = torch.tensor( 2025-08-26T19:55:58.7906473Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T19:55:58.7906836Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T19:55:58.7907143Z >>> input = list(input.chunk(4)) 2025-08-26T19:55:58.7907451Z >>> input 2025-08-26T19:55:58.7907896Z [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])] # Rank 0 2025-08-26T19:55:58.7908526Z [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])] # Rank 1 2025-08-26T19:55:58.7909096Z [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])] # Rank 2 2025-08-26T19:55:58.7909675Z [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])] # Rank 3 2025-08-26T19:55:58.7910224Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T19:55:58.7910640Z >>> dist.all_to_all(output, input) 2025-08-26T19:55:58.7910956Z >>> output 2025-08-26T19:55:58.7911310Z [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])] # Rank 0 2025-08-26T19:55:58.7911865Z [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])] # Rank 1 2025-08-26T19:55:58.7912485Z [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])] # Rank 2 2025-08-26T19:55:58.7913031Z [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])] # Rank 3 2025-08-26T19:55:58.7913385Z 2025-08-26T19:55:58.7913390Z 2025-08-26T19:55:58.7913690Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.7914069Z 2025-08-26T19:55:58.7914628Z msg = Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/launch.py line=2. 2025-08-26T19:55:58.7915509Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.7915913Z 2025-08-26T19:55:58.7916034Z Module ``torch.distributed.launch``. 2025-08-26T19:55:58.7916255Z 2025-08-26T19:55:58.7916592Z ``torch.distributed.launch`` is a module that spawns up multiple distributed 2025-08-26T19:55:58.7917128Z training processes on each of the training nodes. 2025-08-26T19:55:58.7917395Z 2025-08-26T19:55:58.7917494Z .. warning:: 2025-08-26T19:55:58.7917636Z 2025-08-26T19:55:58.7917898Z This module is going to be deprecated in favor of :ref:`torchrun `. 2025-08-26T19:55:58.7918293Z 2025-08-26T19:55:58.7918537Z The utility can be used for single-node distributed training, in which one or 2025-08-26T19:55:58.7919152Z more processes per node will be spawned. The utility can be used for either 2025-08-26T19:55:58.7919741Z CPU training or GPU training. If the utility is used for GPU training, 2025-08-26T19:55:58.7920324Z each distributed process will be operating on a single GPU. This can achieve 2025-08-26T19:55:58.7920945Z well-improved single-node training performance. It can also be used in 2025-08-26T19:55:58.7921578Z multi-node distributed training, by spawning up multiple processes on each node 2025-08-26T19:55:58.7922216Z for well-improved multi-node distributed training performance as well. 2025-08-26T19:55:58.7922809Z This will especially be beneficial for systems with multiple Infiniband 2025-08-26T19:55:58.7923411Z interfaces that have direct-GPU support, since all of them can be utilized for 2025-08-26T19:55:58.7923911Z aggregated communication bandwidth. 2025-08-26T19:55:58.7924123Z 2025-08-26T19:55:58.7924371Z In both cases of single-node distributed training or multi-node distributed 2025-08-26T19:55:58.7924975Z training, this utility will launch the given number of processes per node 2025-08-26T19:55:58.7925556Z (``--nproc-per-node``). If used for GPU training, this number needs to be less 2025-08-26T19:55:58.7926139Z or equal to the number of GPUs on the current system (``nproc_per_node``), 2025-08-26T19:55:58.7926690Z and each process will be operating on a single GPU from *GPU 0 to 2025-08-26T19:55:58.7927126Z GPU (nproc_per_node - 1)*. 2025-08-26T19:55:58.7927308Z 2025-08-26T19:55:58.7927428Z **How to use this module:** 2025-08-26T19:55:58.7927609Z 2025-08-26T19:55:58.7927764Z 1. Single-Node multi-process distributed training 2025-08-26T19:55:58.7928044Z 2025-08-26T19:55:58.7928132Z :: 2025-08-26T19:55:58.7928256Z 2025-08-26T19:55:58.7928500Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T19:55:58.7929135Z YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other 2025-08-26T19:55:58.7929698Z arguments of your training script) 2025-08-26T19:55:58.7929950Z 2025-08-26T19:55:58.7930165Z 2. Multi-Node multi-process distributed training: (e.g. two nodes) 2025-08-26T19:55:58.7930508Z 2025-08-26T19:55:58.7930512Z 2025-08-26T19:55:58.7930657Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)* 2025-08-26T19:55:58.7930922Z 2025-08-26T19:55:58.7931007Z :: 2025-08-26T19:55:58.7931117Z 2025-08-26T19:55:58.7931371Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T19:55:58.7931892Z --nnodes=2 --node-rank=0 --master-addr="192.168.1.1" 2025-08-26T19:55:58.7932388Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T19:55:58.7932881Z and all other arguments of your training script) 2025-08-26T19:55:58.7933148Z 2025-08-26T19:55:58.7933245Z Node 2: 2025-08-26T19:55:58.7933359Z 2025-08-26T19:55:58.7933456Z :: 2025-08-26T19:55:58.7933569Z 2025-08-26T19:55:58.7933808Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T19:55:58.7934369Z --nnodes=2 --node-rank=1 --master-addr="192.168.1.1" 2025-08-26T19:55:58.7934861Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T19:55:58.7935355Z and all other arguments of your training script) 2025-08-26T19:55:58.7935625Z 2025-08-26T19:55:58.7935805Z 3. To look up what optional arguments this module offers: 2025-08-26T19:55:58.7936080Z 2025-08-26T19:55:58.7936162Z :: 2025-08-26T19:55:58.7936289Z 2025-08-26T19:55:58.7936501Z python -m torch.distributed.launch --help 2025-08-26T19:55:58.7936765Z 2025-08-26T19:55:58.7936770Z 2025-08-26T19:55:58.7936868Z **Important Notices:** 2025-08-26T19:55:58.7937031Z 2025-08-26T19:55:58.7937235Z 1. This utility and multi-process distributed (single-node or 2025-08-26T19:55:58.7937946Z multi-node) GPU training currently only achieves the best performance using 2025-08-26T19:55:58.7938574Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to 2025-08-26T19:55:58.7939059Z use for GPU training. 2025-08-26T19:55:58.7939219Z 2025-08-26T19:55:58.7939454Z 2. In your training program, you must parse the command-line argument: 2025-08-26T19:55:58.7940038Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module. 2025-08-26T19:55:58.7940617Z If your training program uses GPUs, you should ensure that your code only 2025-08-26T19:55:58.7941168Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by: 2025-08-26T19:55:58.7941490Z 2025-08-26T19:55:58.7941604Z Parsing the local_rank argument 2025-08-26T19:55:58.7941800Z 2025-08-26T19:55:58.7941895Z :: 2025-08-26T19:55:58.7942004Z 2025-08-26T19:55:58.7942114Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.7942374Z >>> import argparse 2025-08-26T19:55:58.7942666Z >>> parser = argparse.ArgumentParser() 2025-08-26T19:55:58.7943102Z >>> parser.add_argument("--local-rank", "--local_rank", type=int) 2025-08-26T19:55:58.7943532Z >>> args = parser.parse_args() 2025-08-26T19:55:58.7943735Z 2025-08-26T19:55:58.7943857Z Set your device to local rank using either 2025-08-26T19:55:58.7944099Z 2025-08-26T19:55:58.7944181Z :: 2025-08-26T19:55:58.7944302Z 2025-08-26T19:55:58.7944505Z >>> torch.cuda.set_device(args.local_rank) # before your code runs 2025-08-26T19:55:58.7944827Z 2025-08-26T19:55:58.7944918Z or 2025-08-26T19:55:58.7945025Z 2025-08-26T19:55:58.7945119Z :: 2025-08-26T19:55:58.7945225Z 2025-08-26T19:55:58.7945361Z >>> with torch.cuda.device(args.local_rank): 2025-08-26T19:55:58.7945713Z >>> # your code to run 2025-08-26T19:55:58.7945994Z >>> ... 2025-08-26T19:55:58.7946125Z 2025-08-26T19:55:58.7946241Z .. versionchanged:: 2.0.0 2025-08-26T19:55:58.7946416Z 2025-08-26T19:55:58.7946664Z The launcher will passes the ``--local-rank=`` argument to your script. 2025-08-26T19:55:58.7947282Z From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the 2025-08-26T19:55:58.7947869Z previously used underscored ``--local_rank``. 2025-08-26T19:55:58.7948122Z 2025-08-26T19:55:58.7948374Z For backward compatibility, it may be necessary for users to handle both 2025-08-26T19:55:58.7949012Z cases in their argument parsing code. This means including both ``"--local-rank"`` 2025-08-26T19:55:58.7949618Z and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is 2025-08-26T19:55:58.7950222Z provided, the launcher will trigger an error: "error: unrecognized arguments: 2025-08-26T19:55:58.7950845Z --local-rank=". For training code that only supports PyTorch 2.0.0+, 2025-08-26T19:55:58.7951356Z including ``"--local-rank"`` should be sufficient. 2025-08-26T19:55:58.7951619Z 2025-08-26T19:55:58.7951868Z 3. In your training program, you are supposed to call the following function 2025-08-26T19:55:58.7952461Z at the beginning to start the distributed backend. It is strongly recommended 2025-08-26T19:55:58.7953067Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work, 2025-08-26T19:55:58.7953655Z but ``env://`` is the one that is officially supported by this module. 2025-08-26T19:55:58.7953966Z 2025-08-26T19:55:58.7954065Z :: 2025-08-26T19:55:58.7954175Z 2025-08-26T19:55:58.7954384Z >>> torch.distributed.init_process_group(backend='YOUR BACKEND', 2025-08-26T19:55:58.7954862Z >>> init_method='env://') 2025-08-26T19:55:58.7955204Z 2025-08-26T19:55:58.7955562Z 4. In your training program, you can either use regular distributed functions 2025-08-26T19:55:58.7956186Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your 2025-08-26T19:55:58.7956770Z training program uses GPUs for training and you would like to use 2025-08-26T19:55:58.7957285Z :func:`torch.nn.parallel.DistributedDataParallel` module, 2025-08-26T19:55:58.7957810Z here is how to configure it. 2025-08-26T19:55:58.7958012Z 2025-08-26T19:55:58.7958099Z :: 2025-08-26T19:55:58.7958210Z 2025-08-26T19:55:58.7958420Z >>> model = torch.nn.parallel.DistributedDataParallel(model, 2025-08-26T19:55:58.7958865Z >>> device_ids=[args.local_rank], 2025-08-26T19:55:58.7959269Z >>> output_device=args.local_rank) 2025-08-26T19:55:58.7959543Z 2025-08-26T19:55:58.7959794Z Please ensure that ``device_ids`` argument is set to be the only GPU device id 2025-08-26T19:55:58.7960403Z that your code will be operating on. This is generally the local rank of the 2025-08-26T19:55:58.7961008Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``, 2025-08-26T19:55:58.7961584Z and ``output_device`` needs to be ``args.local_rank`` in order to use this 2025-08-26T19:55:58.7962020Z utility 2025-08-26T19:55:58.7962148Z 2025-08-26T19:55:58.7962394Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable 2025-08-26T19:55:58.7962987Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with 2025-08-26T19:55:58.7963552Z ``--use-env=True``. You must adjust the subprocess example above to replace 2025-08-26T19:55:58.7964089Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher 2025-08-26T19:55:58.7964585Z will not pass ``--local-rank`` when you specify this flag. 2025-08-26T19:55:58.7964888Z 2025-08-26T19:55:58.7964981Z .. warning:: 2025-08-26T19:55:58.7965111Z 2025-08-26T19:55:58.7965323Z ``local_rank`` is NOT globally unique: it is only unique per process 2025-08-26T19:55:58.7965826Z on a machine. Thus, don't use it to decide if you should, e.g., 2025-08-26T19:55:58.7966252Z write to a networked filesystem. See 2025-08-26T19:55:58.7966707Z https://github.com/pytorch/pytorch/issues/12042 for an example of 2025-08-26T19:55:58.7967213Z how things can go wrong if you don't do this correctly. 2025-08-26T19:55:58.7967490Z 2025-08-26T19:55:58.7967495Z 2025-08-26T19:55:58.7967532Z 2025-08-26T19:55:58.7967536Z 2025-08-26T19:55:58.7967808Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.7968183Z 2025-08-26T19:55:58.8610606Z msg = Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361. 2025-08-26T19:55:58.8611695Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.8612082Z 2025-08-26T19:55:58.8612326Z Creates an :class:`ShardedTensor` from local shards and the global metadata. 2025-08-26T19:55:58.8612861Z Needs to be called on all ranks in an SPMD fashion. 2025-08-26T19:55:58.8613137Z 2025-08-26T19:55:58.8613220Z Args: 2025-08-26T19:55:58.8613621Z local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list 2025-08-26T19:55:58.8614192Z of shards that represent the local shards on this rank. 2025-08-26T19:55:58.8614717Z global_size (int...): a list, tuple, or `torch.Size` of integers defining the 2025-08-26T19:55:58.8615343Z shape of the overall sharded tensor. 2025-08-26T19:55:58.8615573Z 2025-08-26T19:55:58.8615678Z Keyword args: 2025-08-26T19:55:58.8616089Z process_group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:55:58.8616599Z the default process group will be used. 2025-08-26T19:55:58.8617020Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T19:55:58.8617647Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T19:55:58.8618252Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T19:55:58.8618653Z Default: ``False``. 2025-08-26T19:55:58.8618837Z 2025-08-26T19:55:58.8618923Z Returns: 2025-08-26T19:55:58.8619204Z A :class:`ShardedTensor` object handle on this rank 2025-08-26T19:55:58.8619463Z 2025-08-26T19:55:58.8619467Z 2025-08-26T19:55:58.8619570Z Examples: 2025-08-26T19:55:58.8619955Z Suppose we want construct a sharded tensor on two ranks, global size = (10, 5), 2025-08-26T19:55:58.8620502Z each shard have a (5, 5) local tensor, we can do it like below: 2025-08-26T19:55:58.8620808Z 2025-08-26T19:55:58.8620893Z on rank 0: 2025-08-26T19:55:58.8621166Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T19:55:58.8621518Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T19:55:58.8621840Z >>> shard_offsets=[0, 0], 2025-08-26T19:55:58.8622135Z >>> shard_lengths=[5, 5], 2025-08-26T19:55:58.8622440Z >>> placement="rank:0/cuda:0" 2025-08-26T19:55:58.8622743Z >>> ) 2025-08-26T19:55:58.8623048Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T19:55:58.8623692Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T19:55:58.8624019Z 2025-08-26T19:55:58.8624105Z on rank 1: 2025-08-26T19:55:58.8624362Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T19:55:58.8624722Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T19:55:58.8625051Z >>> shard_offsets=[5, 0], 2025-08-26T19:55:58.8625451Z >>> shard_lengths=[5, 5], 2025-08-26T19:55:58.8625891Z >>> placement="rank:1/cuda:1" 2025-08-26T19:55:58.8626186Z >>> ) 2025-08-26T19:55:58.8626488Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T19:55:58.8627000Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T19:55:58.8627304Z 2025-08-26T19:55:58.8627564Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.8627934Z 2025-08-26T19:55:58.8741419Z msg = Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835. 2025-08-26T19:55:58.8742552Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.8742942Z 2025-08-26T19:55:58.8743323Z Initialize a ShardedTensor given only one local tensor, global sharded tensor 2025-08-26T19:55:58.8743832Z size and sharding spec on each rank. 2025-08-26T19:55:58.8744059Z 2025-08-26T19:55:58.8744143Z Args: 2025-08-26T19:55:58.8744497Z local_tensor (Tensor): Single tensor of local shard stored in each rank. 2025-08-26T19:55:58.8745122Z sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): 2025-08-26T19:55:58.8745673Z The specification describing how to shard the Tensor. 2025-08-26T19:55:58.8746141Z global_size (Sequence[int]): Size of the sharded tensor. 2025-08-26T19:55:58.8746697Z process_group (ProcessGroup, optional): The process group to aggregate on. 2025-08-26T19:55:58.8747186Z Default: None 2025-08-26T19:55:58.8747516Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T19:55:58.8748031Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T19:55:58.8748663Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T19:55:58.8749232Z Default: ``False``. 2025-08-26T19:55:58.8749414Z 2025-08-26T19:55:58.8749515Z Returns: 2025-08-26T19:55:58.8749880Z A :class:`ShardedTensor` sharded based on the given sharding_spec with local 2025-08-26T19:55:58.8750383Z tensor stored in the current rank. 2025-08-26T19:55:58.8750609Z 2025-08-26T19:55:58.8750710Z Examples: 2025-08-26T19:55:58.8750940Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.8751283Z >>> # All tensors below are of torch.int64 type. 2025-08-26T19:55:58.8751645Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:55:58.8752165Z >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T19:55:58.8752680Z >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2])) 2025-08-26T19:55:58.8753106Z >>> local_tensor 2025-08-26T19:55:58.8753420Z tensor([[1, 2, 3, 4]]) # Rank 0 2025-08-26T19:55:58.8753730Z tensor([[3, 4, 5, 6]]) # Rank 1 2025-08-26T19:55:58.8754033Z >>> sharding_dim = 0 2025-08-26T19:55:58.8754338Z >>> sharding_spec = ChunkShardingSpec( 2025-08-26T19:55:58.8754676Z dim=sharding_dim, 2025-08-26T19:55:58.8754951Z placements=[ 2025-08-26T19:55:58.8755219Z "rank:0/cuda:0", 2025-08-26T19:55:58.8755511Z "rank:1/cuda:1", 2025-08-26T19:55:58.8755776Z ], 2025-08-26T19:55:58.8756002Z ) 2025-08-26T19:55:58.8756261Z >>> st = ShardedTensor._init_from_local_tensor( 2025-08-26T19:55:58.8756640Z ... local_tensor, sharding_spec, [2, 4] 2025-08-26T19:55:58.8756960Z ... ) 2025-08-26T19:55:58.8757178Z >>> st 2025-08-26T19:55:58.8757401Z ShardedTensor( 2025-08-26T19:55:58.8757663Z ShardedTensorMetadata( 2025-08-26T19:55:58.8757949Z shards_metadata=[ 2025-08-26T19:55:58.8758410Z ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0), 2025-08-26T19:55:58.8759185Z ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1), 2025-08-26T19:55:58.8759671Z ], 2025-08-26T19:55:58.8759918Z size=torch.Size([2, 4]) 2025-08-26T19:55:58.8760200Z ) 2025-08-26T19:55:58.8760421Z >>> st.local_tensor() 2025-08-26T19:55:58.8760693Z tensor([1, 2, 3, 4]) # Rank 0 2025-08-26T19:55:58.8760978Z tensor([3, 4, 5, 6]) # Rank 1 2025-08-26T19:55:58.8761181Z 2025-08-26T19:55:58.8761454Z Warning: This API is experimental and subject to change. It lacks of a fully across 2025-08-26T19:55:58.8762108Z rank validations, and we only validate the local shard on the current rank. 2025-08-26T19:55:58.8762698Z We fully rely on the user to ensure local tensor is sharded based on the 2025-08-26T19:55:58.8763137Z sharding spec. 2025-08-26T19:55:58.8763299Z 2025-08-26T19:55:58.8763559Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.8763946Z 2025-08-26T19:55:58.8764641Z msg = Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076. 2025-08-26T19:55:58.8765780Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.8766179Z 2025-08-26T19:55:58.8766434Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support 2025-08-26T19:55:58.8766912Z single local shard. 2025-08-26T19:55:58.8767063Z 2025-08-26T19:55:58.8767288Z If ``resharding_spec`` is same as the original one, this becomes a no-op. 2025-08-26T19:55:58.8767890Z If only ``resharding_spec`` shares the same sharding dim with the original one, 2025-08-26T19:55:58.8768439Z we swap local shards directly. 2025-08-26T19:55:58.8768984Z For more generic cases, we merge different shards across different ranks and split 2025-08-26T19:55:58.8769640Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API. 2025-08-26T19:55:58.8770017Z 2025-08-26T19:55:58.8770103Z Args: 2025-08-26T19:55:58.8770522Z resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The 2025-08-26T19:55:58.8771160Z specification describing how the tensor is sharded. 2025-08-26T19:55:58.8771443Z 2025-08-26T19:55:58.8771546Z Returns: 2025-08-26T19:55:58.8771870Z A :class:`ShardedTensor` object whose local shards are resharded. 2025-08-26T19:55:58.8772208Z 2025-08-26T19:55:58.8772297Z Examples: 2025-08-26T19:55:58.8772531Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.8772840Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:55:58.8773319Z >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T19:55:58.8773732Z >>> tensor = torch.stack([tensor, tensor]) 2025-08-26T19:55:58.8774063Z >>> tensor 2025-08-26T19:55:58.8774324Z tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0 2025-08-26T19:55:58.8774686Z tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1 2025-08-26T19:55:58.8775029Z tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2 2025-08-26T19:55:58.8775392Z tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3 2025-08-26T19:55:58.8775805Z >>> sharding_dim = 0 2025-08-26T19:55:58.8776099Z >>> spec = ChunkShardingSpec( 2025-08-26T19:55:58.8776396Z dim=sharding_dim, 2025-08-26T19:55:58.8776691Z placements=[ 2025-08-26T19:55:58.8776964Z "rank:0/cuda:0", 2025-08-26T19:55:58.8777255Z "rank:1/cuda:1", 2025-08-26T19:55:58.8777529Z "rank:2/cuda:2", 2025-08-26T19:55:58.8777817Z "rank:3/cuda:3", 2025-08-26T19:55:58.8778089Z ], 2025-08-26T19:55:58.8778312Z ) 2025-08-26T19:55:58.8778530Z >>> current_offsets = [0] * 2 2025-08-26T19:55:58.8778839Z >>> current_offsets[0] = rank * 2 2025-08-26T19:55:58.8779165Z >>> shard_metadata = ShardMetadata( 2025-08-26T19:55:58.8779544Z shard_offsets=copy.deepcopy(current_offsets), 2025-08-26T19:55:58.8779914Z shard_sizes=tensor.size(), 2025-08-26T19:55:58.8780262Z placement=spec.placements[rank], 2025-08-26T19:55:58.8780586Z ) 2025-08-26T19:55:58.8780807Z >>> local_shards = [ 2025-08-26T19:55:58.8781057Z Shard( 2025-08-26T19:55:58.8781306Z tensor=tensor, 2025-08-26T19:55:58.8781604Z metadata=shard_metadata, 2025-08-26T19:55:58.8781911Z ) 2025-08-26T19:55:58.8782119Z ] 2025-08-26T19:55:58.8782480Z >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size()) 2025-08-26T19:55:58.8782938Z >>> sharding_dim = 1 2025-08-26T19:55:58.8783244Z >>> resharding_spec = ChunkShardingSpec( 2025-08-26T19:55:58.8783574Z dim=sharding_dim, 2025-08-26T19:55:58.8783862Z placements=[ 2025-08-26T19:55:58.8784129Z "rank:0/cuda:0", 2025-08-26T19:55:58.8784419Z "rank:1/cuda:1", 2025-08-26T19:55:58.8784692Z "rank:2/cuda:2", 2025-08-26T19:55:58.8784978Z "rank:3/cuda:3", 2025-08-26T19:55:58.8785297Z ], 2025-08-26T19:55:58.8785531Z ) 2025-08-26T19:55:58.8785761Z >>> st.reshard(resharding_spec) 2025-08-26T19:55:58.8786096Z >>> tensor = st.local_shards()[0].tensor 2025-08-26T19:55:58.8786423Z >>> tensor 2025-08-26T19:55:58.8786694Z tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0 2025-08-26T19:55:58.8787102Z tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1 2025-08-26T19:55:58.8787501Z tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2 2025-08-26T19:55:58.8787904Z tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3 2025-08-26T19:55:58.8788172Z 2025-08-26T19:55:58.8788442Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.8788816Z 2025-08-26T19:55:58.8958878Z msg = Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12. 2025-08-26T19:55:58.8959898Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.8960411Z 2025-08-26T19:55:58.8960636Z Representation of a sharding plan, describes how to shard a module 2025-08-26T19:55:58.8961254Z across hosts. `plan` is used to shard module parameters according to the spec provided, 2025-08-26T19:55:58.8961952Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output 2025-08-26T19:55:58.8962624Z layout of a module with a spec, and when to convert back to data parallel fashion. 2025-08-26T19:55:58.8962994Z 2025-08-26T19:55:58.8963078Z Args: 2025-08-26T19:55:58.8963573Z plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`, 2025-08-26T19:55:58.8964152Z :class:`torch.distributed._shard.sharder.Sharder`]): 2025-08-26T19:55:58.8964722Z a dict describes how to shard a module, there're currently two ways to shard a module: 2025-08-26T19:55:58.8965385Z 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of 2025-08-26T19:55:58.8965885Z a parameter to a `ShardingSpec`. 2025-08-26T19:55:58.8966393Z 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module 2025-08-26T19:55:58.8966976Z to a `Sharder` object. 2025-08-26T19:55:58.8967530Z output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional): 2025-08-26T19:55:58.8968245Z a dict specifies the layout of a module's output which produces a ShardedTensor, 2025-08-26T19:55:58.8968949Z keyed by the name of module to ShardingSpec("" in key means the root module). 2025-08-26T19:55:58.8969416Z Default: `None` 2025-08-26T19:55:58.8969847Z return_local_tensor (List[str], optional): a list of string, each element enables 2025-08-26T19:55:58.8970479Z a module's sharded output to be returned as a Tensor from its local shards to 2025-08-26T19:55:58.8971094Z ensure further processing in a data parallel fashion. ("" in list means the 2025-08-26T19:55:58.8971573Z root module). 2025-08-26T19:55:58.8971824Z Default: None 2025-08-26T19:55:58.8972091Z Example: 2025-08-26T19:55:58.8972497Z Suppose we want to shard a module with two linear layers and then run it with DDP, we also 2025-08-26T19:55:58.8973202Z want to convert the output of the second linear layer back to DDP, we can do it as follows: 2025-08-26T19:55:58.8973629Z 2025-08-26T19:55:58.8973803Z >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d) 2025-08-26T19:55:58.8974212Z >>> class MyModule(nn.Module): 2025-08-26T19:55:58.8974547Z >>> def __init__(self) -> None: 2025-08-26T19:55:58.8974859Z >>> super().__init__() 2025-08-26T19:55:58.8975162Z >>> self.fc1 = nn.Linear() 2025-08-26T19:55:58.8975474Z >>> self.gelu = nn.GELU() 2025-08-26T19:55:58.8975787Z >>> self.fc2 = nn.Linear() 2025-08-26T19:55:58.8976089Z >>> self.relu = nn.Linear() 2025-08-26T19:55:58.8976452Z >>> 2025-08-26T19:55:58.8976681Z >>> def forward(self, input): 2025-08-26T19:55:58.8977075Z >>> return self.relu(self.fc2(self.gelu(self.fc1(input)))) 2025-08-26T19:55:58.8977368Z 2025-08-26T19:55:58.8977372Z 2025-08-26T19:55:58.8977507Z >>> # xdoctest: +SKIP("Undefined spec1, spec2) 2025-08-26T19:55:58.8977877Z >>> sharding_plan = ShardingPlan( 2025-08-26T19:55:58.8978189Z >>> plan={ 2025-08-26T19:55:58.8978450Z >>> "fc1.weight": spec1, 2025-08-26T19:55:58.8978749Z >>> "fc2.weight": spec2 2025-08-26T19:55:58.8979039Z >>> }, 2025-08-26T19:55:58.8979277Z >>> output_plan={ 2025-08-26T19:55:58.8979556Z >>> "fc2": output_spec 2025-08-26T19:55:58.8979829Z >>> }, 2025-08-26T19:55:58.8980075Z >>> return_local_tensor=["fc2"] 2025-08-26T19:55:58.8980383Z >>> ) 2025-08-26T19:55:58.8980503Z 2025-08-26T19:55:58.8980774Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.8981153Z 2025-08-26T19:55:58.9937187Z msg = Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72. 2025-08-26T19:55:58.9938622Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.9939012Z 2025-08-26T19:55:58.9939126Z Run post-localSGD algorithm. 2025-08-26T19:55:58.9939338Z 2025-08-26T19:55:58.9939580Z This DDP communication hook is used for running post-localSGD algorithm, 2025-08-26T19:55:58.9940224Z by combining with a model averaging component (e.g., 2025-08-26T19:55:58.9940844Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`) 2025-08-26T19:55:58.9941410Z that runs after the optimizer step. 2025-08-26T19:55:58.9941638Z 2025-08-26T19:55:58.9941721Z Args: 2025-08-26T19:55:58.9942076Z state (PostLocalSGDState): State information to run post-localSGD. 2025-08-26T19:55:58.9942803Z Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD. 2025-08-26T19:55:58.9943646Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T19:55:58.9944444Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T19:55:58.9944978Z only exactly one tensor is stored in this bucket. 2025-08-26T19:55:58.9945256Z 2025-08-26T19:55:58.9945342Z Returns: 2025-08-26T19:55:58.9945713Z Future handler of the communication, which updates the gradients in place. 2025-08-26T19:55:58.9946085Z 2025-08-26T19:55:58.9946200Z Example:: 2025-08-26T19:55:58.9946415Z >>> # xdoctest: +SKIP 2025-08-26T19:55:58.9946850Z >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup, 2025-08-26T19:55:58.9947357Z start_localSGD_iter=10) 2025-08-26T19:55:58.9947773Z >>> ddp_model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:55:58.9948403Z >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``. 2025-08-26T19:55:58.9949226Z >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module. 2025-08-26T19:55:58.9949716Z 2025-08-26T19:55:58.9949973Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:58.9950346Z 2025-08-26T19:55:58.9990506Z msg = Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342. 2025-08-26T19:55:58.9991619Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:58.9992004Z 2025-08-26T19:55:58.9992134Z Implement PowerSGD algorithm. 2025-08-26T19:55:58.9992330Z 2025-08-26T19:55:58.9992562Z This DDP communication hook implements PowerSGD gradient compression 2025-08-26T19:55:58.9993298Z algorithm described in the `paper `_. 2025-08-26T19:55:58.9993915Z Once gradient tensors are aggregated across all workers, this hook applies 2025-08-26T19:55:58.9994389Z compression as follows: 2025-08-26T19:55:58.9994556Z 2025-08-26T19:55:58.9995015Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups: 2025-08-26T19:55:58.9995579Z 2025-08-26T19:55:58.9996013Z 1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth. 2025-08-26T19:55:58.9996572Z 2025-08-26T19:55:58.9996994Z 1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases). 2025-08-26T19:55:58.9997545Z 2025-08-26T19:55:58.9997656Z 2. Handles uncompressed tensors: 2025-08-26T19:55:58.9997871Z 2025-08-26T19:55:58.9998398Z 2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression; 2025-08-26T19:55:58.9999093Z 2025-08-26T19:55:58.9999451Z 2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor. 2025-08-26T19:55:58.9999921Z 2025-08-26T19:55:59.0000170Z 3. Handles the tensors that should be compressed by PowerSGD compression: 2025-08-26T19:55:59.0000526Z 2025-08-26T19:55:59.0000768Z 3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M, 2025-08-26T19:55:59.0001467Z such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized; 2025-08-26T19:55:59.0002157Z 2025-08-26T19:55:59.0002317Z 3.2. Computes each P in Ps, which is equal to MQ; 2025-08-26T19:55:59.0002595Z 2025-08-26T19:55:59.0002706Z 3.3. Allreduces Ps as a batch; 2025-08-26T19:55:59.0002913Z 2025-08-26T19:55:59.0003044Z 3.4. Orthogonalizes each P in Ps; 2025-08-26T19:55:59.0003262Z 2025-08-26T19:55:59.0003460Z 3.5. Computes each Q in Qs, which is approximately equal to M^TP; 2025-08-26T19:55:59.0003811Z 2025-08-26T19:55:59.0003918Z 3.6. Allreduces Qs as a batch; 2025-08-26T19:55:59.0004131Z 2025-08-26T19:55:59.0004434Z 3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T. 2025-08-26T19:55:59.0004870Z 2025-08-26T19:55:59.0005285Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations. 2025-08-26T19:55:59.0006114Z This not only gives the user more control over the tradeoff between speedup and accuracy, 2025-08-26T19:55:59.0006974Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers. 2025-08-26T19:55:59.0007535Z 2025-08-26T19:55:59.0007617Z Args: 2025-08-26T19:55:59.0008186Z state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc. 2025-08-26T19:55:59.0009194Z To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter`` 2025-08-26T19:55:59.0009803Z and ``min_compression_rate``. 2025-08-26T19:55:59.0010460Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T19:55:59.0011251Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T19:55:59.0011788Z only exactly one tensor is stored in this bucket. 2025-08-26T19:55:59.0012067Z 2025-08-26T19:55:59.0012153Z Returns: 2025-08-26T19:55:59.0012535Z Future handler of the communication, which updates the gradients in place. 2025-08-26T19:55:59.0012901Z 2025-08-26T19:55:59.0013009Z Example:: 2025-08-26T19:55:59.0013225Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.0013681Z >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1, 2025-08-26T19:55:59.0014255Z start_powerSGD_iter=10, min_compression_rate=0.5) 2025-08-26T19:55:59.0014749Z >>> ddp_model.register_comm_hook(state, powerSGD_hook) 2025-08-26T19:55:59.0015026Z 2025-08-26T19:55:59.0015281Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0015667Z 2025-08-26T19:55:59.0041708Z msg = Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38. 2025-08-26T19:55:59.0042857Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0043257Z 2025-08-26T19:55:59.0043458Z Averages parameters periodically after the warm-up stage. 2025-08-26T19:55:59.0043760Z 2025-08-26T19:55:59.0044036Z This can be used for running `post-local SGD `_, 2025-08-26T19:55:59.0044617Z by running :class:`~torch.nn.DistributedDataParallel` (DDP) 2025-08-26T19:55:59.0045165Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`. 2025-08-26T19:55:59.0045540Z 2025-08-26T19:55:59.0045641Z Args: 2025-08-26T19:55:59.0046019Z period (int): The number of steps per model averaging. 2025-08-26T19:55:59.0046584Z Usually the period should be greater than ``1`` to reduce the communication cost. 2025-08-26T19:55:59.0047115Z Otherwise, only DDP needs to be used. 2025-08-26T19:55:59.0047564Z warmup_steps (int): The number of warm-up steps. During this stage, 2025-08-26T19:55:59.0048021Z model averaging is skipped. 2025-08-26T19:55:59.0048458Z process_group: The process group to be used for all-reduce. 2025-08-26T19:55:59.0049079Z If ``None``, the default process group, which 2025-08-26T19:55:59.0049632Z is created by :func:`torch.distributed.init_process_group`, 2025-08-26T19:55:59.0050064Z will be used. (default: ``None``) 2025-08-26T19:55:59.0050313Z 2025-08-26T19:55:59.0050409Z Example:: 2025-08-26T19:55:59.0050536Z 2025-08-26T19:55:59.0050681Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.0051024Z >>> import torch 2025-08-26T19:55:59.0051291Z >>> import torch.distributed as dist 2025-08-26T19:55:59.0051851Z >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD 2025-08-26T19:55:59.0052584Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T19:55:59.0053093Z >>> import torch.nn as nn 2025-08-26T19:55:59.0053363Z >>> 2025-08-26T19:55:59.0053670Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T19:55:59.0054089Z >>> torch.cuda.set_device(rank) 2025-08-26T19:55:59.0054439Z >>> module = nn.Linear(1, 1, bias=False).cuda() 2025-08-26T19:55:59.0054841Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T19:55:59.0055267Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T19:55:59.0055621Z >>> ) 2025-08-26T19:55:59.0055904Z >>> # Register a post-localSGD communication hook. 2025-08-26T19:55:59.0056480Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T19:55:59.0057068Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:55:59.0057436Z >>> 2025-08-26T19:55:59.0057832Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T19:55:59.0058392Z >>> # After 100 steps, run model averaging every 4 steps. 2025-08-26T19:55:59.0058983Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T19:55:59.0059690Z >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T19:55:59.0060178Z >>> for step in range(0, 200): 2025-08-26T19:55:59.0060490Z >>> optimizer.zero_grad() 2025-08-26T19:55:59.0060790Z >>> loss = loss_fn(output, labels) 2025-08-26T19:55:59.0061117Z >>> loss.backward() 2025-08-26T19:55:59.0061445Z >>> optimizer.step() 2025-08-26T19:55:59.0061833Z >>> # Will average model parameters globally every 4 steps. Thus, 2025-08-26T19:55:59.0062352Z >>> # inter-node communication only occurs every 4 iterations after 2025-08-26T19:55:59.0062813Z >>> # the initial ``warmup_steps`` period. 2025-08-26T19:55:59.0063254Z >>> averager.average_parameters(model.parameters()) 2025-08-26T19:55:59.0063718Z 2025-08-26T19:55:59.0064025Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0064399Z 2025-08-26T19:55:59.0065316Z msg = Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19. 2025-08-26T19:55:59.0066580Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0066965Z 2025-08-26T19:55:59.0067312Z Runs hierarchical model averaging (`hierarchical SGD `_). 2025-08-26T19:55:59.0067850Z 2025-08-26T19:55:59.0068163Z Process groups of different sizes are organized in a hierarchy, and they average parameters 2025-08-26T19:55:59.0068819Z by using different periods concurrently after the warm-up stage. 2025-08-26T19:55:59.0069565Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager` 2025-08-26T19:55:59.0070449Z that supports `post-local SGD `_, which essentially only supports 2025-08-26T19:55:59.0071275Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine 2025-08-26T19:55:59.0072077Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`. 2025-08-26T19:55:59.0072958Z Similarly, the process groups within this class do not have such an intra-machine process 2025-08-26T19:55:59.0073700Z subgroup, which should be embedded by the post-local SGD communication hook instead. 2025-08-26T19:55:59.0074119Z 2025-08-26T19:55:59.0074207Z Args: 2025-08-26T19:55:59.0074598Z period_group_size_dict: An ordered dict mapping keys of model averaging period to 2025-08-26T19:55:59.0075188Z process group size, used for initializing process groups of 2025-08-26T19:55:59.0075752Z different sizes in a hierarchy to average parameters concurrently. 2025-08-26T19:55:59.0076327Z Particularly, at each iteration, there will be at most a single 2025-08-26T19:55:59.0076912Z process group that runs averaging -- the period of such group should 2025-08-26T19:55:59.0077498Z have the largest period which the current step can be divided by. 2025-08-26T19:55:59.0078002Z For example, if the dict has three keys: 2, 4, and 8, 2025-08-26T19:55:59.0078509Z then this means totally three process groups will be created to 2025-08-26T19:55:59.0079068Z average parameters every 2, 4, and 8 iterations, respectively. 2025-08-26T19:55:59.0079608Z At the 4th iteration, only the second process group will run 2025-08-26T19:55:59.0080109Z averaging, because the first process group should be a 2025-08-26T19:55:59.0080628Z subset of the second process group, and no need to execute the first 2025-08-26T19:55:59.0081110Z process group redundantly. 2025-08-26T19:55:59.0081556Z On the other hand, the third process group can only be triggered 2025-08-26T19:55:59.0082115Z every 8 iterations, so it will not be triggered at the 4th iteration. 2025-08-26T19:55:59.0082782Z warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped. 2025-08-26T19:55:59.0083656Z process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging. 2025-08-26T19:55:59.0084448Z If ``None``, the default process group, which is created 2025-08-26T19:55:59.0084969Z by :func:`torch.distributed.init_process_group`, will be used. 2025-08-26T19:55:59.0085430Z (default: ``None``) 2025-08-26T19:55:59.0085668Z 2025-08-26T19:55:59.0085775Z Example:: 2025-08-26T19:55:59.0086011Z >>> # xdoctest: +SKIP('undefined rank') 2025-08-26T19:55:59.0086445Z >>> from collections import OrderedDict 2025-08-26T19:55:59.0086781Z >>> import torch 2025-08-26T19:55:59.0087061Z >>> import torch.distributed as dist 2025-08-26T19:55:59.0087559Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T19:55:59.0088074Z >>> PostLocalSGDState, 2025-08-26T19:55:59.0088375Z >>> post_localSGD_hook, 2025-08-26T19:55:59.0088654Z >>> ) 2025-08-26T19:55:59.0089267Z >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD 2025-08-26T19:55:59.0089878Z >>> import torch.nn as nn 2025-08-26T19:55:59.0090158Z >>> 2025-08-26T19:55:59.0090462Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T19:55:59.0090862Z >>> torch.cuda.set_device(rank) 2025-08-26T19:55:59.0091216Z >>> module = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T19:55:59.0091633Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T19:55:59.0092111Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T19:55:59.0092451Z >>> ) 2025-08-26T19:55:59.0092730Z >>> # Register a post-localSGD communication hook. 2025-08-26T19:55:59.0093279Z >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4. 2025-08-26T19:55:59.0093808Z >>> subgroup, _ = dist.new_subgroups() 2025-08-26T19:55:59.0094354Z >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100) 2025-08-26T19:55:59.0094970Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:55:59.0095346Z >>> 2025-08-26T19:55:59.0095753Z >>> # Average parameters among each group of 8 processes every 4 iterations, and among all 2025-08-26T19:55:59.0096300Z >>> # the 16 processes every 16 iterations. 2025-08-26T19:55:59.0096720Z >>> averager = hierarchicalSGD.HierarchicalModelAverager( 2025-08-26T19:55:59.0097267Z >>> period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100) 2025-08-26T19:55:59.0098035Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T19:55:59.0098776Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T19:55:59.0099325Z >>> # After 100 steps, run model averaging at two levels. 2025-08-26T19:55:59.0099716Z >>> for step in range(0, 200): 2025-08-26T19:55:59.0100041Z >>> optimizer.zero_grad() 2025-08-26T19:55:59.0100360Z >>> loss = loss_fn(output, labels) 2025-08-26T19:55:59.0100681Z >>> loss.backward() 2025-08-26T19:55:59.0100973Z >>> optimizer.step() 2025-08-26T19:55:59.0101319Z >>> # Average parameters after ``optimizer.step()``. 2025-08-26T19:55:59.0101894Z >>> # Thus, the inter-node communication only occurs periodically after ``warmup_steps``. 2025-08-26T19:55:59.0102547Z >>> averager.average_parameters(model.parameters()) 2025-08-26T19:55:59.0102830Z 2025-08-26T19:55:59.0102932Z .. warning :: 2025-08-26T19:55:59.0103333Z The last group size in the dict must be the size of the provided ``process_group``, 2025-08-26T19:55:59.0103963Z which indicates model averaging at the highest level of the hierarchy. 2025-08-26T19:55:59.0104639Z If ``process_group`` is not provided, then the last group size should be equal to the world size. 2025-08-26T19:55:59.0105115Z 2025-08-26T19:55:59.0105208Z .. warning :: 2025-08-26T19:55:59.0105598Z `HierarchicalModelAverager` is experimental and subject to change. 2025-08-26T19:55:59.0105970Z 2025-08-26T19:55:59.0106227Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0106599Z 2025-08-26T19:55:59.0586797Z msg = Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=40. 2025-08-26T19:55:59.0587930Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0588331Z 2025-08-26T19:55:59.0588638Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint 2025-08-26T19:55:59.0589304Z on the coordinator rank, and then broadcast and shard each tensor to all ranks. 2025-08-26T19:55:59.0589688Z 2025-08-26T19:55:59.0589912Z . N.B. Intended to be used with DynamicMetaLoadPlanner 2025-08-26T19:55:59.0590263Z 2025-08-26T19:55:59.0590358Z .. warning:: 2025-08-26T19:55:59.0590796Z Current implementation only supports loading Tensors. 2025-08-26T19:55:59.0591086Z 2025-08-26T19:55:59.0591216Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0591529Z >>> sd = {"mode": model} 2025-08-26T19:55:59.0591792Z >>> dcp.load( 2025-08-26T19:55:59.0592018Z >>> sd, 2025-08-26T19:55:59.0592305Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T19:55:59.0592689Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T19:55:59.0593050Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T19:55:59.0593362Z >>> ) 2025-08-26T19:55:59.0593563Z 2025-08-26T19:55:59.0593835Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0594209Z 2025-08-26T19:55:59.0594936Z msg = Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=151. 2025-08-26T19:55:59.0596007Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0596408Z 2025-08-26T19:55:59.0596781Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict, 2025-08-26T19:55:59.0597611Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a 2025-08-26T19:55:59.0598187Z metadata file, like Torch Save files. 2025-08-26T19:55:59.0598403Z 2025-08-26T19:55:59.0598594Z . N.B. Intended to be used with BroadcastingTorchSaveReader 2025-08-26T19:55:59.0598886Z 2025-08-26T19:55:59.0598975Z .. warning:: 2025-08-26T19:55:59.0599291Z Current implementation only supports loading Tensors. 2025-08-26T19:55:59.0599588Z 2025-08-26T19:55:59.0599703Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0600025Z >>> sd = {"mode": model} 2025-08-26T19:55:59.0600285Z >>> dcp.load( 2025-08-26T19:55:59.0600591Z >>> sd, 2025-08-26T19:55:59.0600881Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T19:55:59.0601287Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T19:55:59.0601637Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T19:55:59.0601955Z >>> ) 2025-08-26T19:55:59.0602084Z 2025-08-26T19:55:59.0602341Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0602719Z 2025-08-26T19:55:59.0703782Z msg = Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/optimizer.py line=221. 2025-08-26T19:55:59.0704884Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0705272Z 2025-08-26T19:55:59.0705496Z Load a state_dict in conjunction with FSDP sharded optimizer state. 2025-08-26T19:55:59.0705824Z 2025-08-26T19:55:59.0706001Z This is the current recommended way to checkpoint FSDP. 2025-08-26T19:55:59.0706369Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.0706689Z >>> import torch.distributed.checkpoint as dist_cp 2025-08-26T19:55:59.0707147Z >>> # Save 2025-08-26T19:55:59.0707384Z >>> model: torch.nn.Model 2025-08-26T19:55:59.0707673Z >>> optim_params = model.parameters() 2025-08-26T19:55:59.0708050Z >>> optim = torch.optim.SGD(optim_params, lr=0.01) 2025-08-26T19:55:59.0708399Z >>> # Save 2025-08-26T19:55:59.0708748Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT): 2025-08-26T19:55:59.0709176Z >>> state_dict = { 2025-08-26T19:55:59.0709499Z >>> "optimizer": FSDP.optim_state_dict(model, optim), 2025-08-26T19:55:59.0709967Z >>> "model": model.state_dict() 2025-08-26T19:55:59.0710282Z >>> } 2025-08-26T19:55:59.0710388Z >>> dist_cp.save_state_dict( 2025-08-26T19:55:59.0710492Z >>> state_dict=optim_state, 2025-08-26T19:55:59.0710689Z >>> storage_writer=dist_cp.FileSystemWriter("checkpoint"), 2025-08-26T19:55:59.0710823Z >>> planner=dist_cp.DefaultSavePlanner(), 2025-08-26T19:55:59.0710920Z >>> ) 2025-08-26T19:55:59.0711001Z >>> 2025-08-26T19:55:59.0711087Z >>> # Load 2025-08-26T19:55:59.0711386Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT): 2025-08-26T19:55:59.0711512Z >>> model_state_dict = model_tp.state_dict() 2025-08-26T19:55:59.0711605Z >>> checkpoint = { 2025-08-26T19:55:59.0711723Z >>> "model": model_state_dict 2025-08-26T19:55:59.0711806Z >>> } 2025-08-26T19:55:59.0711922Z >>> dist_cp.load_state_dict( 2025-08-26T19:55:59.0712026Z >>> state_dict=checkpoint, 2025-08-26T19:55:59.0712220Z >>> storage_reader=dist_cp.FileSystemReader(checkpoint_file), 2025-08-26T19:55:59.0712435Z >>> planner=dist_cp.DefaultLoadPlanner(), 2025-08-26T19:55:59.0712523Z >>> ) 2025-08-26T19:55:59.0712688Z >>> model.load_state_dict(checkpoint["model_state"]) 2025-08-26T19:55:59.0712769Z >>> 2025-08-26T19:55:59.0712954Z >>> optim_state = dist_cp.load_sharded_optimizer_state_dict( 2025-08-26T19:55:59.0713066Z >>> model_state_dict, 2025-08-26T19:55:59.0713179Z >>> optimizer_key="optimizer", 2025-08-26T19:55:59.0713373Z >>> storage_reader=dist_cp.FileSystemReader("checkpoint"), 2025-08-26T19:55:59.0713458Z >>> ) 2025-08-26T19:55:59.0713545Z >>> 2025-08-26T19:55:59.0713707Z >>> flattened_osd = FSDP.optim_state_dict_to_load( 2025-08-26T19:55:59.0713834Z >>> model, optim, optim_state["optimizer"] 2025-08-26T19:55:59.0713933Z >>> ) 2025-08-26T19:55:59.0714017Z >>> 2025-08-26T19:55:59.0714138Z >>> optim.load_state_dict(flattened_osd) 2025-08-26T19:55:59.0714143Z 2025-08-26T19:55:59.0714423Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0714428Z 2025-08-26T19:55:59.0735924Z msg = Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-08-26T19:55:59.0736206Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0736211Z 2025-08-26T19:55:59.0736509Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-08-26T19:55:59.0736516Z 2025-08-26T19:55:59.0736826Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-08-26T19:55:59.0736831Z 2025-08-26T19:55:59.0737112Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T19:55:59.0737242Z will be visible to the whole process. 2025-08-26T19:55:59.0737246Z 2025-08-26T19:55:59.0737669Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-08-26T19:55:59.0737673Z 2025-08-26T19:55:59.0737801Z 1) set_up_planner - called on all ranks. 2025-08-26T19:55:59.0737939Z Signals the start of a checkpoint save. 2025-08-26T19:55:59.0737944Z 2025-08-26T19:55:59.0738071Z 2) create_local_plan - called on all ranks. 2025-08-26T19:55:59.0738376Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-08-26T19:55:59.0738476Z 2025-08-26T19:55:59.0738665Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T19:55:59.0738881Z Takes the SavePlan from all ranks and make any global decision. 2025-08-26T19:55:59.0738885Z 2025-08-26T19:55:59.0738999Z 4) finish_plan - called on all ranks. 2025-08-26T19:55:59.0739219Z This gives each rank a chance to adjust to global planning decisions. 2025-08-26T19:55:59.0739223Z 2025-08-26T19:55:59.0739419Z 5) resolve_data - called multiple times on each rank 2025-08-26T19:55:59.0739628Z Lookups a value on the `state_dict` for the storage layer to write. 2025-08-26T19:55:59.0739647Z 2025-08-26T19:55:59.0739960Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-08-26T19:55:59.0740147Z most changes can be expressed by changes in a single method. 2025-08-26T19:55:59.0740152Z 2025-08-26T19:55:59.0740287Z There are 3 usual patterns of extension: 2025-08-26T19:55:59.0740291Z 2025-08-26T19:55:59.0740548Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-08-26T19:55:59.0740836Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-08-26T19:55:59.0740840Z 2025-08-26T19:55:59.0740955Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0741093Z >>> class RenamePlanner(DefaultSavePlanner): 2025-08-26T19:55:59.0741208Z >>> def set_up_planner( 2025-08-26T19:55:59.0741296Z >>> self, 2025-08-26T19:55:59.0741422Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T19:55:59.0741549Z >>> storage_meta: Optional[StorageMeta], 2025-08-26T19:55:59.0741655Z >>> is_coordinator: bool, 2025-08-26T19:55:59.0741841Z >>> ) -> None: 2025-08-26T19:55:59.0741951Z >>> # prefix all keys with `foo_`` 2025-08-26T19:55:59.0742266Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-08-26T19:55:59.0742271Z 2025-08-26T19:55:59.0742612Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-08-26T19:55:59.0742621Z 2025-08-26T19:55:59.0742760Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0742970Z >>> class FP16Planner(DefaultSavePlanner): 2025-08-26T19:55:59.0743155Z >>> def create_local_plan(self): 2025-08-26T19:55:59.0743358Z >>> plan = super().create_local_plan() 2025-08-26T19:55:59.0743461Z >>> for p in plan: 2025-08-26T19:55:59.0743583Z >>> if p.tensor_data is not None: 2025-08-26T19:55:59.0743761Z >>> p.tensor_data.properties.dtype = torch.float16 2025-08-26T19:55:59.0743858Z >>> return plan 2025-08-26T19:55:59.0743962Z >>> 2025-08-26T19:55:59.0744081Z >>> def resolve_data(self, write_item): 2025-08-26T19:55:59.0744208Z >>> item = super().resolve_data(write_item) 2025-08-26T19:55:59.0744502Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-08-26T19:55:59.0744507Z 2025-08-26T19:55:59.0744854Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-08-26T19:55:59.0744863Z 2025-08-26T19:55:59.0744990Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0745104Z >>> from itertools import zip_longest 2025-08-26T19:55:59.0745229Z >>> from dataclasses import replace 2025-08-26T19:55:59.0745401Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-08-26T19:55:59.0745679Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-08-26T19:55:59.0745819Z >>> # This sample doesn't handle ShardedTensors 2025-08-26T19:55:59.0745952Z >>> def create_global_plan(self, all_plans): 2025-08-26T19:55:59.0746122Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-08-26T19:55:59.0746223Z >>> items_per_rank = [ 2025-08-26T19:55:59.0746360Z >>> [item for item in items if item is not None] 2025-08-26T19:55:59.0746537Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-08-26T19:55:59.0746666Z >>> ] 2025-08-26T19:55:59.0746776Z >>> all_plans = [ 2025-08-26T19:55:59.0746890Z >>> replace(plan, items=items) 2025-08-26T19:55:59.0747081Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-08-26T19:55:59.0747182Z >>> ] 2025-08-26T19:55:59.0747326Z >>> return super().create_global_plan(all_plans) 2025-08-26T19:55:59.0747330Z 2025-08-26T19:55:59.0747615Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-08-26T19:55:59.0747890Z accomplished by having each rank contribute their data items in the local plan and 2025-08-26T19:55:59.0748008Z the global planner aggregate them: 2025-08-26T19:55:59.0748012Z 2025-08-26T19:55:59.0748138Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0748294Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-08-26T19:55:59.0748438Z >>> def create_local_plan(self) -> SavePlan: 2025-08-26T19:55:59.0748555Z >>> plan = super().create_local_plan() 2025-08-26T19:55:59.0748721Z >>> return replace(plan, planner_data="per-rank-data") 2025-08-26T19:55:59.0748845Z >>> 2025-08-26T19:55:59.0749151Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-08-26T19:55:59.0749362Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-08-26T19:55:59.0749522Z >>> merged_data = [p.planner_data for p in global_plan] 2025-08-26T19:55:59.0749694Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-08-26T19:55:59.0749816Z >>> return global_plan, metadata 2025-08-26T19:55:59.0749872Z 2025-08-26T19:55:59.0750128Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0750133Z 2025-08-26T19:55:59.0750781Z msg = Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-08-26T19:55:59.0751051Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0751072Z 2025-08-26T19:55:59.0751361Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-08-26T19:55:59.0751366Z 2025-08-26T19:55:59.0751656Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-08-26T19:55:59.0751660Z 2025-08-26T19:55:59.0751954Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T19:55:59.0752074Z will be visible to the whole process. 2025-08-26T19:55:59.0752079Z 2025-08-26T19:55:59.0752376Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-08-26T19:55:59.0752381Z 2025-08-26T19:55:59.0752500Z 1) set_up_planner - called on all ranks. 2025-08-26T19:55:59.0752645Z Signals the start of loading a checkpoint. 2025-08-26T19:55:59.0752649Z 2025-08-26T19:55:59.0752771Z 2) create_local_plan - called on all ranks. 2025-08-26T19:55:59.0753061Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-08-26T19:55:59.0753067Z 2025-08-26T19:55:59.0753262Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T19:55:59.0753461Z Takes the LoadPlan from all ranks and make any global decision. 2025-08-26T19:55:59.0753466Z 2025-08-26T19:55:59.0753625Z 4) load_bytes - called multiple times on each rank 2025-08-26T19:55:59.0753793Z This is called once per non-tensor value in state_dict. 2025-08-26T19:55:59.0753797Z 2025-08-26T19:55:59.0754033Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-08-26T19:55:59.0754217Z They are called in pair for each Tensor value in state_dict. 2025-08-26T19:55:59.0754222Z 2025-08-26T19:55:59.0754528Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-08-26T19:55:59.0754723Z most changes can be expressed by changes in a single method. 2025-08-26T19:55:59.0754728Z 2025-08-26T19:55:59.0754888Z There are two usual patterns of extension: 2025-08-26T19:55:59.0754894Z 2025-08-26T19:55:59.0755163Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-08-26T19:55:59.0755421Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-08-26T19:55:59.0755650Z to keep a reference to the original state_dict as load happens in place so 2025-08-26T19:55:59.0755786Z we need to be able to perform it in place 2025-08-26T19:55:59.0755790Z 2025-08-26T19:55:59.0755903Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0756049Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-08-26T19:55:59.0756153Z >>> def set_up_planner( 2025-08-26T19:55:59.0756239Z >>> self, 2025-08-26T19:55:59.0756363Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T19:55:59.0756463Z >>> metadata: Metadata, 2025-08-26T19:55:59.0756711Z >>> is_coordinator: bool, 2025-08-26T19:55:59.0756802Z >>> ) -> None: 2025-08-26T19:55:59.0756931Z >>> self.original_state_dict = state_dict 2025-08-26T19:55:59.0757160Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-08-26T19:55:59.0757244Z >>> 2025-08-26T19:55:59.0757378Z >>> if self.flatten_sharded_tensors: 2025-08-26T19:55:59.0757534Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-08-26T19:55:59.0757616Z >>> 2025-08-26T19:55:59.0757737Z >>> if self.flatten_state_dict: 2025-08-26T19:55:59.0757921Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-08-26T19:55:59.0758017Z >>> 2025-08-26T19:55:59.0758175Z >>> self.state_dict = state_dict 2025-08-26T19:55:59.0758282Z >>> self.metadata = metadata 2025-08-26T19:55:59.0758417Z >>> self.is_coordinator = is_coordinator 2025-08-26T19:55:59.0758499Z >>> 2025-08-26T19:55:59.0758633Z >>> def load_bytes(self, read_item, value): 2025-08-26T19:55:59.0758737Z >>> # Remove the "foo_" prefix 2025-08-26T19:55:59.0759060Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-08-26T19:55:59.0759069Z 2025-08-26T19:55:59.0759073Z 2025-08-26T19:55:59.0759349Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-08-26T19:55:59.0759353Z 2025-08-26T19:55:59.0759467Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.0759637Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-08-26T19:55:59.0759756Z >>> def resolve_tensor(self, read_item): 2025-08-26T19:55:59.0759889Z >>> tensor = super().resolve_tensor(read_item) 2025-08-26T19:55:59.0760052Z >>> return torch.empty_like(tensor, device="cpu") 2025-08-26T19:55:59.0760134Z >>> 2025-08-26T19:55:59.0760276Z >>> def commit_tensor(self, read_item, tensor): 2025-08-26T19:55:59.0760434Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-08-26T19:55:59.0760438Z 2025-08-26T19:55:59.0760695Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0760715Z 2025-08-26T19:55:59.0952833Z msg = Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py line=1118. 2025-08-26T19:55:59.0953107Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0953124Z 2025-08-26T19:55:59.0953293Z Return the model state_dict and optimizers state_dict. 2025-08-26T19:55:59.0953298Z 2025-08-26T19:55:59.0953521Z ``get_state_dict`` can process any module that is parallelized by PyTorch 2025-08-26T19:55:59.0953801Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any 2025-08-26T19:55:59.0954056Z combination of these parallelisms. The main functions of ``get_state_dict`` 2025-08-26T19:55:59.0954291Z are: 1.) returning a model and optimizer state_dict that can be resharded 2025-08-26T19:55:59.0954504Z with a different number of trainers and/or different parallelisms. 2025-08-26T19:55:59.0954758Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call 2025-08-26T19:55:59.0955007Z these APIs. 2025-08-26T19:55:59.0955176Z 3.) sanity checking the result state_dict. 2025-08-26T19:55:59.0955181Z 2025-08-26T19:55:59.0955410Z The keys of the result state dictionary are the canonical FQNs (Fully 2025-08-26T19:55:59.0955650Z Qualified Names). A canonical FQN refers to the FQN based on a parameter's 2025-08-26T19:55:59.0955889Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a 2025-08-26T19:55:59.0956110Z parameter is the FQN returned by ``module.named_parameters()`` or 2025-08-26T19:55:59.0956325Z ``module.named_buffers()`` when the module is not distributed by any 2025-08-26T19:55:59.0956597Z parallelisms. Since the optimizer internally uses parameter IDs to represent 2025-08-26T19:55:59.0956816Z a parameter, there will be a conversion from the parameter IDs to the 2025-08-26T19:55:59.0956933Z canonical FQNs when calling this API. 2025-08-26T19:55:59.0956951Z 2025-08-26T19:55:59.0957177Z ``get_state_dict`` can also process a module that is not parallelized. In 2025-08-26T19:55:59.0957452Z such a case, ``get_state_dict`` only performs one function -- converting the 2025-08-26T19:55:59.0957609Z optimizer parameter IDs to the canonical FQNs. 2025-08-26T19:55:59.0957614Z 2025-08-26T19:55:59.0957716Z Example: 2025-08-26T19:55:59.0957829Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.0957920Z >>> import torch 2025-08-26T19:55:59.0958161Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:55:59.0958469Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T19:55:59.0958699Z >>> from torch.distributed.checkpoint.state_dict import get_state_dict 2025-08-26T19:55:59.0958703Z 2025-08-26T19:55:59.0958846Z >>> fsdp_model = FSDP(copy.deepcopy(model)) 2025-08-26T19:55:59.0959034Z >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T19:55:59.0959171Z >>> ddp_model = DDP(copy.deepcopy(model)) 2025-08-26T19:55:59.0959355Z >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T19:55:59.0959361Z 2025-08-26T19:55:59.0959365Z 2025-08-26T19:55:59.0959603Z >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim) 2025-08-26T19:55:59.0959789Z >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict( 2025-08-26T19:55:59.0959896Z ... fsdp_model, fsdp_optim 2025-08-26T19:55:59.0959996Z ... ) 2025-08-26T19:55:59.0960000Z 2025-08-26T19:55:59.0960218Z >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(), 2025-08-26T19:55:59.0960329Z >>> # the asserts will fail. 2025-08-26T19:55:59.0960473Z >>> assert ddp_state_dict == fsdp_state_dict 2025-08-26T19:55:59.0960623Z >>> assert ddp_optim_state == fsdp_optim_state_dict 2025-08-26T19:55:59.0960628Z 2025-08-26T19:55:59.0960632Z 2025-08-26T19:55:59.0960728Z Args: 2025-08-26T19:55:59.0960866Z model (nn.Module): the nn.Module to the model. 2025-08-26T19:55:59.0961071Z optimizers (Union[None, Optimizer, Iterable[Optimizer]]): 2025-08-26T19:55:59.0961235Z The optimizers that are used to optimize ``model``. 2025-08-26T19:55:59.0961517Z submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters 2025-08-26T19:55:59.0961642Z that belong to the submodules. 2025-08-26T19:55:59.0961812Z options (StateDictOptions): the options to control how 2025-08-26T19:55:59.0962035Z model state_dict and optimizer state_dict should be returned. See 2025-08-26T19:55:59.0962156Z `StateDictOptions` for the details. 2025-08-26T19:55:59.0962161Z 2025-08-26T19:55:59.0962252Z Returns: 2025-08-26T19:55:59.0962460Z ``Tuple`` that contain model state_dict and optimizer state_dict. 2025-08-26T19:55:59.0962464Z 2025-08-26T19:55:59.0962693Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType] 2025-08-26T19:55:59.0962698Z 2025-08-26T19:55:59.0962967Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.0962999Z 2025-08-26T19:55:59.0993051Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=69. 2025-08-26T19:55:59.0993367Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.0993372Z 2025-08-26T19:55:59.0993572Z Load a checkpoint into a distributed state dict in SPMD style. 2025-08-26T19:55:59.0993577Z 2025-08-26T19:55:59.0993818Z Each rank must have the same keys in their ``state_dict`` provided to this 2025-08-26T19:55:59.0994074Z API. Mismatched keys may result in hangs or errors. If unsure, you can use 2025-08-26T19:55:59.0994295Z the ``utils._assert_same_keys`` API to check (but may incur communication 2025-08-26T19:55:59.0994399Z costs). 2025-08-26T19:55:59.0994404Z 2025-08-26T19:55:59.0994610Z Each rank will try to read the least amount of data necessary 2025-08-26T19:55:59.0994861Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor` 2025-08-26T19:55:59.0995169Z or :class:`DTensor` instances, each rank only reads data for their local shards. 2025-08-26T19:55:59.0995173Z 2025-08-26T19:55:59.0995453Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T19:55:59.0995715Z load will first call ``state_dict`` before attempting deserialization, followed by 2025-08-26T19:55:59.0995902Z ``load_state_dict`` once the deserialization is complete. 2025-08-26T19:55:59.0996164Z For each non-``Stateful`` object, load will deserialize the object, and then replace 2025-08-26T19:55:59.0996374Z it in the ``state_dict`` with the deserialized object. 2025-08-26T19:55:59.0996380Z 2025-08-26T19:55:59.0996495Z .. warning:: 2025-08-26T19:55:59.0996667Z All tensors in ``state_dict`` must be allocated on their 2025-08-26T19:55:59.0996853Z destination device *prior to* calling this function. 2025-08-26T19:55:59.0996857Z 2025-08-26T19:55:59.0997089Z All non-tensor data is loaded using `torch.load()` and modified in place 2025-08-26T19:55:59.0997187Z on state_dict. 2025-08-26T19:55:59.0997206Z 2025-08-26T19:55:59.0997298Z .. warning:: 2025-08-26T19:55:59.0997507Z Users must call `load_state_dict` on the root module to ensure load 2025-08-26T19:55:59.0997706Z pos-processing and non-tensor data properly propagates. 2025-08-26T19:55:59.0997710Z 2025-08-26T19:55:59.0997797Z .. note: 2025-08-26T19:55:59.0998025Z If no process group is initialized, this function will assume the intent 2025-08-26T19:55:59.0998269Z is to load a checkpoint into the local process. This can be useful in the 2025-08-26T19:55:59.0998522Z case of local inference, and when using regular Tensors (as opposed to DTensor 2025-08-26T19:55:59.0998637Z or ShardedTensor) 2025-08-26T19:55:59.0998642Z 2025-08-26T19:55:59.0998728Z .. note: 2025-08-26T19:55:59.0998882Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T19:55:59.0998886Z 2025-08-26T19:55:59.0998972Z Args: 2025-08-26T19:55:59.0999187Z state_dict (Dict[str, Any]): The state_dict to load the checkpoint into. 2025-08-26T19:55:59.0999348Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T19:55:59.0999562Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T19:55:59.0999781Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T19:55:59.0999954Z It can also be a key if the storage is a key-value store. 2025-08-26T19:55:59.1000052Z (Default: ``None``) 2025-08-26T19:55:59.1000199Z storage_reader (Optional[StorageReader]): 2025-08-26T19:55:59.1000411Z Instance of StorageWriter used to perform reads. If this is not 2025-08-26T19:55:59.1000629Z specified, DCP will automatically infer the reader based on the 2025-08-26T19:55:59.1000833Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T19:55:59.1000942Z be raised. (Default: ``None``) 2025-08-26T19:55:59.1001099Z planner (Optional[LoadPlanner]): 2025-08-26T19:55:59.1001305Z Instance of LoadPlanner. If this is not specified, the default 2025-08-26T19:55:59.1001445Z planner will be used. (Default: ``None``) 2025-08-26T19:55:59.1001572Z process_group (Optional[ProcessGroup]): 2025-08-26T19:55:59.1001758Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T19:55:59.1001865Z (Default: ``None``) 2025-08-26T19:55:59.1002081Z no_dist (bool): If ``True``, this function will assume the intent is to load 2025-08-26T19:55:59.1002355Z a checkpoint without using cross-rank synchronization. (Default: ``False``) 2025-08-26T19:55:59.1002542Z Returns: 2025-08-26T19:55:59.1002628Z None. 2025-08-26T19:55:59.1002633Z 2025-08-26T19:55:59.1002731Z Examples 2025-08-26T19:55:59.1002829Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.1002944Z >>> my_model = MyModule() 2025-08-26T19:55:59.1003081Z >>> optimizer = Adagrad(my_model.parameters()) 2025-08-26T19:55:59.1003209Z >>> model_state_dict = my_model.state_dict() 2025-08-26T19:55:59.1003488Z >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader( 2025-08-26T19:55:59.1003586Z ... "/checkpoint/1" 2025-08-26T19:55:59.1003680Z ... ) 2025-08-26T19:55:59.1003685Z 2025-08-26T19:55:59.1003841Z >>> torch.distributed.checkpoint.load_state_dict( 2025-08-26T19:55:59.1003952Z >>> state_dict=model_state_dict, 2025-08-26T19:55:59.1004081Z >>> storage_reader=fs_storage_reader, 2025-08-26T19:55:59.1004164Z >>> ) 2025-08-26T19:55:59.1004168Z 2025-08-26T19:55:59.1004431Z >>> # module.load_state_dict() function might have customized steps 2025-08-26T19:55:59.1004559Z >>> # to flush the state_dict, must call it to 2025-08-26T19:55:59.1004668Z >>> # ensure correct behavior. 2025-08-26T19:55:59.1004814Z >>> my_model.load_state_dict(model_state_dict) 2025-08-26T19:55:59.1004819Z 2025-08-26T19:55:59.1004905Z .. note:: 2025-08-26T19:55:59.1005134Z load_state_dict uses collectives to coordinate reads across ranks. 2025-08-26T19:55:59.1005354Z For NCCL-based process groups, internal tensor representations of 2025-08-26T19:55:59.1005587Z objects must be moved to the GPU device before communication takes place. 2025-08-26T19:55:59.1005823Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T19:55:59.1006132Z and it is the user's responsibility to ensure that this is set so that each 2025-08-26T19:55:59.1006352Z rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T19:55:59.1006357Z 2025-08-26T19:55:59.1006620Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.1006624Z 2025-08-26T19:55:59.1031261Z msg = Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=97. 2025-08-26T19:55:59.1031535Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.1031545Z 2025-08-26T19:55:59.1031669Z Save a distributed model in SPMD style. 2025-08-26T19:55:59.1031686Z 2025-08-26T19:55:59.1031880Z This function is different from ``torch.save()`` as it handles 2025-08-26T19:55:59.1032139Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards. 2025-08-26T19:55:59.1032144Z 2025-08-26T19:55:59.1032439Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T19:55:59.1032589Z save will call ``state_dict`` before serialization. 2025-08-26T19:55:59.1032605Z 2025-08-26T19:55:59.1032699Z .. warning:: 2025-08-26T19:55:59.1032943Z There is no guarantees of Backwards Compatibility across PyTorch versions 2025-08-26T19:55:59.1033055Z for saved state_dicts. 2025-08-26T19:55:59.1033060Z 2025-08-26T19:55:59.1033147Z .. warning:: 2025-08-26T19:55:59.1033372Z If using the `process_group` argument, make sure that only its ranks 2025-08-26T19:55:59.1033579Z call `save_state_dict` and that all data in state_dict belong to it. 2025-08-26T19:55:59.1033637Z 2025-08-26T19:55:59.1033725Z .. note:: 2025-08-26T19:55:59.1034005Z When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of 2025-08-26T19:55:59.1034274Z the shard_group should be calling `save_state_dict` and the corresponding process 2025-08-26T19:55:59.1034400Z group needs to be passed in. 2025-08-26T19:55:59.1034404Z 2025-08-26T19:55:59.1034492Z .. note:: 2025-08-26T19:55:59.1034766Z If no process group is available, this function assumes the intention is to save the 2025-08-26T19:55:59.1034900Z state_dict in the local process. 2025-08-26T19:55:59.1034904Z 2025-08-26T19:55:59.1034991Z .. note: 2025-08-26T19:55:59.1035145Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T19:55:59.1035150Z 2025-08-26T19:55:59.1035153Z 2025-08-26T19:55:59.1035237Z Args: 2025-08-26T19:55:59.1035396Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T19:55:59.1035556Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T19:55:59.1035804Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T19:55:59.1036025Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T19:55:59.1036196Z It can also be a key if the storage is a key-value store. 2025-08-26T19:55:59.1036294Z (Default: ``None``) 2025-08-26T19:55:59.1036438Z storage_writer (Optional[StorageWriter]): 2025-08-26T19:55:59.1036651Z Instance of StorageWriter used to perform writes. If this is not 2025-08-26T19:55:59.1036924Z specified, DCP will automatically infer the writer based on the 2025-08-26T19:55:59.1037129Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T19:55:59.1037238Z be raised. (Default: ``None``) 2025-08-26T19:55:59.1037512Z planner (Optional[SavePlanner]): 2025-08-26T19:55:59.1037720Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T19:55:59.1037882Z planner will be used. (Default: ``None``) 2025-08-26T19:55:59.1038088Z process_group (Optional[ProcessGroup]): 2025-08-26T19:55:59.1038331Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T19:55:59.1038490Z (Default: ``None``) 2025-08-26T19:55:59.1038580Z no_dist (bool): 2025-08-26T19:55:59.1038764Z If ``True``, this function will assume the intent is to load 2025-08-26T19:55:59.1038891Z a checkpoint on a single rank/process. 2025-08-26T19:55:59.1038990Z (Default: ``False``) 2025-08-26T19:55:59.1039272Z use_collectives (bool): If ``False``, this function will assume the intent is to save 2025-08-26T19:55:59.1039448Z a checkpoint without using cross-rank synchronization. 2025-08-26T19:55:59.1039556Z (Default: ``True``) 2025-08-26T19:55:59.1039785Z This configuration is experimental and should be used with caution. 2025-08-26T19:55:59.1040062Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T19:55:59.1040086Z 2025-08-26T19:55:59.1040176Z Returns: 2025-08-26T19:55:59.1040337Z Metadata: Metadata object for the saved checkpoint. 2025-08-26T19:55:59.1040342Z 2025-08-26T19:55:59.1040441Z Example: 2025-08-26T19:55:59.1040539Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.1040639Z >>> my_model = MyModule() 2025-08-26T19:55:59.1040657Z 2025-08-26T19:55:59.1040765Z >>> state_dict = {"model": my_model} 2025-08-26T19:55:59.1040769Z 2025-08-26T19:55:59.1041003Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T19:55:59.1041116Z ... "/checkpoint/1" 2025-08-26T19:55:59.1041199Z ... ) 2025-08-26T19:55:59.1041343Z >>> torch.distributed.checkpoint.save( 2025-08-26T19:55:59.1041446Z >>> state_dict=state_dict, 2025-08-26T19:55:59.1041563Z >>> storage_writer=fs_storage_writer, 2025-08-26T19:55:59.1041656Z >>> ) 2025-08-26T19:55:59.1041660Z 2025-08-26T19:55:59.1041825Z .. note:: 2025-08-26T19:55:59.1042057Z save_state_dict uses collectives to coordinate writes across ranks. 2025-08-26T19:55:59.1042275Z For NCCL-based process groups, internal tensor representations of 2025-08-26T19:55:59.1042509Z objects must be moved to the GPU device before communication takes place. 2025-08-26T19:55:59.1042744Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T19:55:59.1042951Z and it is the user's responsibility to ensure that this is set so that 2025-08-26T19:55:59.1043164Z each rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T19:55:59.1043172Z 2025-08-26T19:55:59.1043428Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.1043433Z 2025-08-26T19:55:59.1044114Z msg = Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=230. 2025-08-26T19:55:59.1044383Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.1044709Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the 2025-08-26T19:55:59.1045001Z staging storage (defaults to CPU memory), and then calls the `save` in a separate thread. 2025-08-26T19:55:59.1045005Z 2025-08-26T19:55:59.1045111Z .. warning:: 2025-08-26T19:55:59.1045273Z This feature is experimental and subject to change. 2025-08-26T19:55:59.1045421Z MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED 2025-08-26T19:55:59.1045425Z 2025-08-26T19:55:59.1045623Z Args: 2025-08-26T19:55:59.1045866Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T19:55:59.1046029Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T19:55:59.1046247Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T19:55:59.1046453Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T19:55:59.1046639Z It can also be a key if the storage is a key-value store. 2025-08-26T19:55:59.1046743Z (Default: ``None``) 2025-08-26T19:55:59.1046895Z storage_writer (Optional[StorageWriter]): 2025-08-26T19:55:59.1047111Z Instance of StorageWriter used to perform 'stage' and 'save'. If 2025-08-26T19:55:59.1047354Z this is not specified, DCP will automatically infer the writer based on the 2025-08-26T19:55:59.1047578Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T19:55:59.1047690Z be raised. (Default: ``None``) 2025-08-26T19:55:59.1047827Z planner (Optional[SavePlanner]): 2025-08-26T19:55:59.1048029Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T19:55:59.1048162Z planner will be used. (Default: ``None``) 2025-08-26T19:55:59.1048306Z process_group (Optional[ProcessGroup]): 2025-08-26T19:55:59.1048493Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T19:55:59.1048607Z (Default: ``None``) 2025-08-26T19:55:59.1058441Z async_checkpointer_type (AsyncCheckpointerType): 2025-08-26T19:55:59.1058719Z whether to do checkpoint in separate thread or process 2025-08-26T19:55:59.1058888Z (Default: ``AsyncCheckpointerType.THREAD``) 2025-08-26T19:55:59.1059002Z async_stager (AsyncStager): 2025-08-26T19:55:59.1059270Z provides staging implementation. If storage_writer implements AsyncStager 2025-08-26T19:55:59.1059512Z and async_stager is provided, async_stager will be used for staging 2025-08-26T19:55:59.1059608Z no_dist (bool): 2025-08-26T19:55:59.1059796Z If ``True``, this function will assume the intent is to save 2025-08-26T19:55:59.1059930Z a checkpoint on a single rank/process. 2025-08-26T19:55:59.1060031Z (Default: ``False``) 2025-08-26T19:55:59.1060366Z use_collectives: If False, Save the checkpoint without rank coordination. (Default: ``True``) 2025-08-26T19:55:59.1060682Z This configuration is experimental and should be used with caution. 2025-08-26T19:55:59.1060972Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T19:55:59.1060979Z 2025-08-26T19:55:59.1061069Z Returns: 2025-08-26T19:55:59.1061288Z Future: A future holding the resultant Metadata object from `save`. 2025-08-26T19:55:59.1061308Z 2025-08-26T19:55:59.1061399Z Example: 2025-08-26T19:55:59.1061499Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.1061620Z >>> my_model = MyModule() 2025-08-26T19:55:59.1061625Z 2025-08-26T19:55:59.1061742Z >>> state_dict = {"model": my_model} 2025-08-26T19:55:59.1061747Z 2025-08-26T19:55:59.1062000Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T19:55:59.1062103Z ... "/checkpoint/1" 2025-08-26T19:55:59.1062190Z ... ) 2025-08-26T19:55:59.1062418Z >>> checkpoint_future = torch.distributed.checkpoint.async_save( 2025-08-26T19:55:59.1062561Z >>> state_dict=state_dict, 2025-08-26T19:55:59.1062700Z >>> storage_writer=fs_storage_writer, 2025-08-26T19:55:59.1062786Z >>> ) 2025-08-26T19:55:59.1062861Z >>> 2025-08-26T19:55:59.1062967Z >>> # ... do some work ... 2025-08-26T19:55:59.1063053Z >>> 2025-08-26T19:55:59.1063165Z >>> checkpoint_future.result() 2025-08-26T19:55:59.1063175Z 2025-08-26T19:55:59.1063258Z 2025-08-26T19:55:59.1063573Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.1063578Z 2025-08-26T19:55:59.1386410Z msg = Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/events/__init__.py line=94. 2025-08-26T19:55:59.1386681Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.1386693Z 2025-08-26T19:55:59.1386913Z Initialize rendezvous event object and record its operations. 2025-08-26T19:55:59.1386920Z 2025-08-26T19:55:59.1387003Z Args: 2025-08-26T19:55:59.1387150Z run_id (str): The run id of the rendezvous. 2025-08-26T19:55:59.1387304Z message (str): The message describing the event. 2025-08-26T19:55:59.1387564Z node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED). 2025-08-26T19:55:59.1387766Z name (str): Event name. (E.g. Current action being performed). 2025-08-26T19:55:59.1387884Z hostname (str): Hostname of the node. 2025-08-26T19:55:59.1388049Z pid (Optional[int]): The process id of the node. 2025-08-26T19:55:59.1388297Z master_endpoint (str): The master endpoint for the rendezvous store, if known. 2025-08-26T19:55:59.1388588Z local_id (Optional[int]): The local_id of the node, if defined in dynamic_rendezvous.py 2025-08-26T19:55:59.1388753Z rank (Optional[int]): The rank of the node, if known. 2025-08-26T19:55:59.1388843Z Returns: 2025-08-26T19:55:59.1388943Z None 2025-08-26T19:55:59.1389029Z Example: 2025-08-26T19:55:59.1389157Z >>> # See DynamicRendezvousHandler class 2025-08-26T19:55:59.1389259Z >>> def _record( 2025-08-26T19:55:59.1389345Z ... self, 2025-08-26T19:55:59.1389454Z ... message: str, 2025-08-26T19:55:59.1389596Z ... node_state: NodeState = NodeState.RUNNING, 2025-08-26T19:55:59.1389704Z ... rank: Optional[int] = None, 2025-08-26T19:55:59.1389807Z ... ) -> None: 2025-08-26T19:55:59.1389926Z ... construct_and_record_rdzv_event( 2025-08-26T19:55:59.1390112Z ... name=f"{self.__class__.__name__}.{get_method_name()}", 2025-08-26T19:55:59.1390230Z ... run_id=self._settings.run_id, 2025-08-26T19:55:59.1390330Z ... message=message, 2025-08-26T19:55:59.1390448Z ... node_state=node_state, 2025-08-26T19:55:59.1390568Z ... hostname=self._this_node.addr, 2025-08-26T19:55:59.1390793Z ... pid=self._this_node.pid, 2025-08-26T19:55:59.1390919Z ... local_id=self._this_node.local_id, 2025-08-26T19:55:59.1391011Z ... rank=rank, 2025-08-26T19:55:59.1391111Z ... ) 2025-08-26T19:55:59.1391116Z 2025-08-26T19:55:59.1391376Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.1391381Z 2025-08-26T19:55:59.5291230Z msg = Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=114. 2025-08-26T19:55:59.5292307Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.5292712Z 2025-08-26T19:55:59.5292899Z This configures FSDP-native mixed precision training. 2025-08-26T19:55:59.5293191Z 2025-08-26T19:55:59.5293298Z Attributes: 2025-08-26T19:55:59.5293664Z param_dtype (Optional[torch.dtype]): This specifies the dtype for model 2025-08-26T19:55:59.5294244Z parameters during forward and backward and thus the dtype for 2025-08-26T19:55:59.5295029Z forward and backward computation. Outside forward and backward, the 2025-08-26T19:55:59.5295588Z *sharded* parameters are kept in full precision (e.g. for the 2025-08-26T19:55:59.5296130Z optimizer step), and for model checkpointing, the parameters are 2025-08-26T19:55:59.5296615Z always saved in full precision. (Default: ``None``) 2025-08-26T19:55:59.5297119Z reduce_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T19:55:59.5297689Z gradient reduction (i.e. reduce-scatter or all-reduce). If this is 2025-08-26T19:55:59.5298318Z ``None`` but ``param_dtype`` is not ``None``, then this takes on 2025-08-26T19:55:59.5299096Z the ``param_dtype`` value, still running gradient reduction in low 2025-08-26T19:55:59.5299868Z precision. This is permitted to differ from ``param_dtype``, e.g. 2025-08-26T19:55:59.5300827Z to force gradient reduction to run in full precision. (Default: 2025-08-26T19:55:59.5301247Z ``None``) 2025-08-26T19:55:59.5301622Z buffer_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T19:55:59.5302158Z buffers. FSDP does not shard buffers. Rather, FSDP casts them to 2025-08-26T19:55:59.5302692Z ``buffer_dtype`` in the first forward pass and keeps them in that 2025-08-26T19:55:59.5303234Z dtype thereafter. For model checkpointing, the buffers are saved 2025-08-26T19:55:59.5303759Z in full precision except for ``LOCAL_STATE_DICT``. (Default: 2025-08-26T19:55:59.5304144Z ``None``) 2025-08-26T19:55:59.5304497Z keep_low_precision_grads (bool): If ``False``, then FSDP upcasts 2025-08-26T19:55:59.5305048Z gradients to full precision after the backward pass in preparation 2025-08-26T19:55:59.5305603Z for the optimizer step. If ``True``, then FSDP keeps the gradients 2025-08-26T19:55:59.5306128Z in the dtype used for gradient reduction, which can save memory if 2025-08-26T19:55:59.5306673Z using a custom optimizer that supports running in low precision. 2025-08-26T19:55:59.5307109Z (Default: ``False``) 2025-08-26T19:55:59.5307510Z cast_forward_inputs (bool): If ``True``, then this FSDP module casts 2025-08-26T19:55:59.5308054Z its forward args and kwargs to ``param_dtype``. This is to ensure 2025-08-26T19:55:59.5308588Z that parameter and input dtypes match for forward computation, as 2025-08-26T19:55:59.5309136Z required by many ops. This may need to be set to ``True`` when only 2025-08-26T19:55:59.5309697Z applying mixed precision to some but not all FSDP modules, in which 2025-08-26T19:55:59.5310262Z case a mixed-precision FSDP submodule needs to recast its inputs. 2025-08-26T19:55:59.5310686Z (Default: ``False``) 2025-08-26T19:55:59.5311101Z cast_root_forward_inputs (bool): If ``True``, then the root FSDP module 2025-08-26T19:55:59.5311653Z casts its forward args and kwargs to ``param_dtype``, overriding 2025-08-26T19:55:59.5312297Z the value of ``cast_forward_inputs``. For non-root FSDP modules, 2025-08-26T19:55:59.5312762Z this does not do anything. (Default: ``True``) 2025-08-26T19:55:59.5313239Z _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies 2025-08-26T19:55:59.5313773Z module classes to ignore for mixed precision when using an 2025-08-26T19:55:59.5314273Z ``auto_wrap_policy``: Modules of these classes will have FSDP 2025-08-26T19:55:59.5314802Z applied to them separately with mixed precision disabled (meaning 2025-08-26T19:55:59.5315347Z that the final FSDP construction would deviate from the specified 2025-08-26T19:55:59.5315873Z policy). If ``auto_wrap_policy`` is not specified, then this does 2025-08-26T19:55:59.5316402Z not do anything. This API is experimental and subject to change. 2025-08-26T19:55:59.5316841Z (Default: ``(_BatchNorm,)``) 2025-08-26T19:55:59.5317055Z 2025-08-26T19:55:59.5317256Z .. note:: This API is experimental and subject to change. 2025-08-26T19:55:59.5317583Z 2025-08-26T19:55:59.5317813Z .. note:: Only floating point tensors are cast to their specified dtypes. 2025-08-26T19:55:59.5318170Z 2025-08-26T19:55:59.5318358Z .. note:: In ``summon_full_params``, parameters are forced to full 2025-08-26T19:55:59.5318777Z precision, but buffers are not. 2025-08-26T19:55:59.5318994Z 2025-08-26T19:55:59.5319215Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when 2025-08-26T19:55:59.5319768Z their inputs are in a low precision like ``float16`` or ``bfloat16``. 2025-08-26T19:55:59.5320406Z Disabling FSDP's mixed precision for those norm modules only means that 2025-08-26T19:55:59.5320993Z the affine parameters are kept in ``float32``. However, this incurs 2025-08-26T19:55:59.5321577Z separate all-gathers and reduce-scatters for those norm modules, which 2025-08-26T19:55:59.5322177Z may be inefficient, so if the workload permits, the user should prefer 2025-08-26T19:55:59.5322680Z to still apply mixed precision to those modules. 2025-08-26T19:55:59.5322959Z 2025-08-26T19:55:59.5323174Z .. note:: By default, if the user passes a model with any ``_BatchNorm`` 2025-08-26T19:55:59.5323727Z modules and specifies an ``auto_wrap_policy``, then the batch norm 2025-08-26T19:55:59.5324291Z modules will have FSDP applied to them separately with mixed precision 2025-08-26T19:55:59.5324823Z disabled. See the ``_module_classes_to_ignore`` argument. 2025-08-26T19:55:59.5325116Z 2025-08-26T19:55:59.5325332Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and 2025-08-26T19:55:59.5325884Z ``cast_forward_inputs=False`` by default. For the root FSDP instance, 2025-08-26T19:55:59.5326404Z its ``cast_root_forward_inputs`` takes precedence over its 2025-08-26T19:55:59.5326882Z ``cast_forward_inputs``. For non-root FSDP instances, their 2025-08-26T19:55:59.5327400Z ``cast_root_forward_inputs`` values are ignored. The default setting is 2025-08-26T19:55:59.5327974Z sufficient for the typical case where each FSDP instance has the same 2025-08-26T19:55:59.5328562Z ``MixedPrecision`` configuration and only needs to cast inputs to the 2025-08-26T19:55:59.5329211Z ``param_dtype`` at the beginning of the model's forward pass. 2025-08-26T19:55:59.5329515Z 2025-08-26T19:55:59.5329742Z .. note:: For nested FSDP instances with different ``MixedPrecision`` 2025-08-26T19:55:59.5330307Z configurations, we recommend setting individual ``cast_forward_inputs`` 2025-08-26T19:55:59.5330894Z values to configure casting inputs or not before each instance's 2025-08-26T19:55:59.5331429Z forward. In such a case, since the casts happen before each FSDP 2025-08-26T19:55:59.5331974Z instance's forward, a parent FSDP instance should have its non-FSDP 2025-08-26T19:55:59.5332557Z submodules run before its FSDP submodules to avoid the activation dtype 2025-08-26T19:55:59.5333126Z being changed due to a different ``MixedPrecision`` configuration. 2025-08-26T19:55:59.5333517Z 2025-08-26T19:55:59.5333608Z Example:: 2025-08-26T19:55:59.5333753Z 2025-08-26T19:55:59.5333888Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.5334315Z >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3)) 2025-08-26T19:55:59.5334694Z >>> model[1] = FSDP( 2025-08-26T19:55:59.5334975Z >>> model[1], 2025-08-26T19:55:59.5335462Z >>> mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True), 2025-08-26T19:55:59.5335994Z >>> ) 2025-08-26T19:55:59.5336223Z >>> model = FSDP( 2025-08-26T19:55:59.5336490Z >>> model, 2025-08-26T19:55:59.5336968Z >>> mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True), 2025-08-26T19:55:59.5337714Z >>> ) 2025-08-26T19:55:59.5337848Z 2025-08-26T19:55:59.5338075Z The above shows a working example. On the other hand, if ``model[1]`` 2025-08-26T19:55:59.5338615Z were replaced with ``model[0]``, meaning that the submodule using 2025-08-26T19:55:59.5339244Z different ``MixedPrecision`` ran its forward first, then ``model[1]`` 2025-08-26T19:55:59.5339824Z would incorrectly see ``float16`` activations instead of ``bfloat16`` 2025-08-26T19:55:59.5340261Z ones. 2025-08-26T19:55:59.5340384Z 2025-08-26T19:55:59.5340387Z 2025-08-26T19:55:59.5340645Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.5341035Z 2025-08-26T19:55:59.5341771Z msg = Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=295. 2025-08-26T19:55:59.5342763Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.5343168Z 2025-08-26T19:55:59.5343381Z ``FullStateDictConfig`` is a config class meant to be used with 2025-08-26T19:55:59.5343920Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-08-26T19:55:59.5344461Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-08-26T19:55:59.5345014Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-08-26T19:55:59.5345577Z is meant to be used via the :func:`state_dict_type` context manager as 2025-08-26T19:55:59.5345994Z follows: 2025-08-26T19:55:59.5346118Z 2025-08-26T19:55:59.5346261Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.5346752Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:55:59.5347238Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-08-26T19:55:59.5347697Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-08-26T19:55:59.5348253Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-08-26T19:55:59.5348717Z >>> state = fsdp.state_dict() 2025-08-26T19:55:59.5349139Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-08-26T19:55:59.5349728Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-08-26T19:55:59.5350344Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-08-26T19:55:59.5350815Z >>> if dist.get_rank() == 0: 2025-08-26T19:55:59.5351196Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-08-26T19:55:59.5351647Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-08-26T19:55:59.5352031Z >>> model.load_state_dict(state_dict) 2025-08-26T19:55:59.5352513Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-08-26T19:55:59.5353129Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-08-26T19:55:59.5353583Z >>> fsdp = FSDP( 2025-08-26T19:55:59.5353835Z ... model, 2025-08-26T19:55:59.5354114Z ... device_id=torch.cuda.current_device(), 2025-08-26T19:55:59.5354476Z ... auto_wrap_policy=..., 2025-08-26T19:55:59.5354828Z ... sync_module_states=True, 2025-08-26T19:55:59.5355125Z ... ) 2025-08-26T19:55:59.5355468Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-08-26T19:55:59.5355802Z 2025-08-26T19:55:59.5355907Z Attributes: 2025-08-26T19:55:59.5356230Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-08-26T19:55:59.5356762Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-08-26T19:55:59.5357255Z ranks save the full state dict. (Default: ``False``) 2025-08-26T19:55:59.5357528Z 2025-08-26T19:55:59.5357802Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.5358181Z 2025-08-26T19:55:59.5445551Z msg = Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=634. 2025-08-26T19:55:59.5446790Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.5447592Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T19:55:59.5448130Z 2025-08-26T19:55:59.5448405Z Also takes (optional) configuration for the model's and optimizer's state dict. 2025-08-26T19:55:59.5449352Z The target module does not have to be a FSDP module. If the target 2025-08-26T19:55:59.5450115Z module is a FSDP module, its ``state_dict_type`` will also be changed. 2025-08-26T19:55:59.5450448Z 2025-08-26T19:55:59.5450829Z .. note:: This API should be called for only the top-level (root) 2025-08-26T19:55:59.5451232Z module. 2025-08-26T19:55:59.5451392Z 2025-08-26T19:55:59.5451605Z .. note:: This API enables users to transparently use the conventional 2025-08-26T19:55:59.5452138Z ``state_dict`` API to take model checkpoints in cases where the 2025-08-26T19:55:59.5452671Z root FSDP module is wrapped by another ``nn.Module``. For example, 2025-08-26T19:55:59.5453219Z the following will ensure ``state_dict`` is called on all non-FSDP 2025-08-26T19:55:59.5453825Z instances, while dispatching into `sharded_state_dict` implementation 2025-08-26T19:55:59.5454284Z for FSDP: 2025-08-26T19:55:59.5454453Z 2025-08-26T19:55:59.5454543Z Example:: 2025-08-26T19:55:59.5454686Z 2025-08-26T19:55:59.5454836Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.5455203Z >>> model = DDP(FSDP(...)) 2025-08-26T19:55:59.5455530Z >>> FSDP.set_state_dict_type( 2025-08-26T19:55:59.5455851Z >>> model, 2025-08-26T19:55:59.5456158Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T19:55:59.5456628Z >>> state_dict_config = ShardedStateDictConfig(offload_to_cpu=True), 2025-08-26T19:55:59.5457194Z >>> optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True), 2025-08-26T19:55:59.5457642Z >>> ) 2025-08-26T19:55:59.5457921Z >>> param_state_dict = model.state_dict() 2025-08-26T19:55:59.5458350Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T19:55:59.5458643Z 2025-08-26T19:55:59.5458728Z Args: 2025-08-26T19:55:59.5458995Z module (torch.nn.Module): Root module. 2025-08-26T19:55:59.5459481Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T19:55:59.5460094Z state_dict_config (Optional[StateDictConfig]): the configuration for the 2025-08-26T19:55:59.5460594Z target ``state_dict_type``. 2025-08-26T19:55:59.5461064Z optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration 2025-08-26T19:55:59.5461573Z for the optimizer state dict. 2025-08-26T19:55:59.5461800Z 2025-08-26T19:55:59.5461900Z Returns: 2025-08-26T19:55:59.5462271Z A StateDictSettings that include the previous state_dict type and 2025-08-26T19:55:59.5462794Z configuration for the module. 2025-08-26T19:55:59.5463111Z 2025-08-26T19:55:59.5463493Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.5463868Z 2025-08-26T19:55:59.5464710Z msg = Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=792. 2025-08-26T19:55:59.5465920Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.5466561Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T19:55:59.5466949Z 2025-08-26T19:55:59.5467271Z This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of 2025-08-26T19:55:59.5467861Z :meth:`set_state_dict_type` for the detail. 2025-08-26T19:55:59.5468104Z 2025-08-26T19:55:59.5468211Z Example:: 2025-08-26T19:55:59.5468355Z 2025-08-26T19:55:59.5468541Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.5468894Z >>> model = DDP(FSDP(...)) 2025-08-26T19:55:59.5469228Z >>> with FSDP.state_dict_type( 2025-08-26T19:55:59.5469553Z >>> model, 2025-08-26T19:55:59.5469865Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T19:55:59.5470196Z >>> ): 2025-08-26T19:55:59.5470473Z >>> checkpoint = model.state_dict() 2025-08-26T19:55:59.5470731Z 2025-08-26T19:55:59.5470817Z Args: 2025-08-26T19:55:59.5471146Z module (torch.nn.Module): Root module. 2025-08-26T19:55:59.5471621Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T19:55:59.5472225Z state_dict_config (Optional[StateDictConfig]): the model ``state_dict`` 2025-08-26T19:55:59.5472757Z configuration for the target ``state_dict_type``. 2025-08-26T19:55:59.5473294Z optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer 2025-08-26T19:55:59.5473878Z ``state_dict`` configuration for the target ``state_dict_type``. 2025-08-26T19:55:59.5474281Z 2025-08-26T19:55:59.5474668Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.5475045Z 2025-08-26T19:55:59.5504570Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1805. 2025-08-26T19:55:59.5505820Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.5506212Z 2025-08-26T19:55:59.5506636Z Transform the state-dict of an optimizer corresponding to a sharded model. 2025-08-26T19:55:59.5507039Z 2025-08-26T19:55:59.5507251Z The given state-dict can be transformed to one of three types: 2025-08-26T19:55:59.5508212Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict. 2025-08-26T19:55:59.5508892Z 2025-08-26T19:55:59.5509136Z For full optimizer state_dict, all states are unflattened and not sharded. 2025-08-26T19:55:59.5509722Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to 2025-08-26T19:55:59.5510154Z avoid OOM. 2025-08-26T19:55:59.5510280Z 2025-08-26T19:55:59.5510531Z For sharded optimizer state_dict, all states are unflattened but sharded. 2025-08-26T19:55:59.5511103Z CPU only can be specified via :meth:`state_dict_type` to further save 2025-08-26T19:55:59.5511510Z memory. 2025-08-26T19:55:59.5511644Z 2025-08-26T19:55:59.5511865Z For local state_dict, no transformation will be performed. But a state 2025-08-26T19:55:59.5512455Z will be converted from nn.Tensor to ShardedTensor to represent its sharding 2025-08-26T19:55:59.5512936Z nature (this is not supported yet). 2025-08-26T19:55:59.5513147Z 2025-08-26T19:55:59.5513248Z Example:: 2025-08-26T19:55:59.5513467Z 2025-08-26T19:55:59.5513597Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.5514096Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:55:59.5514627Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T19:55:59.5515090Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T19:55:59.5515584Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T19:55:59.5516009Z >>> # Save a checkpoint 2025-08-26T19:55:59.5516291Z >>> model, optim = ... 2025-08-26T19:55:59.5516576Z >>> FSDP.set_state_dict_type( 2025-08-26T19:55:59.5516861Z >>> model, 2025-08-26T19:55:59.5517129Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:55:59.5517494Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5517894Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5518232Z >>> ) 2025-08-26T19:55:59.5518468Z >>> state_dict = model.state_dict() 2025-08-26T19:55:59.5518868Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T19:55:59.5519354Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T19:55:59.5519711Z >>> # Load a checkpoint 2025-08-26T19:55:59.5519999Z >>> model, optim = ... 2025-08-26T19:55:59.5520343Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T19:55:59.5520729Z >>> FSDP.set_state_dict_type( 2025-08-26T19:55:59.5521014Z >>> model, 2025-08-26T19:55:59.5521287Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:55:59.5521722Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5522123Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5522461Z >>> ) 2025-08-26T19:55:59.5522700Z >>> model.load_state_dict(state_dict) 2025-08-26T19:55:59.5523089Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T19:55:59.5523478Z >>> model, optim, optim_state_dict 2025-08-26T19:55:59.5523781Z >>> ) 2025-08-26T19:55:59.5524035Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T19:55:59.5524291Z 2025-08-26T19:55:59.5524374Z Args: 2025-08-26T19:55:59.5524698Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T19:55:59.5525219Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T19:55:59.5525686Z were passed into the optimizer ``optim``. 2025-08-26T19:55:59.5526129Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T19:55:59.5526534Z parameters. 2025-08-26T19:55:59.5526900Z optim_state_dict (Dict[str, Any]): the target optimizer state_dict to 2025-08-26T19:55:59.5527460Z transform. If the value is None, optim.state_dict() will be used. ( 2025-08-26T19:55:59.5527904Z Default: ``None``) 2025-08-26T19:55:59.5528332Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T19:55:59.5528980Z are sharded or ``None`` if using the default process group. ( 2025-08-26T19:55:59.5529389Z Default: ``None``) 2025-08-26T19:55:59.5529579Z 2025-08-26T19:55:59.5529666Z Returns: 2025-08-26T19:55:59.5529992Z Dict[str, Any]: A :class:`dict` containing the optimizer state for 2025-08-26T19:55:59.5530485Z ``model``. The sharding of the optimizer state is based on 2025-08-26T19:55:59.5530867Z ``state_dict_type``. 2025-08-26T19:55:59.5531050Z 2025-08-26T19:55:59.5531312Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.5531704Z 2025-08-26T19:55:59.5532603Z msg = Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1903. 2025-08-26T19:55:59.5533850Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.5534248Z 2025-08-26T19:55:59.5534613Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model. 2025-08-26T19:55:59.5535148Z 2025-08-26T19:55:59.5535337Z Given a ``optim_state_dict`` that is transformed through 2025-08-26T19:55:59.5535844Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer 2025-08-26T19:55:59.5536389Z state_dict that can be loaded to ``optim`` which is the optimizer for 2025-08-26T19:55:59.5536928Z ``model``. ``model`` must be sharded by FullyShardedDataParallel. 2025-08-26T19:55:59.5537248Z 2025-08-26T19:55:59.5537572Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.5538074Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:55:59.5538598Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T19:55:59.5539044Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T19:55:59.5539555Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T19:55:59.5539981Z >>> # Save a checkpoint 2025-08-26T19:55:59.5540266Z >>> model, optim = ... 2025-08-26T19:55:59.5540625Z >>> FSDP.set_state_dict_type( 2025-08-26T19:55:59.5540926Z >>> model, 2025-08-26T19:55:59.5541196Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:55:59.5541568Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5541955Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5542307Z >>> ) 2025-08-26T19:55:59.5542551Z >>> state_dict = model.state_dict() 2025-08-26T19:55:59.5542898Z >>> original_osd = optim.state_dict() 2025-08-26T19:55:59.5543252Z >>> optim_state_dict = FSDP.optim_state_dict( 2025-08-26T19:55:59.5543672Z >>> model, 2025-08-26T19:55:59.5543910Z >>> optim, 2025-08-26T19:55:59.5544169Z >>> optim_state_dict=original_osd 2025-08-26T19:55:59.5544472Z >>> ) 2025-08-26T19:55:59.5544751Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T19:55:59.5545128Z >>> # Load a checkpoint 2025-08-26T19:55:59.5545421Z >>> model, optim = ... 2025-08-26T19:55:59.5545749Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T19:55:59.5546136Z >>> FSDP.set_state_dict_type( 2025-08-26T19:55:59.5546434Z >>> model, 2025-08-26T19:55:59.5546701Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:55:59.5547057Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5547455Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:55:59.5547803Z >>> ) 2025-08-26T19:55:59.5548046Z >>> model.load_state_dict(state_dict) 2025-08-26T19:55:59.5548424Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T19:55:59.5548814Z >>> model, optim, optim_state_dict 2025-08-26T19:55:59.5549128Z >>> ) 2025-08-26T19:55:59.5549383Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T19:55:59.5549622Z 2025-08-26T19:55:59.5549705Z Args: 2025-08-26T19:55:59.5550029Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T19:55:59.5550561Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T19:55:59.5551028Z were passed into the optimizer ``optim``. 2025-08-26T19:55:59.5551459Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T19:55:59.5551858Z parameters. 2025-08-26T19:55:59.5552230Z optim_state_dict (Dict[str, Any]): The optimizer states to be loaded. 2025-08-26T19:55:59.5552782Z is_named_optimizer (bool): Is this optimizer a NamedOptimizer or 2025-08-26T19:55:59.5553310Z KeyedOptimizer. Only set to True if ``optim`` is TorchRec's 2025-08-26T19:55:59.5553801Z KeyedOptimizer or torch.distributed's NamedOptimizer. 2025-08-26T19:55:59.5554304Z load_directly (bool): If this is set to True, this API will also 2025-08-26T19:55:59.5554826Z call optim.load_state_dict(result) before returning the result. 2025-08-26T19:55:59.5555381Z Otherwise, users are responsible to call ``optim.load_state_dict()`` 2025-08-26T19:55:59.5555822Z (Default: ``False``) 2025-08-26T19:55:59.5556323Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T19:55:59.5556891Z are sharded or ``None`` if using the default process group. ( 2025-08-26T19:55:59.5557299Z Default: ``None``) 2025-08-26T19:55:59.5557472Z 2025-08-26T19:55:59.5557742Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.5558119Z 2025-08-26T19:55:59.6101445Z msg = Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=129. 2025-08-26T19:55:59.6102516Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.6102919Z 2025-08-26T19:55:59.6103150Z RemoteModule instance can only be created after RPC initialization. 2025-08-26T19:55:59.6103514Z 2025-08-26T19:55:59.6103713Z It creates a user-specified module on a specified remote node. 2025-08-26T19:55:59.6104272Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T19:55:59.6104860Z executed on the remote node. 2025-08-26T19:55:59.6105298Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T19:55:59.6105822Z gradients back to the corresponding remote module. 2025-08-26T19:55:59.6106465Z It can be shared across processors using `RPC framework `__, 2025-08-26T19:55:59.6107143Z without incurring any overheads of copying the actual module, 2025-08-26T19:55:59.6107656Z which is equivalent to an :class:`~torch.distributed.rpc.RRef` 2025-08-26T19:55:59.6108178Z pointing to the remote module. 2025-08-26T19:55:59.6108387Z 2025-08-26T19:55:59.6108642Z The arguments of ``forward_async`` and ``forward`` are the same as 2025-08-26T19:55:59.6109227Z the ``forward`` method of the module returned by the ``module_cls``. 2025-08-26T19:55:59.6109811Z 2025-08-26T19:55:59.6110385Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now. 2025-08-26T19:55:59.6110858Z 2025-08-26T19:55:59.6111117Z Particularly, to create a hybrid model, typically the local modules should be 2025-08-26T19:55:59.6111886Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``). 2025-08-26T19:55:59.6112539Z Hybrid Example: 2025-08-26T19:55:59.6112809Z >>> class HybridModel(nn.Module): 2025-08-26T19:55:59.6113167Z >>> def __init__(self) -> None: 2025-08-26T19:55:59.6113513Z >>> nn.Module.__init__(self) 2025-08-26T19:55:59.6113882Z >>> self.remote_embedding = RemoteModule(...) 2025-08-26T19:55:59.6114282Z >>> self.local_linear = nn.Linear(...) 2025-08-26T19:55:59.6114536Z 2025-08-26T19:55:59.6114740Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T19:55:59.6115326Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T19:55:59.6115930Z the generated ``RemoteModule`` will have 2 methods in signature of 2025-08-26T19:55:59.6116391Z ``def forward(input: Tensor) -> Tensor:`` and 2025-08-26T19:55:59.6116815Z ``def forward_async(input: Tensor) -> Future[Tensor]:``. 2025-08-26T19:55:59.6117106Z 2025-08-26T19:55:59.6117211Z .. note:: 2025-08-26T19:55:59.6117486Z If the remote module is placed on a cuda device, 2025-08-26T19:55:59.6118059Z any input CPU tensors will be automatically moved to the same cuda device, 2025-08-26T19:55:59.6119329Z and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend. 2025-08-26T19:55:59.6119872Z 2025-08-26T19:55:59.6119959Z Args: 2025-08-26T19:55:59.6120384Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T19:55:59.6121110Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T19:55:59.6121610Z formats: 2025-08-26T19:55:59.6121842Z 2025-08-26T19:55:59.6121989Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T19:55:59.6122409Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T19:55:59.6122677Z 2025-08-26T19:55:59.6122938Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T19:55:59.6123434Z module_cls (nn.Module): For example, 2025-08-26T19:55:59.6123763Z >>> class MyModule(nn.Module): 2025-08-26T19:55:59.6124086Z >>> def forward(input): 2025-08-26T19:55:59.6124397Z >>> return input + 1 2025-08-26T19:55:59.6124696Z >>> 2025-08-26T19:55:59.6124917Z >>> module_cls = MyModule 2025-08-26T19:55:59.6125322Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T19:55:59.6125858Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T19:55:59.6126472Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T19:55:59.6127120Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T19:55:59.6128345Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T19:55:59.6129020Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T19:55:59.6129382Z 2025-08-26T19:55:59.6129484Z Returns: 2025-08-26T19:55:59.6129866Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T19:55:59.6130469Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T19:55:59.6131195Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T19:55:59.6131755Z on the user-provided module on the remote side. 2025-08-26T19:55:59.6132014Z 2025-08-26T19:55:59.6132120Z Example:: 2025-08-26T19:55:59.6132395Z Run the following code in two different processes: 2025-08-26T19:55:59.6132678Z 2025-08-26T19:55:59.6132794Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:55:59.6133117Z >>> # On worker 0: 2025-08-26T19:55:59.6133375Z >>> import torch 2025-08-26T19:55:59.6133654Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.6134009Z >>> from torch import nn, Tensor 2025-08-26T19:55:59.6134451Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T19:55:59.6134891Z >>> 2025-08-26T19:55:59.6135149Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:55:59.6135535Z >>> remote_linear_module = RemoteModule( 2025-08-26T19:55:59.6135907Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T19:55:59.6136242Z >>> ) 2025-08-26T19:55:59.6136475Z >>> input = torch.randn(128, 20) 2025-08-26T19:55:59.6136835Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T19:55:59.6137214Z >>> ret = ret_fut.wait() 2025-08-26T19:55:59.6137676Z >>> rpc.shutdown() 2025-08-26T19:55:59.6137837Z 2025-08-26T19:55:59.6137947Z >>> # On worker 1: 2025-08-26T19:55:59.6138192Z >>> import torch 2025-08-26T19:55:59.6138483Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.6138812Z >>> 2025-08-26T19:55:59.6139081Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:55:59.6139426Z >>> rpc.shutdown() 2025-08-26T19:55:59.6139601Z 2025-08-26T19:55:59.6139858Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.6140251Z 2025-08-26T19:55:59.6140978Z msg = Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=506. 2025-08-26T19:55:59.6142079Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.6142464Z 2025-08-26T19:55:59.6142810Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef. 2025-08-26T19:55:59.6143266Z 2025-08-26T19:55:59.6143675Z This alternate initialization method can be particularly useful if we want to create multiple 2025-08-26T19:55:59.6144464Z RemoteModule instances that share the same underlying module and reduce memory consumption. 2025-08-26T19:55:59.6144924Z 2025-08-26T19:55:59.6145206Z Moreover, this also provides a workaround for passing script RemoteModule over RPC, 2025-08-26T19:55:59.6145801Z which is not supported. The recommended way is as follows: 2025-08-26T19:55:59.6146093Z 2025-08-26T19:55:59.6146228Z 1. the sender creates a RemoteModule; 2025-08-26T19:55:59.6146598Z 2. the sender sends its ``module_rref`` over RPC; 2025-08-26T19:55:59.6147210Z 3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``. 2025-08-26T19:55:59.6147687Z 2025-08-26T19:55:59.6147777Z Example:: 2025-08-26T19:55:59.6148066Z Run the following code in two different processes: 2025-08-26T19:55:59.6148336Z 2025-08-26T19:55:59.6148464Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:55:59.6148780Z >>> # On worker 0: 2025-08-26T19:55:59.6149091Z >>> import torch 2025-08-26T19:55:59.6149383Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.6149746Z >>> from torch import nn, Tensor 2025-08-26T19:55:59.6150173Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T19:55:59.6150611Z >>> 2025-08-26T19:55:59.6150883Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:55:59.6151253Z >>> remote_module = RemoteModule( 2025-08-26T19:55:59.6151596Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T19:55:59.6152013Z >>> ) 2025-08-26T19:55:59.6152225Z >>> 2025-08-26T19:55:59.6152460Z >>> remote_module1 = rpc.rpc_sync( 2025-08-26T19:55:59.6152771Z >>> "worker1/cpu", 2025-08-26T19:55:59.6153086Z >>> RemoteModule.init_from_module_rref, 2025-08-26T19:55:59.6153494Z >>> ("worker1/cpu", remote_module1.get_module_rref()), 2025-08-26T19:55:59.6153863Z >>> ) 2025-08-26T19:55:59.6154079Z >>> rpc.shutdown() 2025-08-26T19:55:59.6154254Z 2025-08-26T19:55:59.6154350Z >>> # On worker 1: 2025-08-26T19:55:59.6154603Z >>> import torch 2025-08-26T19:55:59.6154896Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.6155211Z >>> 2025-08-26T19:55:59.6155481Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:55:59.6155840Z >>> rpc.shutdown() 2025-08-26T19:55:59.6156000Z 2025-08-26T19:55:59.6156098Z Args: 2025-08-26T19:55:59.6156516Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T19:55:59.6157253Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T19:55:59.6157771Z formats: 2025-08-26T19:55:59.6157916Z 2025-08-26T19:55:59.6158074Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T19:55:59.6158483Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T19:55:59.6158766Z 2025-08-26T19:55:59.6159016Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T19:55:59.6159663Z module_rref (RRef[nn.Module]): The module reference shared by both the caller and 2025-08-26T19:55:59.6160163Z the created remote module. 2025-08-26T19:55:59.6160660Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T19:55:59.6161301Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T19:55:59.6161892Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T19:55:59.6162479Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T19:55:59.6162839Z 2025-08-26T19:55:59.6162938Z Returns: 2025-08-26T19:55:59.6163313Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T19:55:59.6163913Z user-provided ``module_rref``, it has a blocking ``forward`` method and an 2025-08-26T19:55:59.6164588Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T19:55:59.6165143Z on the user-provided module on the remote side. 2025-08-26T19:55:59.6165403Z 2025-08-26T19:55:59.6165671Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.6166045Z 2025-08-26T19:55:59.6166733Z msg = Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=598. 2025-08-26T19:55:59.6167749Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.6168133Z 2025-08-26T19:55:59.6168369Z A RemoteModule instance can only be created after RPC initialization. 2025-08-26T19:55:59.6168738Z 2025-08-26T19:55:59.6169030Z It creates a user-specified module on a specified remote node. 2025-08-26T19:55:59.6169595Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T19:55:59.6170071Z executed on the remote node. 2025-08-26T19:55:59.6170560Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T19:55:59.6171078Z gradients back to the corresponding remote module. 2025-08-26T19:55:59.6171366Z 2025-08-26T19:55:59.6171589Z It generates two methods ``forward_async`` and ``forward`` based on the 2025-08-26T19:55:59.6172156Z signature of the ``forward`` method of ``module_cls``. ``forward_async`` 2025-08-26T19:55:59.6172757Z runs asynchronously and returns a Future. The arguments of ``forward_async`` 2025-08-26T19:55:59.6173401Z and ``forward`` are the same as the ``forward`` method of the module 2025-08-26T19:55:59.6173828Z returned by the ``module_cls``. 2025-08-26T19:55:59.6174050Z 2025-08-26T19:55:59.6174254Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T19:55:59.6174840Z that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T19:55:59.6175463Z the generated ``RemoteModule`` will have 2 methods with the signatures: 2025-08-26T19:55:59.6175815Z 2025-08-26T19:55:59.6175957Z | ``def forward(input: Tensor) -> Tensor:`` 2025-08-26T19:55:59.6176361Z | ``def forward_async(input: Tensor) -> Future[Tensor]:`` 2025-08-26T19:55:59.6176658Z 2025-08-26T19:55:59.6176742Z Args: 2025-08-26T19:55:59.6177168Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T19:55:59.6177952Z The format should be "/", where the device field can be parsed as torch.device type. 2025-08-26T19:55:59.6178558Z E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0". 2025-08-26T19:55:59.6179068Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T19:55:59.6179705Z module_cls (nn.Module): Class for the module to be created remotely. For example, 2025-08-26T19:55:59.6180078Z 2025-08-26T19:55:59.6180206Z >>> class MyModule(nn.Module): 2025-08-26T19:55:59.6180535Z >>> def forward(input): 2025-08-26T19:55:59.6180833Z >>> return input + 1 2025-08-26T19:55:59.6181128Z >>> 2025-08-26T19:55:59.6181359Z >>> module_cls = MyModule 2025-08-26T19:55:59.6181553Z 2025-08-26T19:55:59.6181766Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T19:55:59.6182275Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T19:55:59.6182602Z 2025-08-26T19:55:59.6182687Z Returns: 2025-08-26T19:55:59.6183072Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T19:55:59.6183680Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T19:55:59.6184310Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T19:55:59.6184859Z on the user-provided module on the remote side. 2025-08-26T19:55:59.6185130Z 2025-08-26T19:55:59.6185277Z Example:: 2025-08-26T19:55:59.6185565Z Run the following code in two different processes: 2025-08-26T19:55:59.6185830Z 2025-08-26T19:55:59.6185959Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:55:59.6186270Z >>> # On worker 0: 2025-08-26T19:55:59.6186529Z >>> import torch 2025-08-26T19:55:59.6186815Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.6187164Z >>> from torch import nn, Tensor 2025-08-26T19:55:59.6187590Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T19:55:59.6188022Z >>> 2025-08-26T19:55:59.6188292Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:55:59.6188672Z >>> remote_linear_module = RemoteModule( 2025-08-26T19:55:59.6189025Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T19:55:59.6189356Z >>> ) 2025-08-26T19:55:59.6189589Z >>> input = torch.randn(128, 20) 2025-08-26T19:55:59.6189965Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T19:55:59.6190338Z >>> ret = ret_fut.wait() 2025-08-26T19:55:59.6190663Z >>> rpc.shutdown() 2025-08-26T19:55:59.6190838Z 2025-08-26T19:55:59.6190931Z >>> # On worker 1: 2025-08-26T19:55:59.6191186Z >>> import torch 2025-08-26T19:55:59.6191459Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.6191556Z >>> 2025-08-26T19:55:59.6191697Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:55:59.6191803Z >>> rpc.shutdown() 2025-08-26T19:55:59.6191807Z 2025-08-26T19:55:59.6192003Z Furthermore, a more practical example that is combined with 2025-08-26T19:55:59.6192568Z `DistributedDataParallel `__ (DDP) 2025-08-26T19:55:59.6192919Z can be found in this `tutorial `__. 2025-08-26T19:55:59.6192924Z 2025-08-26T19:55:59.6193182Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.6193189Z 2025-08-26T19:55:59.6356518Z msg = Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/optimizer.py line=129. 2025-08-26T19:55:59.6356793Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.6356797Z 2025-08-26T19:55:59.6357061Z DistributedOptimizer takes remote references to parameters scattered 2025-08-26T19:55:59.6357305Z across workers and applies the given optimizer locally for each parameter. 2025-08-26T19:55:59.6357332Z 2025-08-26T19:55:59.6357589Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order 2025-08-26T19:55:59.6357746Z to retrieve the gradients for specific parameters. 2025-08-26T19:55:59.6357751Z 2025-08-26T19:55:59.6357877Z Concurrent calls to 2025-08-26T19:55:59.6358086Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`, 2025-08-26T19:55:59.6358233Z either from the same or different clients, will 2025-08-26T19:55:59.6358482Z be serialized on each worker -- as each worker's optimizer can only work 2025-08-26T19:55:59.6358695Z on one set of gradients at a time. However, there is no guarantee that 2025-08-26T19:55:59.6358959Z the full forward-backward-optimizer sequence will execute for one client 2025-08-26T19:55:59.6359179Z at a time. This means that the gradients being applied may not correspond 2025-08-26T19:55:59.6359407Z to the latest forward pass executed on a given worker. Also, there is no 2025-08-26T19:55:59.6359537Z guaranteed ordering across workers. 2025-08-26T19:55:59.6359541Z 2025-08-26T19:55:59.6359814Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled 2025-08-26T19:55:59.6360061Z by default, so that optimizer updates are not blocked by the Python Global 2025-08-26T19:55:59.6360309Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed 2025-08-26T19:55:59.6360556Z Model Parallel). This feature is currently enabled for most optimizers. You 2025-08-26T19:55:59.6360960Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support 2025-08-26T19:55:59.6361074Z for your own custom optimizers. 2025-08-26T19:55:59.6361079Z 2025-08-26T19:55:59.6361179Z Args: 2025-08-26T19:55:59.6361381Z optimizer_class (optim.Optimizer): the class of optimizer to 2025-08-26T19:55:59.6361505Z instantiate on each worker. 2025-08-26T19:55:59.6361719Z params_rref (list[RRef]): list of RRefs to local or remote parameters 2025-08-26T19:55:59.6361812Z to optimize. 2025-08-26T19:55:59.6362052Z args: arguments to pass to the optimizer constructor on each worker. 2025-08-26T19:55:59.6362279Z kwargs: arguments to pass to the optimizer constructor on each worker. 2025-08-26T19:55:59.6362283Z 2025-08-26T19:55:59.6362402Z Example:: 2025-08-26T19:55:59.6362520Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:55:59.6362688Z >>> import torch.distributed.autograd as dist_autograd 2025-08-26T19:55:59.6362833Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.6362988Z >>> from torch import optim 2025-08-26T19:55:59.6363194Z >>> from torch.distributed.optim import DistributedOptimizer 2025-08-26T19:55:59.6363281Z >>> 2025-08-26T19:55:59.6363418Z >>> with dist_autograd.context() as context_id: 2025-08-26T19:55:59.6363529Z >>> # Forward pass. 2025-08-26T19:55:59.6363732Z >>> rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3)) 2025-08-26T19:55:59.6363930Z >>> rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1)) 2025-08-26T19:55:59.6364155Z >>> loss = rref1.to_here() + rref2.to_here() 2025-08-26T19:55:59.6364239Z >>> 2025-08-26T19:55:59.6364351Z >>> # Backward pass. 2025-08-26T19:55:59.6364505Z >>> dist_autograd.backward(context_id, [loss.sum()]) 2025-08-26T19:55:59.6364591Z >>> 2025-08-26T19:55:59.6364699Z >>> # Optimizer. 2025-08-26T19:55:59.6364826Z >>> dist_optim = DistributedOptimizer( 2025-08-26T19:55:59.6364934Z >>> optim.SGD, 2025-08-26T19:55:59.6365031Z >>> [rref1, rref2], 2025-08-26T19:55:59.6365122Z >>> lr=0.05, 2025-08-26T19:55:59.6365219Z >>> ) 2025-08-26T19:55:59.6365331Z >>> dist_optim.step(context_id) 2025-08-26T19:55:59.6365336Z 2025-08-26T19:55:59.6365506Z __ https://github.com/pytorch/tutorials/pull/1465 2025-08-26T19:55:59.6365510Z 2025-08-26T19:55:59.6365766Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.6365771Z 2025-08-26T19:55:59.6375935Z msg = Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9. 2025-08-26T19:55:59.6376208Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.6376212Z 2025-08-26T19:55:59.6376621Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD `_, 2025-08-26T19:55:59.6376779Z This optimizer runs local optimizer at every step. 2025-08-26T19:55:59.6377125Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied. 2025-08-26T19:55:59.6377130Z 2025-08-26T19:55:59.6377225Z Args: 2025-08-26T19:55:59.6377333Z optim: The local optimizer. 2025-08-26T19:55:59.6377568Z averager: A model averager instance to run post-localSGD algorithm. 2025-08-26T19:55:59.6377573Z 2025-08-26T19:55:59.6377666Z Example:: 2025-08-26T19:55:59.6377670Z 2025-08-26T19:55:59.6377798Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:55:59.6377899Z >>> import torch 2025-08-26T19:55:59.6378020Z >>> import torch.distributed as dist 2025-08-26T19:55:59.6378311Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T19:55:59.6378415Z >>> import torch.nn as nn 2025-08-26T19:55:59.6378613Z >>> from torch.distributed.optim import PostLocalSGDOptimizer 2025-08-26T19:55:59.6378907Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T19:55:59.6379061Z >>> PostLocalSGDState, 2025-08-26T19:55:59.6379174Z >>> post_localSGD_hook, 2025-08-26T19:55:59.6379257Z >>> ) 2025-08-26T19:55:59.6379342Z >>> 2025-08-26T19:55:59.6379515Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T19:55:59.6379673Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T19:55:59.6379771Z >>> ) 2025-08-26T19:55:59.6379854Z >>> 2025-08-26T19:55:59.6380001Z >>> # Register a post-localSGD communication hook. 2025-08-26T19:55:59.6380322Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T19:55:59.6380486Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:55:59.6380581Z >>> 2025-08-26T19:55:59.6380788Z >>> # Create a post-localSGD optimizer that wraps a local optimizer. 2025-08-26T19:55:59.6381043Z >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as 2025-08-26T19:55:59.6381257Z >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T19:55:59.6381473Z >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01) 2025-08-26T19:55:59.6381604Z >>> opt = PostLocalSGDOptimizer( 2025-08-26T19:55:59.6381705Z >>> optim=local_optim, 2025-08-26T19:55:59.6381957Z >>> averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T19:55:59.6382053Z >>> ) 2025-08-26T19:55:59.6382137Z >>> 2025-08-26T19:55:59.6382440Z >>> # In the first 100 steps, DDP runs global gradient averaging at every step. 2025-08-26T19:55:59.6382748Z >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default), 2025-08-26T19:55:59.6383134Z >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer. 2025-08-26T19:55:59.6383254Z >>> for step in range(0, 200): 2025-08-26T19:55:59.6383353Z >>> opt.zero_grad() 2025-08-26T19:55:59.6383478Z >>> loss = loss_fn(output, labels) 2025-08-26T19:55:59.6383581Z >>> loss.backward() 2025-08-26T19:55:59.6383673Z >>> opt.step() 2025-08-26T19:55:59.6383677Z 2025-08-26T19:55:59.6383956Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.6383961Z 2025-08-26T19:55:59.6500284Z msg = Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284. 2025-08-26T19:55:59.6500600Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.6500605Z 2025-08-26T19:55:59.6501025Z Wrap an arbitrary :class:`optim.Optimizer ` and shards its states across ranks in the group. 2025-08-26T19:55:59.6501030Z 2025-08-26T19:55:59.6501284Z The sharing is done as described by `ZeRO `_. 2025-08-26T19:55:59.6501291Z 2025-08-26T19:55:59.6501438Z The local optimizer instance in each rank is only 2025-08-26T19:55:59.6501698Z responsible for updating approximately ``1 / world_size`` parameters and 2025-08-26T19:55:59.6501901Z hence only needs to keep ``1 / world_size`` optimizer states. After 2025-08-26T19:55:59.6502158Z parameters are updated locally, each rank will broadcast its parameters to 2025-08-26T19:55:59.6502342Z all other peers to keep all model replicas in the same state. 2025-08-26T19:55:59.6502536Z ``ZeroRedundancyOptimizer`` can be used in conjunction with 2025-08-26T19:55:59.6502809Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak 2025-08-26T19:55:59.6502904Z memory consumption. 2025-08-26T19:55:59.6502909Z 2025-08-26T19:55:59.6503308Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number 2025-08-26T19:55:59.6503542Z of parameters at each rank. Each parameter belongs to a single rank and is 2025-08-26T19:55:59.6503797Z not divided among ranks. The partition is arbitrary and might not match the 2025-08-26T19:55:59.6504085Z the parameter registration or usage order. 2025-08-26T19:55:59.6504090Z 2025-08-26T19:55:59.6504178Z Arguments: 2025-08-26T19:55:59.6504391Z params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s 2025-08-26T19:55:59.6504581Z or :class:`dict` s giving all parameters, which will be sharded 2025-08-26T19:55:59.6504688Z across ranks. 2025-08-26T19:55:59.6504692Z 2025-08-26T19:55:59.6504783Z Keyword Args: 2025-08-26T19:55:59.6505008Z optimizer_class (:class:`torch.nn.Optimizer`): the class of the local 2025-08-26T19:55:59.6505117Z optimizer. 2025-08-26T19:55:59.6505332Z process_group (``ProcessGroup``, optional): ``torch.distributed`` 2025-08-26T19:55:59.6505550Z ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by 2025-08-26T19:55:59.6505700Z :meth:`torch.distributed.init_process_group`). 2025-08-26T19:55:59.6505932Z parameters_as_bucket_view (bool, optional): if ``True``, parameters are 2025-08-26T19:55:59.6506160Z packed into buckets to speed up communication, and ``param.data`` 2025-08-26T19:55:59.6506453Z fields point to bucket views at different offsets; if ``False``, 2025-08-26T19:55:59.6506675Z each individual parameter is communicated separately, and each 2025-08-26T19:55:59.6506828Z ``params.data`` stays intact (default: ``False``). 2025-08-26T19:55:59.6507023Z overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is 2025-08-26T19:55:59.6507241Z overlapped with :class:`DistributedDataParallel` 's gradient 2025-08-26T19:55:59.6507554Z synchronization; this requires (1) either a functional optimizer 2025-08-26T19:55:59.6507751Z for the ``optimizer_class`` argument or one with a functional 2025-08-26T19:55:59.6507929Z equivalent and (2) registering a DDP communication hook 2025-08-26T19:55:59.6508134Z constructed from one of the functions in ``ddp_zero_hook.py``; 2025-08-26T19:55:59.6508321Z parameters are packed into buckets matching those in 2025-08-26T19:55:59.6508480Z :class:`DistributedDataParallel`, meaning that the 2025-08-26T19:55:59.6508646Z ``parameters_as_bucket_view`` argument is ignored. 2025-08-26T19:55:59.6508836Z If ``False``, :meth:`step` runs disjointly after the backward pass 2025-08-26T19:55:59.6508927Z (per normal). 2025-08-26T19:55:59.6509040Z (default: ``False``) 2025-08-26T19:55:59.6509252Z **defaults: any trailing arguments, which are forwarded to the local 2025-08-26T19:55:59.6509355Z optimizer. 2025-08-26T19:55:59.6509360Z 2025-08-26T19:55:59.6509462Z Example:: 2025-08-26T19:55:59.6509467Z 2025-08-26T19:55:59.6509577Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.6509679Z >>> import torch.nn as nn 2025-08-26T19:55:59.6509884Z >>> from torch.distributed.optim import ZeroRedundancyOptimizer 2025-08-26T19:55:59.6510100Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T19:55:59.6510332Z >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)]) 2025-08-26T19:55:59.6510465Z >>> ddp = DDP(model, device_ids=[rank]) 2025-08-26T19:55:59.6510583Z >>> opt = ZeroRedundancyOptimizer( 2025-08-26T19:55:59.6510687Z >>> ddp.parameters(), 2025-08-26T19:55:59.6510822Z >>> optimizer_class=torch.optim.Adam, 2025-08-26T19:55:59.6510909Z >>> lr=0.01 2025-08-26T19:55:59.6510993Z >>> ) 2025-08-26T19:55:59.6511113Z >>> ddp(inputs).sum().backward() 2025-08-26T19:55:59.6511202Z >>> opt.step() 2025-08-26T19:55:59.6511206Z 2025-08-26T19:55:59.6511310Z .. warning:: 2025-08-26T19:55:59.6511524Z Currently, ``ZeroRedundancyOptimizer`` requires that all of the 2025-08-26T19:55:59.6511671Z passed-in parameters are the same dense type. 2025-08-26T19:55:59.6511695Z 2025-08-26T19:55:59.6511783Z .. warning:: 2025-08-26T19:55:59.6511999Z If you pass ``overlap_with_ddp=True``, be wary of the following: Given 2025-08-26T19:55:59.6512254Z the way that overlapping :class:`DistributedDataParallel` with 2025-08-26T19:55:59.6512494Z :class:`ZeroRedundancyOptimizer` is currently implemented, the first 2025-08-26T19:55:59.6512713Z two or three training iterations do not perform parameter updates in 2025-08-26T19:55:59.6512922Z the optimizer step, depending on if ``static_graph=False`` or 2025-08-26T19:55:59.6513108Z ``static_graph=True``, respectively. This is because it needs 2025-08-26T19:55:59.6513308Z information about the gradient bucketing strategy used by 2025-08-26T19:55:59.6513536Z :class:`DistributedDataParallel`, which is not finalized until the 2025-08-26T19:55:59.6513750Z second forward pass if ``static_graph=False`` or until the third 2025-08-26T19:55:59.6513964Z forward pass if ``static_graph=True``. To adjust for this, one option 2025-08-26T19:55:59.6514072Z is to prepend dummy inputs. 2025-08-26T19:55:59.6514076Z 2025-08-26T19:55:59.6514351Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change. 2025-08-26T19:55:59.6514387Z 2025-08-26T19:55:59.6514645Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.6514650Z 2025-08-26T19:55:59.6757008Z msg = Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py line=29. 2025-08-26T19:55:59.6758055Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.6758442Z 2025-08-26T19:55:59.6758678Z Custom reducer class that can be used to specify a custom operation that 2025-08-26T19:55:59.6759334Z reduces losses of multiple microbatches into one value. 2025-08-26T19:55:59.6759640Z 2025-08-26T19:55:59.6759729Z Example: 2025-08-26T19:55:59.6759960Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.6760227Z >>> sum_reducer = _CustomReducer( 2025-08-26T19:55:59.6760543Z >>> torch.tensor(0.0), 2025-08-26T19:55:59.6760829Z >>> lambda a, b: a + b 2025-08-26T19:55:59.6761097Z >>> ) 2025-08-26T19:55:59.6761213Z 2025-08-26T19:55:59.6761489Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.6761865Z 2025-08-26T19:55:59.7335663Z msg = Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/functions.py line=6. 2025-08-26T19:55:59.7336792Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.7337180Z 2025-08-26T19:55:59.7337596Z A decorator for a function indicating that the return value of the function 2025-08-26T19:55:59.7338181Z is guaranteed to be a :class:`~torch.futures.Future` object and this 2025-08-26T19:55:59.7338767Z function can run asynchronously on the RPC callee. More specifically, the 2025-08-26T19:55:59.7339385Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped 2025-08-26T19:55:59.7339997Z function and installs subsequent processing steps as a callback to that 2025-08-26T19:55:59.7340596Z :class:`~torch.futures.Future`. The installed callback will read the value 2025-08-26T19:55:59.7341173Z from the :class:`~torch.futures.Future` when completed and send the 2025-08-26T19:55:59.7341687Z value back as the RPC response. That also means the returned 2025-08-26T19:55:59.7342230Z :class:`~torch.futures.Future` only exists on the callee side and is never 2025-08-26T19:55:59.7342827Z sent through RPC. This decorator is useful when the wrapped function's 2025-08-26T19:55:59.7343366Z (``fn``) execution needs to pause and resume due to, e.g., containing 2025-08-26T19:55:59.7343926Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals. 2025-08-26T19:55:59.7344285Z 2025-08-26T19:55:59.7344517Z .. note:: To enable asynchronous execution, applications must pass the 2025-08-26T19:55:59.7345091Z function object returned by this decorator to RPC APIs. If RPC detected 2025-08-26T19:55:59.7345676Z attributes installed by this decorator, it knows that this function 2025-08-26T19:55:59.7346303Z returns a ``Future`` object and will handle that accordingly. 2025-08-26T19:55:59.7346831Z However, this does not mean this decorator has to be outmost one when 2025-08-26T19:55:59.7347405Z defining a function. For example, when combined with ``@staticmethod`` 2025-08-26T19:55:59.7347977Z or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the 2025-08-26T19:55:59.7348530Z inner decorator to allow the target function be recognized as a static 2025-08-26T19:55:59.7349118Z or class function. This target function can still execute asynchronously 2025-08-26T19:55:59.7349720Z because, when accessed, the static or class method preserves attributes 2025-08-26T19:55:59.7350239Z installed by ``@rpc.functions.async_execution``. 2025-08-26T19:55:59.7350507Z 2025-08-26T19:55:59.7350511Z 2025-08-26T19:55:59.7350615Z Example:: 2025-08-26T19:55:59.7350943Z The returned :class:`~torch.futures.Future` object can come from 2025-08-26T19:55:59.7351409Z :meth:`~torch.distributed.rpc.rpc_async`, 2025-08-26T19:55:59.7351950Z :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future` 2025-08-26T19:55:59.7352484Z constructor. The example below shows directly using the 2025-08-26T19:55:59.7352908Z :class:`~torch.futures.Future` returned by 2025-08-26T19:55:59.7353278Z :meth:`~torch.futures.Future.then`. 2025-08-26T19:55:59.7353516Z 2025-08-26T19:55:59.7353637Z >>> from torch.distributed import rpc 2025-08-26T19:55:59.7353958Z >>> 2025-08-26T19:55:59.7354183Z >>> # omitting setup and shutdown RPC 2025-08-26T19:55:59.7354501Z >>> 2025-08-26T19:55:59.7354800Z >>> # On all workers 2025-08-26T19:55:59.7355093Z >>> @rpc.functions.async_execution 2025-08-26T19:55:59.7355423Z >>> def async_add_chained(to, x, y, z): 2025-08-26T19:55:59.7355854Z >>> # This function runs on "worker1" and returns immediately when 2025-08-26T19:55:59.7356370Z >>> # the callback is installed through the `then(cb)` API. In the 2025-08-26T19:55:59.7356884Z >>> # mean time, the `rpc_async` to "worker2" can run concurrently. 2025-08-26T19:55:59.7357367Z >>> # When the return value of that `rpc_async` arrives at 2025-08-26T19:55:59.7357829Z >>> # "worker1", "worker1" will run the lambda function accordingly 2025-08-26T19:55:59.7358334Z >>> # and set the value for the previously returned `Future`, which 2025-08-26T19:55:59.7358835Z >>> # will then trigger RPC to send the result back to "worker0". 2025-08-26T19:55:59.7359318Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:55:59.7359714Z >>> lambda fut: fut.wait() + z 2025-08-26T19:55:59.7360026Z >>> ) 2025-08-26T19:55:59.7360243Z >>> 2025-08-26T19:55:59.7360453Z >>> # On worker0 2025-08-26T19:55:59.7360695Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.7360971Z >>> ret = rpc.rpc_sync( 2025-08-26T19:55:59.7361247Z >>> "worker1", 2025-08-26T19:55:59.7361508Z >>> async_add_chained, 2025-08-26T19:55:59.7361809Z >>> args=("worker2", torch.ones(2), 1, 1) 2025-08-26T19:55:59.7362135Z >>> ) 2025-08-26T19:55:59.7362382Z >>> print(ret) # prints tensor([3., 3.]) 2025-08-26T19:55:59.7362611Z 2025-08-26T19:55:59.7362853Z When combined with TorchScript decorators, this decorator must be the 2025-08-26T19:55:59.7363282Z outmost one. 2025-08-26T19:55:59.7363433Z 2025-08-26T19:55:59.7363538Z >>> from torch import Tensor 2025-08-26T19:55:59.7363854Z >>> from torch.futures import Future 2025-08-26T19:55:59.7364202Z >>> from torch.distributed import rpc 2025-08-26T19:55:59.7364511Z >>> 2025-08-26T19:55:59.7364746Z >>> # omitting setup and shutdown RPC 2025-08-26T19:55:59.7365060Z >>> 2025-08-26T19:55:59.7365271Z >>> # On all workers 2025-08-26T19:55:59.7365528Z >>> @torch.jit.script 2025-08-26T19:55:59.7365853Z >>> def script_add(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T19:55:59.7366211Z >>> return x + y 2025-08-26T19:55:59.7366540Z >>> 2025-08-26T19:55:59.7366772Z >>> @rpc.functions.async_execution 2025-08-26T19:55:59.7367099Z >>> @torch.jit.script 2025-08-26T19:55:59.7367470Z >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]: 2025-08-26T19:55:59.7367928Z >>> return rpc.rpc_async(to, script_add, (x, y)) 2025-08-26T19:55:59.7368262Z >>> 2025-08-26T19:55:59.7368470Z >>> # On worker0 2025-08-26T19:55:59.7368725Z >>> ret = rpc.rpc_sync( 2025-08-26T19:55:59.7369092Z >>> "worker1", 2025-08-26T19:55:59.7369331Z >>> async_add, 2025-08-26T19:55:59.7369616Z >>> args=("worker2", torch.ones(2), 1) 2025-08-26T19:55:59.7369947Z >>> ) 2025-08-26T19:55:59.7370209Z >>> print(ret) # prints tensor([2., 2.]) 2025-08-26T19:55:59.7370437Z 2025-08-26T19:55:59.7370657Z When combined with static or class method, this decorator must be the 2025-08-26T19:55:59.7371099Z inner one. 2025-08-26T19:55:59.7371247Z 2025-08-26T19:55:59.7371368Z >>> from torch.distributed import rpc 2025-08-26T19:55:59.7371735Z >>> 2025-08-26T19:55:59.7371962Z >>> # omitting setup and shutdown RPC 2025-08-26T19:55:59.7372281Z >>> 2025-08-26T19:55:59.7372499Z >>> # On all workers 2025-08-26T19:55:59.7372789Z >>> class AsyncExecutionClass: 2025-08-26T19:55:59.7373078Z >>> 2025-08-26T19:55:59.7373303Z >>> @staticmethod 2025-08-26T19:55:59.7373599Z >>> @rpc.functions.async_execution 2025-08-26T19:55:59.7373954Z >>> def static_async_add(to, x, y, z): 2025-08-26T19:55:59.7374359Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:55:59.7374836Z >>> lambda fut: fut.wait() + z 2025-08-26T19:55:59.7375159Z >>> ) 2025-08-26T19:55:59.7375396Z >>> 2025-08-26T19:55:59.7375600Z >>> @classmethod 2025-08-26T19:55:59.7375896Z >>> @rpc.functions.async_execution 2025-08-26T19:55:59.7376258Z >>> def class_async_add(cls, to, x, y, z): 2025-08-26T19:55:59.7376637Z >>> ret_fut = torch.futures.Future() 2025-08-26T19:55:59.7377037Z >>> rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:55:59.7377449Z >>> lambda fut: ret_fut.set_result(fut.wait() + z) 2025-08-26T19:55:59.7377807Z >>> ) 2025-08-26T19:55:59.7378052Z >>> return ret_fut 2025-08-26T19:55:59.7378324Z >>> 2025-08-26T19:55:59.7378550Z >>> @rpc.functions.async_execution 2025-08-26T19:55:59.7378910Z >>> def bound_async_add(self, to, x, y, z): 2025-08-26T19:55:59.7379331Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:55:59.7379740Z >>> lambda fut: fut.wait() + z 2025-08-26T19:55:59.7380045Z >>> ) 2025-08-26T19:55:59.7380275Z >>> 2025-08-26T19:55:59.7380487Z >>> # On worker0 2025-08-26T19:55:59.7380743Z >>> ret = rpc.rpc_sync( 2025-08-26T19:55:59.7381004Z >>> "worker1", 2025-08-26T19:55:59.7381302Z >>> AsyncExecutionClass.static_async_add, 2025-08-26T19:55:59.7381682Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T19:55:59.7382008Z >>> ) 2025-08-26T19:55:59.7382241Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:55:59.7382564Z >>> 2025-08-26T19:55:59.7382782Z >>> ret = rpc.rpc_sync( 2025-08-26T19:55:59.7383057Z >>> "worker1", 2025-08-26T19:55:59.7383340Z >>> AsyncExecutionClass.class_async_add, 2025-08-26T19:55:59.7383707Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T19:55:59.7384031Z >>> ) 2025-08-26T19:55:59.7384274Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:55:59.7384508Z 2025-08-26T19:55:59.7384673Z This decorator also works with RRef helpers, i.e., . 2025-08-26T19:55:59.7385101Z :meth:`torch.distributed.rpc.RRef.rpc_sync`, 2025-08-26T19:55:59.7385524Z :meth:`torch.distributed.rpc.RRef.rpc_async`, and 2025-08-26T19:55:59.7385941Z :meth:`torch.distributed.rpc.RRef.remote`. 2025-08-26T19:55:59.7386197Z 2025-08-26T19:55:59.7386358Z >>> from torch.distributed import rpc 2025-08-26T19:55:59.7386687Z >>> 2025-08-26T19:55:59.7386955Z >>> # reuse the AsyncExecutionClass class above 2025-08-26T19:55:59.7387375Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T19:55:59.7387853Z >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2) 2025-08-26T19:55:59.7388318Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:55:59.7388637Z >>> 2025-08-26T19:55:59.7388913Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T19:55:59.7389414Z >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait() 2025-08-26T19:55:59.7389899Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:55:59.7390218Z >>> 2025-08-26T19:55:59.7390497Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T19:55:59.7391007Z >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here() 2025-08-26T19:55:59.7391485Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:55:59.7391769Z 2025-08-26T19:55:59.7392026Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.7392417Z 2025-08-26T19:55:59.7393173Z msg = Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/options.py line=113. 2025-08-26T19:55:59.7394275Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.7394663Z 2025-08-26T19:55:59.7394967Z Set device mapping between each RPC caller and callee pair. This 2025-08-26T19:55:59.7395483Z function can be called multiple times to incrementally add 2025-08-26T19:55:59.7395892Z device placement configurations. 2025-08-26T19:55:59.7396110Z 2025-08-26T19:55:59.7396193Z Args: 2025-08-26T19:55:59.7396414Z to (str): Callee name. 2025-08-26T19:55:59.7396795Z device_map (Dict of int, str, or torch.device): Device placement 2025-08-26T19:55:59.7397291Z mappings from this worker to the callee. This map must be 2025-08-26T19:55:59.7397686Z invertible. 2025-08-26T19:55:59.7397844Z 2025-08-26T19:55:59.7397929Z Example: 2025-08-26T19:55:59.7398171Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:55:59.7398481Z >>> # both workers 2025-08-26T19:55:59.7398734Z >>> def add(x, y): 2025-08-26T19:55:59.7399037Z >>> print(x) # tensor([1., 1.], device='cuda:1') 2025-08-26T19:55:59.7399407Z >>> return x + y, (x + y).to(2) 2025-08-26T19:55:59.7399699Z >>> 2025-08-26T19:55:59.7399921Z >>> # on worker 0 2025-08-26T19:55:59.7400227Z >>> options = TensorPipeRpcBackendOptions( 2025-08-26T19:55:59.7400587Z >>> num_worker_threads=8, 2025-08-26T19:55:59.7400887Z >>> device_maps={"worker1": {0: 1}} 2025-08-26T19:55:59.7401249Z >>> # maps worker0's cuda:0 to worker1's cuda:1 2025-08-26T19:55:59.7412289Z >>> ) 2025-08-26T19:55:59.7412582Z >>> options.set_device_map("worker1", {1: 2}) 2025-08-26T19:55:59.7412998Z >>> # maps worker0's cuda:1 to worker1's cuda:2 2025-08-26T19:55:59.7413352Z >>> 2025-08-26T19:55:59.7413578Z >>> rpc.init_rpc( 2025-08-26T19:55:59.7413827Z >>> "worker0", 2025-08-26T19:55:59.7414080Z >>> rank=0, 2025-08-26T19:55:59.7414325Z >>> world_size=2, 2025-08-26T19:55:59.7414634Z >>> backend=rpc.BackendType.TENSORPIPE, 2025-08-26T19:55:59.7414986Z >>> rpc_backend_options=options 2025-08-26T19:55:59.7415299Z >>> ) 2025-08-26T19:55:59.7415510Z >>> 2025-08-26T19:55:59.7415734Z >>> x = torch.ones(2) 2025-08-26T19:55:59.7416068Z >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) 2025-08-26T19:55:59.7416543Z >>> # The first argument will be moved to cuda:1 on worker1. When 2025-08-26T19:55:59.7417049Z >>> # sending the return value back, it will follow the invert of 2025-08-26T19:55:59.7417538Z >>> # the device map, and hence will be moved back to cuda:0 and 2025-08-26T19:55:59.7418030Z >>> # cuda:1 on worker0 2025-08-26T19:55:59.7418355Z >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') 2025-08-26T19:55:59.7418778Z >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') 2025-08-26T19:55:59.7419042Z 2025-08-26T19:55:59.7419318Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.7419720Z 2025-08-26T19:55:59.7420635Z msg = Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19. 2025-08-26T19:55:59.7421792Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.7422180Z 2025-08-26T19:55:59.7422394Z It has the same API as ``torch.autograd.profiler.profile`` class, 2025-08-26T19:55:59.7422986Z except that it enables profiling on all threads running RPC server request callbacks. 2025-08-26T19:55:59.7423403Z 2025-08-26T19:55:59.7423689Z Context manager that manages autograd profiler state and holds a summary of results. 2025-08-26T19:55:59.7424395Z Under the hood it just records events of functions being executed in C++ and 2025-08-26T19:55:59.7424997Z exposes those events to Python. You can wrap any code into it and it will 2025-08-26T19:55:59.7425487Z only report runtime of PyTorch functions. 2025-08-26T19:55:59.7425987Z Note: profiler is thread local and is automatically propagated into the async tasks 2025-08-26T19:55:59.7426394Z 2025-08-26T19:55:59.7426477Z Args: 2025-08-26T19:55:59.7426933Z enabled (bool, optional): Setting this to False makes this context manager a no-op. 2025-08-26T19:55:59.7427439Z Default: ``True``. 2025-08-26T19:55:59.7427613Z 2025-08-26T19:55:59.7427904Z use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API. 2025-08-26T19:55:59.7428528Z Adds approximately 4us of overhead to each tensor operation. 2025-08-26T19:55:59.7428948Z Default: ``False`` 2025-08-26T19:55:59.7429122Z 2025-08-26T19:55:59.7429368Z record_shapes (bool, optional): If shapes recording is set, information 2025-08-26T19:55:59.7429965Z about input dimensions will be collected. This allows one to see which 2025-08-26T19:55:59.7430530Z dimensions have been used under the hood and further group by them 2025-08-26T19:55:59.7431097Z using prof.key_averages(group_by_input_shape=True). Please note that 2025-08-26T19:55:59.7431681Z shape recording might skew your profiling data. It is recommended to 2025-08-26T19:55:59.7432283Z use separate runs with and without shape recording to validate the timing. 2025-08-26T19:55:59.7432884Z Most likely the skew will be negligible for bottom most events (in a case 2025-08-26T19:55:59.7433451Z of nested function calls). But for higher level functions the total 2025-08-26T19:55:59.7434001Z self cpu time might be artificially increased because of the shape 2025-08-26T19:55:59.7434430Z collection. 2025-08-26T19:55:59.7434580Z 2025-08-26T19:55:59.7434870Z profile_memory (bool, optional): Whether to report memory usage, default: ``False`` 2025-08-26T19:55:59.7435268Z 2025-08-26T19:55:59.7435375Z .. warning:: 2025-08-26T19:55:59.7435717Z Enabling memory profiling incurs additional profiler overhead 2025-08-26T19:55:59.7436053Z 2025-08-26T19:55:59.7436142Z .. warning:: 2025-08-26T19:55:59.7436572Z Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`), 2025-08-26T19:55:59.7437195Z one cannot use the profiler with ``use_cuda = True`` to benchmark 2025-08-26T19:55:59.7437917Z DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading, 2025-08-26T19:55:59.7438454Z please use ``use_cuda = False`` or ``num_workers = 0``. 2025-08-26T19:55:59.7438750Z 2025-08-26T19:55:59.7438838Z Example: 2025-08-26T19:55:59.7439069Z >>> # xdoctest: +SKIP 2025-08-26T19:55:59.7439326Z >>> # On worker 0: 2025-08-26T19:55:59.7439581Z >>> import torch 2025-08-26T19:55:59.7439973Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.7440364Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:55:59.7440737Z >>> x, y = torch.tensor(1), torch.tensor(2) 2025-08-26T19:55:59.7441100Z >>> outer_profile_rref = rpc.remote( 2025-08-26T19:55:59.7441497Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T19:55:59.7441873Z ... ) 2025-08-26T19:55:59.7442117Z >>> outer_profile_rref.rpc_sync().__enter__() 2025-08-26T19:55:59.7442518Z >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y)) 2025-08-26T19:55:59.7442909Z >>> inner_profile_rref = rpc.remote( 2025-08-26T19:55:59.7443297Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T19:55:59.7443655Z ... ) 2025-08-26T19:55:59.7443910Z >>> inner_profile_rref.rpc_sync().__enter__() 2025-08-26T19:55:59.7444308Z >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y)) 2025-08-26T19:55:59.7444752Z >>> inner_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T19:55:59.7445279Z >>> outer_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T19:55:59.7445728Z >>> print(inner_profile_rref.rpc_sync().key_averages()) 2025-08-26T19:55:59.7446251Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:55:59.7446936Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T19:55:59.7447693Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:55:59.7448241Z sub 85.06% 76.275us 100.00% 89.667us 89.667us 1 2025-08-26T19:55:59.7448753Z empty 14.94% 13.392us 14.94% 13.392us 13.392us 1 2025-08-26T19:55:59.7449389Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:55:59.7449869Z Self CPU time total: 89.667us 2025-08-26T19:55:59.7450242Z >>> print(outer_profile_rref.rpc_sync().key_averages()) 2025-08-26T19:55:59.7450743Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:55:59.7451414Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T19:55:59.7452078Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:55:59.7452617Z sub 35.65% 76.275us 41.91% 89.667us 89.667us 1 2025-08-26T19:55:59.7453121Z empty 12.67% 27.101us 12.67% 27.101us 13.551us 2 2025-08-26T19:55:59.7453615Z add 51.68% 110.550us 58.09% 124.259us 124.259us 1 2025-08-26T19:55:59.7454167Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:55:59.7454643Z Self CPU time total: 213.926us 2025-08-26T19:55:59.7454956Z >>> rpc.shutdown() 2025-08-26T19:55:59.7455117Z 2025-08-26T19:55:59.7455220Z >>> # On worker 1: 2025-08-26T19:55:59.7455496Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:55:59.7455881Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:55:59.7456301Z >>> # wait for worker 0 to finish work, and then shutdown. 2025-08-26T19:55:59.7456681Z >>> rpc.shutdown() 2025-08-26T19:55:59.7456841Z 2025-08-26T19:55:59.7457098Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.7457487Z 2025-08-26T19:55:59.8754745Z msg = Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35. 2025-08-26T19:55:59.8755950Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.8756355Z 2025-08-26T19:55:59.8756627Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s 2025-08-26T19:55:59.8757307Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting 2025-08-26T19:55:59.8757989Z the local components of :class:`DTensor`, call the function, and wrap the outputs to 2025-08-26T19:55:59.8758537Z :class:`DTensor` according to the ``out_placements``. 2025-08-26T19:55:59.8758817Z 2025-08-26T19:55:59.8758900Z Args: 2025-08-26T19:55:59.8759241Z func (Callable): the function to be applied on each local shard of 2025-08-26T19:55:59.8759670Z :class:`DTensor` s. 2025-08-26T19:55:59.8760076Z out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]): 2025-08-26T19:55:59.8760691Z the desired placements of the :class:`DTensor` s in ``func``'s flattened output. 2025-08-26T19:55:59.8761328Z If the flattened ``output`` is a single value, the ``out_placements`` should be 2025-08-26T19:55:59.8762006Z of type `PlacementType`. Otherwise if the flattened ``output`` has multiple 2025-08-26T19:55:59.8762632Z values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1 2025-08-26T19:55:59.8763124Z mapping to the flattened ``output``. 2025-08-26T19:55:59.8763571Z Besides, for :class:`Tensor` output, we use `PlacementType` as its 2025-08-26T19:55:59.8764187Z placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType` 2025-08-26T19:55:59.8764782Z should be `None`. 2025-08-26T19:55:59.8765191Z Note that the only exception is when no :class:`DTensor` argument is passed 2025-08-26T19:55:59.8765789Z in. In this case, even if `out_placements` is not `None`, the result function 2025-08-26T19:55:59.8766403Z should ignore the desired placements because the function is not running with 2025-08-26T19:55:59.8766898Z :class:`DTensor` s. 2025-08-26T19:55:59.8767283Z in_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T19:55:59.8767857Z the required placements of the :class:`DTensor` s in the flattened inputs of ``func``. 2025-08-26T19:55:59.8768500Z If ``in_placements`` is specified, :meth:`local_map` would examine whether the 2025-08-26T19:55:59.8769181Z placements of each :class:`DTensor` argument is the same as the required 2025-08-26T19:55:59.8769728Z placements or not. If the placements are not the same and 2025-08-26T19:55:59.8770288Z ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if 2025-08-26T19:55:59.8770913Z ``redistribute_inputs`` is ``True``, the argument will be first redistributed to 2025-08-26T19:55:59.8771545Z the required sharding placements before passing its local tensor to ``func``. 2025-08-26T19:55:59.8772168Z The only exception is when required placements are not ``None`` and the 2025-08-26T19:55:59.8772771Z argument is a :class:`torch.Tensor`. In this case, the placements examination 2025-08-26T19:55:59.8773373Z will be skipped and the argument will be directly passed to ``func``. 2025-08-26T19:55:59.8773934Z If ``in_placements`` is ``None``, no placements examination will be performed. 2025-08-26T19:55:59.8774388Z Default: None 2025-08-26T19:55:59.8774736Z in_grad_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T19:55:59.8775260Z the placements hint of the :class:`DTensor` s gradient corresponds 2025-08-26T19:55:59.8775820Z to the flattened input DTensor. This argument is the hint that user 2025-08-26T19:55:59.8776337Z can give to :meth:`to_local` in case the gradient layout of the 2025-08-26T19:55:59.8776868Z local tensor input does not match its :class:`DTensor` input layout. 2025-08-26T19:55:59.8777422Z If not specified, we will assume the gradient layout of the local 2025-08-26T19:55:59.8778017Z tensor input remains the same as the original :class:`DTensor` input 2025-08-26T19:55:59.8778526Z and use that for gradient computation. Default: None. 2025-08-26T19:55:59.8778957Z device_mesh (:class:`DeviceMesh`, optional): 2025-08-26T19:55:59.8779443Z the device mesh that the output :class:`DTensor` s are placed on. If not 2025-08-26T19:55:59.8780055Z specified, this will be inferred from the first input :class:`DTensor`'s device 2025-08-26T19:55:59.8780551Z mesh. Default: None. 2025-08-26T19:55:59.8780734Z 2025-08-26T19:55:59.8780826Z Keyword Args: 2025-08-26T19:55:59.8781094Z redistribute_inputs (bool, optional): 2025-08-26T19:55:59.8781594Z the bool value indicating whether to reshard the input :class:`DTensor` s when 2025-08-26T19:55:59.8782238Z their placements are different from the required input placements. If this 2025-08-26T19:55:59.8782838Z value is ``False`` and some :class:`DTensor` input has a different placement, 2025-08-26T19:55:59.8783345Z an exception will be raised. Default: False. 2025-08-26T19:55:59.8783648Z 2025-08-26T19:55:59.8783734Z Returns: 2025-08-26T19:55:59.8784126Z A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor` 2025-08-26T19:55:59.8784761Z and returns a :class:`DTensor` constructed from the return value of ``func``. 2025-08-26T19:55:59.8785125Z 2025-08-26T19:55:59.8785211Z Raises: 2025-08-26T19:55:59.8785585Z AssertionError: For any non-DTensor output, we require its corresponding 2025-08-26T19:55:59.8786298Z output placement in ``out_placements`` be None. An AssertionError will be raised 2025-08-26T19:55:59.8786797Z if this is not the case. 2025-08-26T19:55:59.8786992Z 2025-08-26T19:55:59.8787258Z ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs 2025-08-26T19:55:59.8787810Z a redistribution according to ``in_placements``. 2025-08-26T19:55:59.8788086Z 2025-08-26T19:55:59.8788173Z Example: 2025-08-26T19:55:59.8788413Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:55:59.8788788Z >>> def mm_allreduce_forward(device_mesh, W, X): 2025-08-26T19:55:59.8789160Z >>> partial_sum_tensor = torch.mm(W, X) 2025-08-26T19:55:59.8789647Z >>> reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh) 2025-08-26T19:55:59.8790124Z >>> return reduced_tensor 2025-08-26T19:55:59.8790412Z >>> 2025-08-26T19:55:59.8790651Z >>> W = torch.randn(12, 8, requires_grad=False) 2025-08-26T19:55:59.8791031Z >>> X = torch.randn(8, 16, requires_grad=False) 2025-08-26T19:55:59.8791382Z >>> Y = torch.mm(W, X) 2025-08-26T19:55:59.8791754Z >>> row_wise = [Shard(0)] # row-wise sharding placements on 1-d mesh 2025-08-26T19:55:59.8792247Z >>> col_wise = [Shard(1)] # col-wise sharding placements on 1-d mesh 2025-08-26T19:55:59.8792649Z >>> 2025-08-26T19:55:59.8793046Z >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor conversion 2025-08-26T19:55:59.8793582Z >>> local_mm_allreduce_forward = local_map( 2025-08-26T19:55:59.8793923Z >>> mm_allreduce_forward, 2025-08-26T19:55:59.8794245Z >>> out_placements=[Replicate()], 2025-08-26T19:55:59.8794597Z >>> in_placements=[col_wise, row_wise], 2025-08-26T19:55:59.8794940Z >>> device_mesh=device_mesh, 2025-08-26T19:55:59.8795226Z >>> ) 2025-08-26T19:55:59.8795438Z >>> 2025-08-26T19:55:59.8795665Z >>> W_dt = distribute_tensor( 2025-08-26T19:55:59.8795979Z ... W, device_mesh, (col_wise) 2025-08-26T19:55:59.8796300Z ... ) # col-wisely sharded W tensor 2025-08-26T19:55:59.8796627Z >>> X_dt = distribute_tensor( 2025-08-26T19:55:59.8796936Z ... X, device_mesh, (row_wise) 2025-08-26T19:55:59.8797262Z ... ) # row-wisely sharded X tensor 2025-08-26T19:55:59.8797588Z >>> Y_dt = local_mm_allreduce_forward( 2025-08-26T19:55:59.8797920Z ... device_mesh, W_dt, X_dt 2025-08-26T19:55:59.8798316Z ... ) # apply local_mm_allreduce_forward to DTensors 2025-08-26T19:55:59.8798579Z 2025-08-26T19:55:59.8798809Z .. note:: This API is currently experimental and subject to change 2025-08-26T19:55:59.8799120Z 2025-08-26T19:55:59.8799390Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.8799762Z 2025-08-26T19:55:59.8800533Z msg = Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25. 2025-08-26T19:55:59.8801646Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.8802044Z 2025-08-26T19:55:59.8802327Z :meth:`register_sharding` is an experimental API that allows users to register sharding 2025-08-26T19:55:59.8802995Z strategies for an operator when the tensor inputs and outputs are DTensor. 2025-08-26T19:55:59.8803620Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``, 2025-08-26T19:55:59.8804253Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2) 2025-08-26T19:55:59.8804921Z when users would like to overwrite default sharding strategies of existing operators. 2025-08-26T19:55:59.8805333Z 2025-08-26T19:55:59.8805415Z Args: 2025-08-26T19:55:59.8805665Z op (Union[OpOverload, List[OpOverload]]): 2025-08-26T19:55:59.8806110Z An op or a list of ops to register the customized sharding function. 2025-08-26T19:55:59.8806424Z 2025-08-26T19:55:59.8806508Z Returns: 2025-08-26T19:55:59.8806966Z A function decorator which can be used to wrap a function that defines the sharding 2025-08-26T19:55:59.8807646Z strategy for the operator specified in ``op``. The defined sharding strategy will be 2025-08-26T19:55:59.8808333Z registered to DTensor and will override the default sharding strategy if DTensor has 2025-08-26T19:55:59.8809141Z already implemented the operator. The customized sharding function takes the same inputs 2025-08-26T19:55:59.8809819Z as the original op (except that if an arg is a :class:`torch.Tensor`, it will be 2025-08-26T19:55:59.8810474Z replaced by a tensor-like object that DTensor uses internally). The function should 2025-08-26T19:55:59.8811156Z return a sequence of 2-tuples, each specifying acceptable output placements and its 2025-08-26T19:55:59.8811681Z corresponding input placements. 2025-08-26T19:55:59.8811898Z 2025-08-26T19:55:59.8811998Z Example: 2025-08-26T19:55:59.8812228Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:55:59.8812594Z >>> @register_sharding(aten._softmax.default) 2025-08-26T19:55:59.8813013Z >>> def custom_softmax_sharding(x, dim, half_to_float): 2025-08-26T19:55:59.8813441Z >>> softmax_dim = dim if dim >= 0 else dim + x.ndim 2025-08-26T19:55:59.8813809Z >>> acceptable_shardings = [] 2025-08-26T19:55:59.8814113Z >>> 2025-08-26T19:55:59.8814417Z >>> all_replicate = ([Replicate()], [Replicate(), None, None]) 2025-08-26T19:55:59.8814870Z >>> acceptable_shardings.append(all_replicate) 2025-08-26T19:55:59.8815206Z >>> 2025-08-26T19:55:59.8815446Z >>> for sharding_dim in range(x.ndim): 2025-08-26T19:55:59.8815800Z >>> if sharding_dim != softmax_dim: 2025-08-26T19:55:59.8816136Z >>> all_sharded = ( 2025-08-26T19:55:59.8816447Z >>> [Shard(sharding_dim)], 2025-08-26T19:55:59.8816805Z >>> [Shard(sharding_dim), None, None], 2025-08-26T19:55:59.8817140Z >>> ) 2025-08-26T19:55:59.8817444Z >>> acceptable_shardings.append(all_sharded) 2025-08-26T19:55:59.8817782Z >>> 2025-08-26T19:55:59.8818016Z >>> return acceptable_shardings 2025-08-26T19:55:59.8818249Z 2025-08-26T19:55:59.8818451Z .. note:: This API is currently experimental and subject to change 2025-08-26T19:55:59.8818764Z 2025-08-26T19:55:59.8819030Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.8819446Z 2025-08-26T19:55:59.9033954Z msg = Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=428. 2025-08-26T19:55:59.9035032Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.9035418Z 2025-08-26T19:55:59.9035807Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to 2025-08-26T19:55:59.9036657Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``. 2025-08-26T19:55:59.9037123Z 2025-08-26T19:55:59.9037220Z Keyword Args: 2025-08-26T19:55:59.9037707Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:55:59.9038377Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T19:55:59.9039195Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T19:55:59.9039921Z as a placeholder. default: None. 2025-08-26T19:55:59.9040394Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:55:59.9041149Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:55:59.9042069Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T19:55:59.9042720Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T19:55:59.9043450Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T19:55:59.9044055Z default: None 2025-08-26T19:55:59.9044386Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T19:55:59.9045048Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:55:59.9045698Z have the desired DTensor layouts. default: None. 2025-08-26T19:55:59.9046086Z use_local_output (bool, optional): 2025-08-26T19:55:59.9046683Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T19:55:59.9047264Z Returns: 2025-08-26T19:55:59.9047705Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs. 2025-08-26T19:55:59.9048160Z 2025-08-26T19:55:59.9048255Z Example:: 2025-08-26T19:55:59.9048492Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:55:59.9049093Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput 2025-08-26T19:55:59.9049732Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T19:55:59.9050140Z >>> ... 2025-08-26T19:55:59.9050591Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T19:55:59.9051164Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T19:55:59.9051499Z >>> 2025-08-26T19:55:59.9051955Z >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor 2025-08-26T19:55:59.9052572Z >>> # and then redistributed to Replicated DTensor. 2025-08-26T19:55:59.9052975Z >>> parallelize_module( 2025-08-26T19:55:59.9053298Z >>> block, # this can be a submodule or module 2025-08-26T19:55:59.9053639Z >>> tp_mesh, 2025-08-26T19:55:59.9053891Z >>> parallelize_plan={ 2025-08-26T19:55:59.9054216Z >>> "attn": PrepareModuleInput( 2025-08-26T19:55:59.9054589Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T19:55:59.9055021Z >>> desired_input_layouts=(Replicate(), None, None, ...) 2025-08-26T19:55:59.9055393Z >>> ), 2025-08-26T19:55:59.9055626Z >>> } 2025-08-26T19:55:59.9055853Z >>> ) 2025-08-26T19:55:59.9055973Z 2025-08-26T19:55:59.9056308Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.9056689Z 2025-08-26T19:55:59.9057386Z msg = Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=597. 2025-08-26T19:55:59.9058440Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.9058843Z 2025-08-26T19:55:59.9059247Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to 2025-08-26T19:55:59.9060123Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``. 2025-08-26T19:55:59.9060587Z 2025-08-26T19:55:59.9060692Z Keyword Args: 2025-08-26T19:55:59.9061004Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:55:59.9061622Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T19:55:59.9062485Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T19:55:59.9063179Z ``None`` need to be specified as a placeholder. 2025-08-26T19:55:59.9063649Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:55:59.9064368Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T19:55:59.9064996Z have the desired DTensor layouts. 2025-08-26T19:55:59.9065352Z use_local_output (bool, optional): 2025-08-26T19:55:59.9065999Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T19:55:59.9066581Z Returns: 2025-08-26T19:55:59.9066998Z A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs. 2025-08-26T19:55:59.9067427Z 2025-08-26T19:55:59.9067516Z Example:: 2025-08-26T19:55:59.9067761Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:55:59.9068299Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput 2025-08-26T19:55:59.9068936Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T19:55:59.9069333Z >>> ... 2025-08-26T19:55:59.9069772Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T19:55:59.9070336Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T19:55:59.9070670Z >>> 2025-08-26T19:55:59.9071197Z >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor 2025-08-26T19:55:59.9071873Z >>> # and then redistributed to Sharded DTensor. 2025-08-26T19:55:59.9072234Z >>> parallelize_module( 2025-08-26T19:55:59.9072565Z >>> block, # this can be a submodule or module 2025-08-26T19:55:59.9072896Z >>> tp_mesh, 2025-08-26T19:55:59.9073194Z >>> parallelize_plan = PrepareModuleOutput( 2025-08-26T19:55:59.9073576Z >>> output_layouts=Replicate(), 2025-08-26T19:55:59.9073931Z >>> desired_output_layouts=Shard(0) 2025-08-26T19:55:59.9074244Z >>> ) 2025-08-26T19:55:59.9074465Z >>> ) 2025-08-26T19:55:59.9074597Z 2025-08-26T19:55:59.9074852Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.9075227Z 2025-08-26T19:55:59.9075949Z msg = Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=705. 2025-08-26T19:55:59.9077044Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.9077434Z 2025-08-26T19:55:59.9077877Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module 2025-08-26T19:55:59.9078876Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution 2025-08-26T19:55:59.9079849Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of 2025-08-26T19:55:59.9080578Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`. 2025-08-26T19:55:59.9080901Z 2025-08-26T19:55:59.9081005Z Keyword Args: 2025-08-26T19:55:59.9081341Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:55:59.9082005Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T19:55:59.9082846Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T19:55:59.9083457Z as a placeholder. default: None. 2025-08-26T19:55:59.9083925Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:55:59.9084664Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:55:59.9085167Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T19:55:59.9085304Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T19:55:59.9085699Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T19:55:59.9085792Z default: None 2025-08-26T19:55:59.9085956Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T19:55:59.9086401Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:55:59.9086555Z have the desired DTensor layouts. default: None. 2025-08-26T19:55:59.9086683Z use_local_input (bool, optional): 2025-08-26T19:55:59.9087048Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T19:55:59.9087217Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:55:59.9087575Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T19:55:59.9087962Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T19:55:59.9088119Z ``None`` need to be specified as a placeholder. 2025-08-26T19:55:59.9088317Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:55:59.9088730Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T19:55:59.9088923Z have the desired DTensor layouts. 2025-08-26T19:55:59.9089040Z use_local_output (bool, optional): 2025-08-26T19:55:59.9089419Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T19:55:59.9089506Z Returns: 2025-08-26T19:55:59.9089895Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs. 2025-08-26T19:55:59.9089902Z 2025-08-26T19:55:59.9089994Z Example:: 2025-08-26T19:55:59.9090102Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:55:59.9090462Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput 2025-08-26T19:55:59.9090660Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T19:55:59.9090756Z >>> ... 2025-08-26T19:55:59.9091068Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T19:55:59.9091196Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T19:55:59.9091292Z >>> 2025-08-26T19:55:59.9091630Z >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor 2025-08-26T19:55:59.9092005Z >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated 2025-08-26T19:55:59.9092261Z >>> # as Replicated DTensor and then redistributed to Sharded DTensor. 2025-08-26T19:55:59.9092364Z >>> parallelize_module( 2025-08-26T19:55:59.9092512Z >>> block, # this can be a submodule or module 2025-08-26T19:55:59.9092600Z >>> tp_mesh, 2025-08-26T19:55:59.9092715Z >>> parallelize_plan={ 2025-08-26T19:55:59.9092848Z >>> "attn": PrepareModuleInputOutput( 2025-08-26T19:55:59.9092986Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T19:55:59.9093174Z >>> desired_input_layouts=(Replicate(), None, None, ...), 2025-08-26T19:55:59.9093295Z >>> output_layouts=Replicate(), 2025-08-26T19:55:59.9093435Z >>> desired_output_layouts=Shard(0), 2025-08-26T19:55:59.9093519Z >>> ), 2025-08-26T19:55:59.9093603Z >>> } 2025-08-26T19:55:59.9093703Z >>> ) 2025-08-26T19:55:59.9093708Z 2025-08-26T19:55:59.9093970Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.9094002Z 2025-08-26T19:55:59.9788772Z msg = Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56. 2025-08-26T19:55:59.9789059Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.9789064Z 2025-08-26T19:55:59.9789389Z Creates a multivariate normal distribution with covariance matrix having a low-rank form 2025-08-26T19:55:59.9789721Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`:: 2025-08-26T19:55:59.9789727Z 2025-08-26T19:55:59.9789924Z covariance_matrix = cov_factor @ cov_factor.T + cov_diag 2025-08-26T19:55:59.9789929Z 2025-08-26T19:55:59.9790016Z Example: 2025-08-26T19:55:59.9790163Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T19:55:59.9790319Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:55:59.9790442Z >>> m = LowRankMultivariateNormal( 2025-08-26T19:55:59.9790641Z ... torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2) 2025-08-26T19:55:59.9790727Z ... ) 2025-08-26T19:55:59.9791021Z >>> m.sample() # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]` 2025-08-26T19:55:59.9791140Z tensor([-0.2102, -0.5429]) 2025-08-26T19:55:59.9791144Z 2025-08-26T19:55:59.9791227Z Args: 2025-08-26T19:55:59.9791478Z loc (Tensor): mean of the distribution with shape `batch_shape + event_shape` 2025-08-26T19:55:59.9791744Z cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape 2025-08-26T19:55:59.9791868Z `batch_shape + event_shape + (rank,)` 2025-08-26T19:55:59.9792142Z cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape 2025-08-26T19:55:59.9792248Z `batch_shape + event_shape` 2025-08-26T19:55:59.9792252Z 2025-08-26T19:55:59.9792347Z Note: 2025-08-26T19:55:59.9792623Z The computation for determinant and inverse of covariance matrix is avoided when 2025-08-26T19:55:59.9792881Z `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity 2025-08-26T19:55:59.9793101Z `_ and 2025-08-26T19:55:59.9793397Z `matrix determinant lemma `_. 2025-08-26T19:55:59.9793665Z Thanks to these formulas, we just need to compute the determinant and inverse of 2025-08-26T19:55:59.9793788Z the small size "capacitance" matrix:: 2025-08-26T19:55:59.9793792Z 2025-08-26T19:55:59.9793996Z capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor 2025-08-26T19:55:59.9794001Z 2025-08-26T19:55:59.9794256Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.9794260Z 2025-08-26T19:55:59.9814162Z msg = Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/mixture_same_family.py line=15. 2025-08-26T19:55:59.9814490Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.9814494Z 2025-08-26T19:55:59.9814725Z The `MixtureSameFamily` distribution implements a (batch of) mixture 2025-08-26T19:55:59.9814989Z distribution where all component are from different parameterizations of 2025-08-26T19:55:59.9815229Z the same distribution type. It is parameterized by a `Categorical` 2025-08-26T19:55:59.9815447Z "selecting distribution" (over `k` component) and a component 2025-08-26T19:55:59.9815661Z distribution, i.e., a `Distribution` with a rightmost batch shape 2025-08-26T19:55:59.9815849Z (equal to `[k]`) which indexes each (batch of) component. 2025-08-26T19:55:59.9815854Z 2025-08-26T19:55:59.9815948Z Examples:: 2025-08-26T19:55:59.9815952Z 2025-08-26T19:55:59.9816084Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:55:59.9816290Z >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally 2025-08-26T19:55:59.9816406Z >>> # weighted normal distributions 2025-08-26T19:55:59.9816583Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T19:55:59.9816731Z >>> comp = D.Normal(torch.randn(5,), torch.rand(5,)) 2025-08-26T19:55:59.9816864Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T19:55:59.9816869Z 2025-08-26T19:55:59.9817073Z >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally 2025-08-26T19:55:59.9817206Z >>> # weighted bivariate normal distributions 2025-08-26T19:55:59.9817338Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T19:55:59.9817503Z >>> comp = D.Independent(D.Normal( 2025-08-26T19:55:59.9817648Z ... torch.randn(5,2), torch.rand(5,2)), 1) 2025-08-26T19:55:59.9817770Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T19:55:59.9817774Z 2025-08-26T19:55:59.9817960Z >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each 2025-08-26T19:55:59.9818185Z >>> # consisting of 5 random weighted bivariate normal distributions 2025-08-26T19:55:59.9818312Z >>> mix = D.Categorical(torch.rand(3,5)) 2025-08-26T19:55:59.9818440Z >>> comp = D.Independent(D.Normal( 2025-08-26T19:55:59.9818575Z ... torch.randn(3,5,2), torch.rand(3,5,2)), 1) 2025-08-26T19:55:59.9818697Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T19:55:59.9818702Z 2025-08-26T19:55:59.9818802Z Args: 2025-08-26T19:55:59.9819012Z mixture_distribution: `torch.distributions.Categorical`-like 2025-08-26T19:55:59.9819217Z instance. Manages the probability of selecting component. 2025-08-26T19:55:59.9819392Z The number of categories must match the rightmost batch 2025-08-26T19:55:59.9819584Z dimension of the `component_distribution`. Must have either 2025-08-26T19:55:59.9819745Z scalar `batch_shape` or `batch_shape` matching 2025-08-26T19:55:59.9819885Z `component_distribution.batch_shape[:-1]` 2025-08-26T19:55:59.9820121Z component_distribution: `torch.distributions.Distribution`-like 2025-08-26T19:55:59.9820304Z instance. Right-most batch dimension indexes component. 2025-08-26T19:55:59.9820311Z 2025-08-26T19:55:59.9820580Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.9820585Z 2025-08-26T19:55:59.9976894Z msg = Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_bernoulli.py line=120. 2025-08-26T19:55:59.9977196Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.9977202Z 2025-08-26T19:55:59.9977395Z Creates a RelaxedBernoulli distribution, parametrized by 2025-08-26T19:55:59.9977589Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits` 2025-08-26T19:55:59.9977824Z (but not both). This is a relaxed version of the `Bernoulli` distribution, 2025-08-26T19:55:59.9978010Z so the values are in (0, 1), and has reparametrizable samples. 2025-08-26T19:55:59.9978015Z 2025-08-26T19:55:59.9978190Z Example:: 2025-08-26T19:55:59.9978195Z 2025-08-26T19:55:59.9978345Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:55:59.9978478Z >>> m = RelaxedBernoulli(torch.tensor([2.2]), 2025-08-26T19:55:59.9978620Z ... torch.tensor([0.1, 0.2, 0.3, 0.99])) 2025-08-26T19:55:59.9978710Z >>> m.sample() 2025-08-26T19:55:59.9978841Z tensor([ 0.2951, 0.3442, 0.8918, 0.9021]) 2025-08-26T19:55:59.9978845Z 2025-08-26T19:55:59.9978926Z Args: 2025-08-26T19:55:59.9979065Z temperature (Tensor): relaxation temperature 2025-08-26T19:55:59.9979254Z probs (Number, Tensor): the probability of sampling `1` 2025-08-26T19:55:59.9979420Z logits (Number, Tensor): the log-odds of sampling `1` 2025-08-26T19:55:59.9979424Z 2025-08-26T19:55:59.9979692Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:55:59.9979696Z 2025-08-26T19:55:59.9997663Z msg = Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_categorical.py line=109. 2025-08-26T19:55:59.9997995Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:55:59.9998000Z 2025-08-26T19:55:59.9998220Z Creates a RelaxedOneHotCategorical distribution parametrized by 2025-08-26T19:55:59.9998432Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`. 2025-08-26T19:55:59.9998674Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so 2025-08-26T19:55:59.9998842Z its samples are on simplex, and are reparametrizable. 2025-08-26T19:55:59.9998847Z 2025-08-26T19:55:59.9999017Z Example:: 2025-08-26T19:55:59.9999023Z 2025-08-26T19:55:59.9999164Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:55:59.9999334Z >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]), 2025-08-26T19:55:59.9999464Z ... torch.tensor([0.1, 0.2, 0.3, 0.4])) 2025-08-26T19:55:59.9999554Z >>> m.sample() 2025-08-26T19:55:59.9999685Z tensor([ 0.1294, 0.2324, 0.3859, 0.2523]) 2025-08-26T19:55:59.9999697Z 2025-08-26T19:55:59.9999780Z Args: 2025-08-26T19:55:59.9999933Z temperature (Tensor): relaxation temperature 2025-08-26T19:56:00.0000053Z probs (Tensor): event probabilities 2025-08-26T19:56:00.0000242Z logits (Tensor): unnormalized log probability for each event 2025-08-26T19:56:00.0000261Z 2025-08-26T19:56:00.0000515Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.0000520Z 2025-08-26T19:56:00.4201381Z msg = Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=245. 2025-08-26T19:56:00.4202545Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.4203157Z Return a new dict with new, potentially nested, key value pair 2025-08-26T19:56:00.4203466Z 2025-08-26T19:56:00.4203598Z >>> purchase = { 2025-08-26T19:56:00.4204092Z ... "name": "Alice", 2025-08-26T19:56:00.4204623Z ... "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T19:56:00.4205112Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T19:56:00.4205453Z ... } 2025-08-26T19:56:00.4206063Z >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00]) # doctest: +SKIP 2025-08-26T19:56:00.4206694Z {'credit card': '5555-1234-1234-1234', 2025-08-26T19:56:00.4207013Z 'name': 'Alice', 2025-08-26T19:56:00.4207346Z 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} 2025-08-26T19:56:00.4207742Z 2025-08-26T19:56:00.4208173Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.4208551Z 2025-08-26T19:56:00.4209838Z msg = Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=261. 2025-08-26T19:56:00.4210901Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.4211660Z Update value in a (potentially) nested dictionary 2025-08-26T19:56:00.4211926Z 2025-08-26T19:56:00.4212030Z inputs: 2025-08-26T19:56:00.4212272Z d - dictionary on which to operate 2025-08-26T19:56:00.4212732Z keys - list or tuple giving the location of the value to be changed in d 2025-08-26T19:56:00.4213207Z func - function to operate on that value 2025-08-26T19:56:00.4213443Z 2025-08-26T19:56:00.4213650Z If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the 2025-08-26T19:56:00.4214206Z original dictionary with v replaced by func(v), but does not mutate the 2025-08-26T19:56:00.4214670Z original dictionary. 2025-08-26T19:56:00.4214856Z 2025-08-26T19:56:00.4215069Z If k0 is not a key in d, update_in creates nested dictionaries to the depth 2025-08-26T19:56:00.4215624Z specified by the keys, with the innermost value set to func(default). 2025-08-26T19:56:00.4215966Z 2025-08-26T19:56:00.4216079Z >>> inc = lambda x: x + 1 2025-08-26T19:56:00.4216442Z >>> update_in({"a": 0}, ["a"], inc) 2025-08-26T19:56:00.4216750Z {'a': 1} 2025-08-26T19:56:00.4216879Z 2025-08-26T19:56:00.4216988Z >>> transaction = { 2025-08-26T19:56:00.4217256Z ... "name": "Alice", 2025-08-26T19:56:00.4217623Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T19:56:00.4218060Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T19:56:00.4218380Z ... } 2025-08-26T19:56:00.4218819Z >>> update_in(transaction, ["purchase", "costs"], sum) # doctest: +SKIP 2025-08-26T19:56:00.4219261Z {'credit card': '5555-1234-1234-1234', 2025-08-26T19:56:00.4219576Z 'name': 'Alice', 2025-08-26T19:56:00.4219910Z 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} 2025-08-26T19:56:00.4220194Z 2025-08-26T19:56:00.4220328Z >>> # updating a value when k0 is not in d 2025-08-26T19:56:00.4220689Z >>> update_in({}, [1, 2, 3], str, default="bar") 2025-08-26T19:56:00.4221034Z {1: {2: {3: 'bar'}}} 2025-08-26T19:56:00.4221321Z >>> update_in({1: "foo"}, [2, 3, 4], inc, 0) 2025-08-26T19:56:00.4221654Z {1: 'foo', 2: {3: {4: 1}}} 2025-08-26T19:56:00.4221913Z 2025-08-26T19:56:00.4222294Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.4222682Z 2025-08-26T19:56:00.4223339Z msg = Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=320. 2025-08-26T19:56:00.4224381Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.4224942Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. 2025-08-26T19:56:00.4225222Z 2025-08-26T19:56:00.4225407Z If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless 2025-08-26T19:56:00.4225919Z ``no_default`` is specified, then it raises KeyError or IndexError. 2025-08-26T19:56:00.4226258Z 2025-08-26T19:56:00.4226470Z ``get_in`` is a generalization of ``operator.getitem`` for nested data 2025-08-26T19:56:00.4226942Z structures such as dictionaries and lists. 2025-08-26T19:56:00.4227185Z 2025-08-26T19:56:00.4227293Z >>> transaction = { 2025-08-26T19:56:00.4227547Z ... "name": "Alice", 2025-08-26T19:56:00.4227921Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T19:56:00.4228359Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T19:56:00.4228685Z ... } 2025-08-26T19:56:00.4228945Z >>> get_in(["purchase", "items", 0], transaction) 2025-08-26T19:56:00.4229297Z 'Apple' 2025-08-26T19:56:00.4229544Z >>> get_in(["name"], transaction) 2025-08-26T19:56:00.4229854Z 'Alice' 2025-08-26T19:56:00.4230106Z >>> get_in(["purchase", "total"], transaction) 2025-08-26T19:56:00.4230511Z >>> get_in(["purchase", "items", "apple"], transaction) 2025-08-26T19:56:00.4230925Z >>> get_in(["purchase", "items", 10], transaction) 2025-08-26T19:56:00.4231369Z >>> get_in(["purchase", "total"], transaction, 0) 2025-08-26T19:56:00.4231703Z 0 2025-08-26T19:56:00.4231940Z >>> get_in(["y"], {}, no_default=True) 2025-08-26T19:56:00.4232287Z Traceback (most recent call last): 2025-08-26T19:56:00.4232604Z ... 2025-08-26T19:56:00.4232815Z KeyError: 'y' 2025-08-26T19:56:00.4232975Z 2025-08-26T19:56:00.4233062Z See Also: 2025-08-26T19:56:00.4233293Z itertoolz.get 2025-08-26T19:56:00.4233556Z operator.getitem 2025-08-26T19:56:00.4233807Z 2025-08-26T19:56:00.4234190Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.4234579Z 2025-08-26T19:56:00.4235250Z msg = Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=373. 2025-08-26T19:56:00.4236303Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.4236812Z Group a collection by a key function 2025-08-26T19:56:00.4237065Z 2025-08-26T19:56:00.4237232Z >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"] 2025-08-26T19:56:00.4237863Z >>> groupby(len, names) # doctest: +SKIP 2025-08-26T19:56:00.4238291Z {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} 2025-08-26T19:56:00.4238570Z 2025-08-26T19:56:00.4238694Z >>> iseven = lambda x: x % 2 == 0 2025-08-26T19:56:00.4239084Z >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP 2025-08-26T19:56:00.4239586Z {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} 2025-08-26T19:56:00.4239824Z 2025-08-26T19:56:00.4239969Z Non-callable keys imply grouping on a member. 2025-08-26T19:56:00.4240238Z 2025-08-26T19:56:00.4240330Z >>> groupby( 2025-08-26T19:56:00.4240565Z ... "gender", 2025-08-26T19:56:00.4240795Z ... [ 2025-08-26T19:56:00.4241052Z ... {"name": "Alice", "gender": "F"}, 2025-08-26T19:56:00.4241413Z ... {"name": "Bob", "gender": "M"}, 2025-08-26T19:56:00.4241775Z ... {"name": "Charlie", "gender": "M"}, 2025-08-26T19:56:00.4242092Z ... ], 2025-08-26T19:56:00.4242330Z ... ) # doctest:+SKIP 2025-08-26T19:56:00.4242630Z {'F': [{'gender': 'F', 'name': 'Alice'}], 2025-08-26T19:56:00.4242970Z 'M': [{'gender': 'M', 'name': 'Bob'}, 2025-08-26T19:56:00.4243305Z {'gender': 'M', 'name': 'Charlie'}]} 2025-08-26T19:56:00.4243532Z 2025-08-26T19:56:00.4243673Z Not to be confused with ``itertools.groupby`` 2025-08-26T19:56:00.4243939Z 2025-08-26T19:56:00.4244025Z See Also: 2025-08-26T19:56:00.4244250Z countby 2025-08-26T19:56:00.4244472Z 2025-08-26T19:56:00.4244835Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.4245227Z 2025-08-26T19:56:00.7342792Z msg = Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py line=142. 2025-08-26T19:56:00.7343715Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.7344366Z Return the recommended gain value for the given nonlinearity function. 2025-08-26T19:56:00.7344720Z 2025-08-26T19:56:00.7344863Z The values are as follows: 2025-08-26T19:56:00.7345060Z 2025-08-26T19:56:00.7345179Z ================= ==================================================== 2025-08-26T19:56:00.7345532Z nonlinearity gain 2025-08-26T19:56:00.7345835Z ================= ==================================================== 2025-08-26T19:56:00.7346199Z Linear / Identity :math:`1` 2025-08-26T19:56:00.7346483Z Conv{1,2,3}D :math:`1` 2025-08-26T19:56:00.7346769Z Sigmoid :math:`1` 2025-08-26T19:56:00.7347067Z Tanh :math:`\frac{5}{3}` 2025-08-26T19:56:00.7347395Z ReLU :math:`\sqrt{2}` 2025-08-26T19:56:00.7347794Z Leaky Relu :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}` 2025-08-26T19:56:00.7348388Z SELU :math:`\frac{3}{4}` 2025-08-26T19:56:00.7348737Z ================= ==================================================== 2025-08-26T19:56:00.7348977Z 2025-08-26T19:56:00.7349104Z .. warning:: 2025-08-26T19:56:00.7349436Z In order to implement `Self-Normalizing Neural Networks`_ , 2025-08-26T19:56:00.7349997Z you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``. 2025-08-26T19:56:00.7350554Z This gives the initial weights a variance of ``1 / N``, 2025-08-26T19:56:00.7351081Z which is necessary to induce a stable fixed point in the forward pass. 2025-08-26T19:56:00.7351662Z In contrast, the default gain for ``SELU`` sacrifices the normalization 2025-08-26T19:56:00.7352197Z effect for more stable gradient flow in rectangular layers. 2025-08-26T19:56:00.7352515Z 2025-08-26T19:56:00.7352601Z Args: 2025-08-26T19:56:00.7352933Z nonlinearity: the non-linear function (`nn.functional` name) 2025-08-26T19:56:00.7353439Z param: optional parameter for the non-linear function 2025-08-26T19:56:00.7353786Z 2025-08-26T19:56:00.7353876Z Examples: 2025-08-26T19:56:00.7354134Z >>> gain = nn.init.calculate_gain( 2025-08-26T19:56:00.7354473Z ... "leaky_relu", 0.2 2025-08-26T19:56:00.7354802Z ... ) # leaky_relu with negative_slope=0.2 2025-08-26T19:56:00.7355045Z 2025-08-26T19:56:00.7355561Z .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html 2025-08-26T19:56:00.7356242Z 2025-08-26T19:56:00.7356728Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.7357123Z 2025-08-26T19:56:00.7978930Z msg = Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=603. 2025-08-26T19:56:00.7979970Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.7980556Z Applies Batch Normalization over a N-Dimensional input. 2025-08-26T19:56:00.7980858Z 2025-08-26T19:56:00.7981210Z The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper 2025-08-26T19:56:00.7981948Z `Batch Normalization: Accelerating Deep Network Training by Reducing 2025-08-26T19:56:00.7982534Z Internal Covariate Shift `__ . 2025-08-26T19:56:00.7982882Z 2025-08-26T19:56:00.7982990Z .. math:: 2025-08-26T19:56:00.7983123Z 2025-08-26T19:56:00.7983365Z y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta 2025-08-26T19:56:00.7983707Z 2025-08-26T19:56:00.7983957Z The mean and standard-deviation are calculated per-dimension over all 2025-08-26T19:56:00.7984544Z mini-batches of the same process groups. :math:`\gamma` and :math:`\beta` 2025-08-26T19:56:00.7985174Z are learnable parameter vectors of size `C` (where `C` is the input size). 2025-08-26T19:56:00.7985740Z By default, the elements of :math:`\gamma` are sampled from 2025-08-26T19:56:00.7986255Z :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0. 2025-08-26T19:56:00.7986853Z The standard-deviation is calculated via the biased estimator, equivalent to 2025-08-26T19:56:00.7987353Z `torch.var(input, unbiased=False)`. 2025-08-26T19:56:00.7987593Z 2025-08-26T19:56:00.7987835Z Also by default, during training this layer keeps running estimates of its 2025-08-26T19:56:00.7988451Z computed mean and variance, which are then used for normalization during 2025-08-26T19:56:00.7989078Z evaluation. The running estimates are kept with a default :attr:`momentum` 2025-08-26T19:56:00.7989545Z of 0.1. 2025-08-26T19:56:00.7989672Z 2025-08-26T19:56:00.7989912Z If :attr:`track_running_stats` is set to ``False``, this layer then does not 2025-08-26T19:56:00.7990507Z keep running estimates, and batch statistics are instead used during 2025-08-26T19:56:00.7991124Z evaluation time as well. 2025-08-26T19:56:00.7991316Z 2025-08-26T19:56:00.7991425Z .. note:: 2025-08-26T19:56:00.7991784Z This :attr:`momentum` argument is different from one used in optimizer 2025-08-26T19:56:00.7992373Z classes and the conventional notion of momentum. Mathematically, the 2025-08-26T19:56:00.7992867Z update rule for running statistics here is 2025-08-26T19:56:00.7993394Z :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`, 2025-08-26T19:56:00.7994005Z where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the 2025-08-26T19:56:00.7994433Z new observed value. 2025-08-26T19:56:00.7994629Z 2025-08-26T19:56:00.7994938Z Because the Batch Normalization is done for each channel in the ``C`` dimension, computing 2025-08-26T19:56:00.7995626Z statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch 2025-08-26T19:56:00.7996191Z Normalization or Spatio-temporal Batch Normalization. 2025-08-26T19:56:00.7996537Z 2025-08-26T19:56:00.7996690Z Currently :class:`SyncBatchNorm` only supports 2025-08-26T19:56:00.7997249Z :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use 2025-08-26T19:56:00.7997888Z :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert 2025-08-26T19:56:00.7998440Z :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping 2025-08-26T19:56:00.7998874Z Network with DDP. 2025-08-26T19:56:00.7999037Z 2025-08-26T19:56:00.7999122Z Args: 2025-08-26T19:56:00.7999525Z num_features: :math:`C` from an expected input of size 2025-08-26T19:56:00.7999920Z :math:`(N, C, +)` 2025-08-26T19:56:00.8000311Z eps: a value added to the denominator for numerical stability. 2025-08-26T19:56:00.8000718Z Default: ``1e-5`` 2025-08-26T19:56:00.8001114Z momentum: the value used for the running_mean and running_var 2025-08-26T19:56:00.8001657Z computation. Can be set to ``None`` for cumulative moving average 2025-08-26T19:56:00.8002127Z (i.e. simple average). Default: 0.1 2025-08-26T19:56:00.8002574Z affine: a boolean value that when set to ``True``, this module has 2025-08-26T19:56:00.8003067Z learnable affine parameters. Default: ``True`` 2025-08-26T19:56:00.8003564Z track_running_stats: a boolean value that when set to ``True``, this 2025-08-26T19:56:00.8004149Z module tracks the running mean and variance, and when set to ``False``, 2025-08-26T19:56:00.8004747Z this module does not track such statistics, and initializes statistics 2025-08-26T19:56:00.8005298Z buffers :attr:`running_mean` and :attr:`running_var` as ``None``. 2025-08-26T19:56:00.8005866Z When these buffers are ``None``, this module always uses batch statistics. 2025-08-26T19:56:00.8006385Z in both training and eval modes. Default: ``True`` 2025-08-26T19:56:00.8006926Z process_group: synchronization of stats happen within each process group 2025-08-26T19:56:00.8007545Z individually. Default behavior is synchronization across the whole 2025-08-26T19:56:00.8007982Z world 2025-08-26T19:56:00.8008138Z 2025-08-26T19:56:00.8008228Z Shape: 2025-08-26T19:56:00.8008472Z - Input: :math:`(N, C, +)` 2025-08-26T19:56:00.8008912Z - Output: :math:`(N, C, +)` (same shape as input) 2025-08-26T19:56:00.8009180Z 2025-08-26T19:56:00.8009272Z .. note:: 2025-08-26T19:56:00.8009674Z Synchronization of batchnorm statistics occurs only while training, i.e. 2025-08-26T19:56:00.8010266Z synchronization is disabled when ``model.eval()`` is set or if 2025-08-26T19:56:00.8010734Z ``self.training`` is otherwise ``False``. 2025-08-26T19:56:00.8010981Z 2025-08-26T19:56:00.8011074Z Examples:: 2025-08-26T19:56:00.8011224Z 2025-08-26T19:56:00.8011323Z >>> # xdoctest: +SKIP 2025-08-26T19:56:00.8011671Z >>> # With Learnable Parameters 2025-08-26T19:56:00.8012011Z >>> m = nn.SyncBatchNorm(100) 2025-08-26T19:56:00.8012357Z >>> # creating process group (optional) 2025-08-26T19:56:00.8012737Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T19:56:00.8013107Z >>> ranks = list(range(8)) 2025-08-26T19:56:00.8013423Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T19:56:00.8013798Z >>> # Note: every rank calls into new_group for every 2025-08-26T19:56:00.8014212Z >>> # process group created, even if that rank is not 2025-08-26T19:56:00.8014594Z >>> # part of the group. 2025-08-26T19:56:00.8015051Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T19:56:00.8015641Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T19:56:00.8016081Z >>> # Without Learnable Parameters 2025-08-26T19:56:00.8016524Z >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group) 2025-08-26T19:56:00.8017026Z >>> input = torch.randn(20, 100, 35, 45, 10) 2025-08-26T19:56:00.8017372Z >>> output = m(input) 2025-08-26T19:56:00.8017557Z 2025-08-26T19:56:00.8017674Z >>> # network is nn.BatchNorm layer 2025-08-26T19:56:00.8018188Z >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group) 2025-08-26T19:56:00.8018766Z >>> # only single gpu per process is currently supported 2025-08-26T19:56:00.8019275Z >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel( 2025-08-26T19:56:00.8019801Z >>> sync_bn_network, 2025-08-26T19:56:00.8020158Z >>> device_ids=[args.local_rank], 2025-08-26T19:56:00.8020550Z >>> output_device=args.local_rank) 2025-08-26T19:56:00.8020894Z 2025-08-26T19:56:00.8021273Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.8021651Z 2025-08-26T19:56:00.8022356Z msg = Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=830. 2025-08-26T19:56:00.8023404Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.8024119Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers. 2025-08-26T19:56:00.8024566Z 2025-08-26T19:56:00.8024653Z Args: 2025-08-26T19:56:00.8025049Z module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers 2025-08-26T19:56:00.8025658Z process_group (optional): process group to scope synchronization, 2025-08-26T19:56:00.8026107Z default is the whole world 2025-08-26T19:56:00.8026340Z 2025-08-26T19:56:00.8026426Z Returns: 2025-08-26T19:56:00.8026837Z The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm` 2025-08-26T19:56:00.8027448Z layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer, 2025-08-26T19:56:00.8028014Z a new :class:`torch.nn.SyncBatchNorm` layer object will be returned 2025-08-26T19:56:00.8028433Z instead. 2025-08-26T19:56:00.8028599Z 2025-08-26T19:56:00.8028693Z Example:: 2025-08-26T19:56:00.8028837Z 2025-08-26T19:56:00.8028971Z >>> # Network with nn.BatchNorm layer 2025-08-26T19:56:00.8029368Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:00.8029744Z >>> module = torch.nn.Sequential( 2025-08-26T19:56:00.8030113Z >>> torch.nn.Linear(20, 100), 2025-08-26T19:56:00.8030487Z >>> torch.nn.BatchNorm1d(100), 2025-08-26T19:56:00.8030834Z >>> ).cuda() 2025-08-26T19:56:00.8031152Z >>> # creating process group (optional) 2025-08-26T19:56:00.8031555Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T19:56:00.8031967Z >>> ranks = list(range(8)) 2025-08-26T19:56:00.8032309Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T19:56:00.8032683Z >>> # Note: every rank calls into new_group for every 2025-08-26T19:56:00.8033121Z >>> # process group created, even if that rank is not 2025-08-26T19:56:00.8033511Z >>> # part of the group. 2025-08-26T19:56:00.8033853Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:00.8034354Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T19:56:00.8034942Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T19:56:00.8035582Z >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group) 2025-08-26T19:56:00.8036015Z 2025-08-26T19:56:00.8036101Z 2025-08-26T19:56:00.8036491Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.8036873Z 2025-08-26T19:56:00.8253534Z msg = Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py line=66. 2025-08-26T19:56:00.8254613Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.8255002Z 2025-08-26T19:56:00.8255316Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`. 2025-08-26T19:56:00.8255767Z 2025-08-26T19:56:00.8256042Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can 2025-08-26T19:56:00.8256772Z be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively. 2025-08-26T19:56:00.8257123Z 2025-08-26T19:56:00.8257456Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be 2025-08-26T19:56:00.8258164Z a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input; a `NamedShape` 2025-08-26T19:56:00.8258714Z (tuple of `(name, size)` tuples) for `NamedTensor` input. 2025-08-26T19:56:00.8259017Z 2025-08-26T19:56:00.8259103Z Shape: 2025-08-26T19:56:00.8259455Z - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at 2025-08-26T19:56:00.8260063Z dimension :attr:`dim` and :math:`*` means any number of dimensions including none. 2025-08-26T19:56:00.8260668Z - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and 2025-08-26T19:56:00.8261140Z :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`. 2025-08-26T19:56:00.8261399Z 2025-08-26T19:56:00.8261483Z Args: 2025-08-26T19:56:00.8261763Z dim (Union[int, str]): Dimension to be unflattened 2025-08-26T19:56:00.8262390Z unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension 2025-08-26T19:56:00.8262868Z 2025-08-26T19:56:00.8262957Z Examples: 2025-08-26T19:56:00.8263196Z >>> input = torch.randn(2, 50) 2025-08-26T19:56:00.8263512Z >>> # With tuple of ints 2025-08-26T19:56:00.8263808Z >>> m = nn.Sequential( 2025-08-26T19:56:00.8264077Z >>> nn.Linear(50, 50), 2025-08-26T19:56:00.8264376Z >>> nn.Unflatten(1, (2, 5, 5)) 2025-08-26T19:56:00.8264678Z >>> ) 2025-08-26T19:56:00.8264900Z >>> output = m(input) 2025-08-26T19:56:00.8265160Z >>> output.size() 2025-08-26T19:56:00.8265425Z torch.Size([2, 2, 5, 5]) 2025-08-26T19:56:00.8265709Z >>> # With torch.Size 2025-08-26T19:56:00.8265987Z >>> m = nn.Sequential( 2025-08-26T19:56:00.8266254Z >>> nn.Linear(50, 50), 2025-08-26T19:56:00.8266566Z >>> nn.Unflatten(1, torch.Size([2, 5, 5])) 2025-08-26T19:56:00.8266903Z >>> ) 2025-08-26T19:56:00.8267130Z >>> output = m(input) 2025-08-26T19:56:00.8267391Z >>> output.size() 2025-08-26T19:56:00.8267656Z torch.Size([2, 2, 5, 5]) 2025-08-26T19:56:00.8267961Z >>> # With namedshape (tuple of tuples) 2025-08-26T19:56:00.8268349Z >>> input = torch.randn(2, 50, names=("N", "features")) 2025-08-26T19:56:00.8268873Z >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5))) 2025-08-26T19:56:00.8269319Z >>> output = unflatten(input) 2025-08-26T19:56:00.8269626Z >>> output.size() 2025-08-26T19:56:00.8269895Z torch.Size([2, 2, 5, 5]) 2025-08-26T19:56:00.8270075Z 2025-08-26T19:56:00.8270333Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.8270725Z 2025-08-26T19:56:00.8625702Z msg = Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1798. 2025-08-26T19:56:00.8626799Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.8627401Z Creates a criterion that measures the triplet loss given input 2025-08-26T19:56:00.8627930Z tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor, 2025-08-26T19:56:00.8628470Z positive, and negative examples, respectively), and a nonnegative, 2025-08-26T19:56:00.8629075Z real-valued function ("distance function") used to compute the relationship 2025-08-26T19:56:00.8629760Z between the anchor and positive example ("positive distance") and the 2025-08-26T19:56:00.8630267Z anchor and negative example ("negative distance"). 2025-08-26T19:56:00.8630546Z 2025-08-26T19:56:00.8630761Z The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``) 2025-08-26T19:56:00.8631197Z can be described as: 2025-08-26T19:56:00.8631371Z 2025-08-26T19:56:00.8631477Z .. math:: 2025-08-26T19:56:00.8631761Z \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad 2025-08-26T19:56:00.8632262Z l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\} 2025-08-26T19:56:00.8632533Z 2025-08-26T19:56:00.8632795Z where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function 2025-08-26T19:56:00.8633474Z quantifying the closeness of two tensors, referred to as the :attr:`distance_function`; 2025-08-26T19:56:00.8634131Z and :math:`margin` is a nonnegative margin representing the minimum difference 2025-08-26T19:56:00.8634758Z between the positive and negative distances that is required for the loss to 2025-08-26T19:56:00.8635372Z be 0. The input tensors have :math:`N` elements each and can be of any shape 2025-08-26T19:56:00.8635858Z that the distance function can handle. 2025-08-26T19:56:00.8636087Z 2025-08-26T19:56:00.8636220Z If :attr:`reduction` is not ``'none'`` 2025-08-26T19:56:00.8636550Z (default ``'mean'``), then: 2025-08-26T19:56:00.8636753Z 2025-08-26T19:56:00.8636844Z .. math:: 2025-08-26T19:56:00.8637079Z \ell(x, y) = 2025-08-26T19:56:00.8637328Z \begin{cases} 2025-08-26T19:56:00.8637857Z \operatorname{mean}(L), & \text{if reduction} = \text{`mean';}\\ 2025-08-26T19:56:00.8638388Z \operatorname{sum}(L), & \text{if reduction} = \text{`sum'.} 2025-08-26T19:56:00.8638818Z \end{cases} 2025-08-26T19:56:00.8639052Z 2025-08-26T19:56:00.8639468Z See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet 2025-08-26T19:56:00.8640098Z loss for input tensors using the :math:`l_p` distance as the distance function. 2025-08-26T19:56:00.8640550Z 2025-08-26T19:56:00.8640699Z Args: 2025-08-26T19:56:00.8641449Z distance_function (Callable, optional): A nonnegative, real-valued function that 2025-08-26T19:56:00.8642129Z quantifies the closeness of two tensors. If not specified, 2025-08-26T19:56:00.8642629Z `nn.PairwiseDistance` will be used. Default: ``None`` 2025-08-26T19:56:00.8643196Z margin (float, optional): A nonnegative margin representing the minimum difference 2025-08-26T19:56:00.8643889Z between the positive and negative distances required for the loss to be 0. Larger 2025-08-26T19:56:00.8644590Z margins penalize cases where the negative examples are not distant enough from the 2025-08-26T19:56:00.8645192Z anchors, relative to the positives. Default: :math:`1`. 2025-08-26T19:56:00.8645833Z swap (bool, optional): Whether to use the distance swap described in the paper 2025-08-26T19:56:00.8646481Z `Learning shallow convolutional feature descriptors with triplet losses` by 2025-08-26T19:56:00.8647125Z V. Balntas, E. Riba et al. If True, and if the positive example is closer to the 2025-08-26T19:56:00.8647776Z negative example than the anchor is, swaps the positive example and the anchor in 2025-08-26T19:56:00.8648328Z the loss computation. Default: ``False``. 2025-08-26T19:56:00.8648930Z reduction (str, optional): Specifies the (optional) reduction to apply to the output: 2025-08-26T19:56:00.8649543Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T19:56:00.8650050Z ``'mean'``: the sum of the output will be divided by the number of 2025-08-26T19:56:00.8650614Z elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'`` 2025-08-26T19:56:00.8650984Z 2025-08-26T19:56:00.8651039Z 2025-08-26T19:56:00.8651143Z Shape: 2025-08-26T19:56:00.8651522Z - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions 2025-08-26T19:56:00.8652025Z as supported by the distance function. 2025-08-26T19:56:00.8652528Z - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar 2025-08-26T19:56:00.8653011Z otherwise. 2025-08-26T19:56:00.8653164Z 2025-08-26T19:56:00.8653265Z Examples: 2025-08-26T19:56:00.8653398Z 2025-08-26T19:56:00.8653577Z >>> # Initialize embeddings 2025-08-26T19:56:00.8653897Z >>> embedding = nn.Embedding(1000, 128) 2025-08-26T19:56:00.8654256Z >>> anchor_ids = torch.randint(0, 1000, (1,)) 2025-08-26T19:56:00.8654633Z >>> positive_ids = torch.randint(0, 1000, (1,)) 2025-08-26T19:56:00.8655004Z >>> negative_ids = torch.randint(0, 1000, (1,)) 2025-08-26T19:56:00.8655367Z >>> anchor = embedding(anchor_ids) 2025-08-26T19:56:00.8655715Z >>> positive = embedding(positive_ids) 2025-08-26T19:56:00.8656075Z >>> negative = embedding(negative_ids) 2025-08-26T19:56:00.8656380Z >>> 2025-08-26T19:56:00.8656617Z >>> # Built-in Distance Function 2025-08-26T19:56:00.8656932Z >>> triplet_loss = \ 2025-08-26T19:56:00.8657395Z >>> nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance()) 2025-08-26T19:56:00.8657958Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T19:56:00.8658339Z >>> output.backward() 2025-08-26T19:56:00.8658604Z >>> 2025-08-26T19:56:00.8658840Z >>> # Custom Distance Function 2025-08-26T19:56:00.8659142Z >>> def l_infinity(x1, x2): 2025-08-26T19:56:00.8659494Z >>> return torch.max(torch.abs(x1 - x2), dim=1).values 2025-08-26T19:56:00.8659859Z >>> 2025-08-26T19:56:00.8660174Z >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time") 2025-08-26T19:56:00.8660574Z >>> triplet_loss = ( 2025-08-26T19:56:00.8661041Z >>> nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5)) 2025-08-26T19:56:00.8661615Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T19:56:00.8661994Z >>> output.backward() 2025-08-26T19:56:00.8662247Z >>> 2025-08-26T19:56:00.8662489Z >>> # Custom Distance Function (Lambda) 2025-08-26T19:56:00.8662822Z >>> triplet_loss = ( 2025-08-26T19:56:00.8663135Z >>> nn.TripletMarginWithDistanceLoss( 2025-08-26T19:56:00.8663597Z >>> distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y))) 2025-08-26T19:56:00.8664101Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T19:56:00.8664478Z >>> output.backward() 2025-08-26T19:56:00.8664650Z 2025-08-26T19:56:00.8664752Z Reference: 2025-08-26T19:56:00.8665206Z V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses: 2025-08-26T19:56:00.8665867Z https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html 2025-08-26T19:56:00.8666334Z 2025-08-26T19:56:00.8666718Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17)) 2025-08-26T19:56:00.8667097Z 2025-08-26T19:56:00.8667663Z msg = Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1933. 2025-08-26T19:56:00.8668556Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.8669101Z The Connectionist Temporal Classification loss. 2025-08-26T19:56:00.8669363Z 2025-08-26T19:56:00.8669768Z Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the 2025-08-26T19:56:00.8670632Z probability of possible alignments of input to target, producing a loss value which is differentiable 2025-08-26T19:56:00.8671471Z with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which 2025-08-26T19:56:00.8672247Z limits the length of the target sequence such that it must be :math:`\leq` the input length. 2025-08-26T19:56:00.8672705Z 2025-08-26T19:56:00.8672803Z Args: 2025-08-26T19:56:00.8673098Z blank (int, optional): blank label. Default :math:`0`. 2025-08-26T19:56:00.8673620Z reduction (str, optional): Specifies the reduction to apply to the output: 2025-08-26T19:56:00.8674181Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T19:56:00.8674708Z ``'mean'``: the output losses will be divided by the target lengths and 2025-08-26T19:56:00.8675364Z then the mean over the batch is taken, ``'sum'``: the output losses will be summed. 2025-08-26T19:56:00.8675848Z Default: ``'mean'`` 2025-08-26T19:56:00.8676151Z zero_infinity (bool, optional): 2025-08-26T19:56:00.8676576Z Whether to zero infinite losses and the associated gradients. 2025-08-26T19:56:00.8677003Z Default: ``False`` 2025-08-26T19:56:00.8677387Z Infinite losses mainly occur when the inputs are too short 2025-08-26T19:56:00.8677804Z to be aligned to the targets. 2025-08-26T19:56:00.8678038Z 2025-08-26T19:56:00.8678127Z Shape: 2025-08-26T19:56:00.8678454Z - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`, 2025-08-26T19:56:00.8678901Z where :math:`T = \text{input length}`, 2025-08-26T19:56:00.8679251Z :math:`N = \text{batch size}`, and 2025-08-26T19:56:00.8679643Z :math:`C = \text{number of classes (including blank)}`. 2025-08-26T19:56:00.8680165Z The logarithmized probabilities of the outputs (e.g. obtained with 2025-08-26T19:56:00.8680663Z :func:`torch.nn.functional.log_softmax`). 2025-08-26T19:56:00.8681037Z - Targets: Tensor of size :math:`(N, S)` or 2025-08-26T19:56:00.8691621Z :math:`(\operatorname{sum}(\text{target\_lengths}))`, 2025-08-26T19:56:00.8692071Z where :math:`N = \text{batch size}` and 2025-08-26T19:56:00.8692507Z :math:`S = \text{max target length, if shape is } (N, S)`. 2025-08-26T19:56:00.8693004Z It represents the target sequences. Each element in the target 2025-08-26T19:56:00.8693582Z sequence is a class index. And the target index cannot be blank (default=0). 2025-08-26T19:56:00.8694121Z In the :math:`(N, S)` form, targets are padded to the 2025-08-26T19:56:00.8694547Z length of the longest sequence, and stacked. 2025-08-26T19:56:00.8694994Z In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form, 2025-08-26T19:56:00.8695474Z the targets are assumed to be un-padded and 2025-08-26T19:56:00.8695854Z concatenated within 1 dimension. 2025-08-26T19:56:00.8696309Z - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T19:56:00.8696856Z where :math:`N = \text{batch size}`. It represents the lengths of the 2025-08-26T19:56:00.8697387Z inputs (must each be :math:`\leq T`). And the lengths are specified 2025-08-26T19:56:00.8698050Z for each sequence to achieve masking under the assumption that sequences 2025-08-26T19:56:00.8698531Z are padded to equal lengths. 2025-08-26T19:56:00.8698974Z - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T19:56:00.8699527Z where :math:`N = \text{batch size}`. It represents lengths of the targets. 2025-08-26T19:56:00.8700108Z Lengths are specified for each sequence to achieve masking under the 2025-08-26T19:56:00.8700724Z assumption that sequences are padded to equal lengths. If target shape is 2025-08-26T19:56:00.8701287Z :math:`(N,S)`, target_lengths are effectively the stop index 2025-08-26T19:56:00.8701845Z :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for 2025-08-26T19:56:00.8702400Z each target in a batch. Lengths must each be :math:`\leq S` 2025-08-26T19:56:00.8702951Z If the targets are given as a 1d tensor that is the concatenation of individual 2025-08-26T19:56:00.8703611Z targets, the target_lengths must add up to the total length of the tensor. 2025-08-26T19:56:00.8704179Z - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or 2025-08-26T19:56:00.8704733Z ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or 2025-08-26T19:56:00.8705285Z :math:`()` if input is unbatched, where :math:`N = \text{batch size}`. 2025-08-26T19:56:00.8705621Z 2025-08-26T19:56:00.8705715Z Examples: 2025-08-26T19:56:00.8705922Z 2025-08-26T19:56:00.8706035Z >>> # Target are to be padded 2025-08-26T19:56:00.8706371Z >>> T = 50 # Input sequence length 2025-08-26T19:56:00.8706731Z >>> C = 20 # Number of classes (including blank) 2025-08-26T19:56:00.8707088Z >>> N = 16 # Batch size 2025-08-26T19:56:00.8707515Z >>> S = 30 # Target sequence length of longest target in batch (padding length) 2025-08-26T19:56:00.8708072Z >>> S_min = 10 # Minimum target length, for demonstration purposes 2025-08-26T19:56:00.8708473Z >>> 2025-08-26T19:56:00.8708797Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T19:56:00.8709343Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T19:56:00.8709776Z >>> 2025-08-26T19:56:00.8710106Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T19:56:00.8710646Z >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long) 2025-08-26T19:56:00.8711080Z >>> 2025-08-26T19:56:00.8711438Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T19:56:00.8711916Z >>> target_lengths = torch.randint( 2025-08-26T19:56:00.8712238Z ... low=S_min, 2025-08-26T19:56:00.8712509Z ... high=S, 2025-08-26T19:56:00.8712767Z ... size=(N,), 2025-08-26T19:56:00.8713049Z ... dtype=torch.long, 2025-08-26T19:56:00.8713328Z ... ) 2025-08-26T19:56:00.8713572Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T19:56:00.8713976Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T19:56:00.8714390Z >>> loss.backward() 2025-08-26T19:56:00.8714652Z >>> 2025-08-26T19:56:00.8714871Z >>> 2025-08-26T19:56:00.8715116Z >>> # Target are to be un-padded 2025-08-26T19:56:00.8715455Z >>> T = 50 # Input sequence length 2025-08-26T19:56:00.8715814Z >>> C = 20 # Number of classes (including blank) 2025-08-26T19:56:00.8716172Z >>> N = 16 # Batch size 2025-08-26T19:56:00.8716453Z >>> 2025-08-26T19:56:00.8716793Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T19:56:00.8717327Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T19:56:00.8717894Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T19:56:00.8718375Z >>> 2025-08-26T19:56:00.8718708Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T19:56:00.8719267Z >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long) 2025-08-26T19:56:00.8719749Z >>> target = torch.randint( 2025-08-26T19:56:00.8720059Z ... low=1, 2025-08-26T19:56:00.8720316Z ... high=C, 2025-08-26T19:56:00.8720582Z ... size=(sum(target_lengths),), 2025-08-26T19:56:00.8720917Z ... dtype=torch.long, 2025-08-26T19:56:00.8721207Z ... ) 2025-08-26T19:56:00.8721446Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T19:56:00.8721830Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T19:56:00.8722246Z >>> loss.backward() 2025-08-26T19:56:00.8722513Z >>> 2025-08-26T19:56:00.8722725Z >>> 2025-08-26T19:56:00.8723036Z >>> # Target are to be un-padded and unbatched (effectively N=1) 2025-08-26T19:56:00.8723505Z >>> T = 50 # Input sequence length 2025-08-26T19:56:00.8723875Z >>> C = 20 # Number of classes (including blank) 2025-08-26T19:56:00.8724217Z >>> 2025-08-26T19:56:00.8724547Z >>> # Initialize random batch of input vectors, for *size = (T,C) 2025-08-26T19:56:00.8725000Z >>> # xdoctest: +SKIP("FIXME: error in doctest") 2025-08-26T19:56:00.8725469Z >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_() 2025-08-26T19:56:00.8726017Z >>> input_lengths = torch.tensor(T, dtype=torch.long) 2025-08-26T19:56:00.8726382Z >>> 2025-08-26T19:56:00.8726705Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T19:56:00.8727268Z >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long) 2025-08-26T19:56:00.8727741Z >>> target = torch.randint( 2025-08-26T19:56:00.8728049Z ... low=1, 2025-08-26T19:56:00.8728292Z ... high=C, 2025-08-26T19:56:00.8728572Z ... size=(target_lengths,), 2025-08-26T19:56:00.8728997Z ... dtype=torch.long, 2025-08-26T19:56:00.8729293Z ... ) 2025-08-26T19:56:00.8729526Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T19:56:00.8729929Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T19:56:00.8730349Z >>> loss.backward() 2025-08-26T19:56:00.8730530Z 2025-08-26T19:56:00.8730635Z Reference: 2025-08-26T19:56:00.8730946Z A. Graves et al.: Connectionist Temporal Classification: 2025-08-26T19:56:00.8731486Z Labelling Unsegmented Sequence Data with Recurrent Neural Networks: 2025-08-26T19:56:00.8732023Z https://www.cs.toronto.edu/~graves/icml_2006.pdf 2025-08-26T19:56:00.8732295Z 2025-08-26T19:56:00.8732383Z Note: 2025-08-26T19:56:00.8732757Z In order to use CuDNN, the following must be satisfied: :attr:`targets` must be 2025-08-26T19:56:00.8733384Z in concatenated format, all :attr:`input_lengths` must be `T`. :math:`blank=0`, 2025-08-26T19:56:00.8733999Z :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of 2025-08-26T19:56:00.8734459Z dtype :attr:`torch.int32`. 2025-08-26T19:56:00.8734665Z 2025-08-26T19:56:00.8734958Z The regular implementation uses the (more common in PyTorch) `torch.long` dtype. 2025-08-26T19:56:00.8735359Z 2025-08-26T19:56:00.8735363Z 2025-08-26T19:56:00.8735460Z Note: 2025-08-26T19:56:00.8735828Z In some circumstances when using the CUDA backend with CuDNN, this operator 2025-08-26T19:56:00.8736476Z may select a nondeterministic algorithm to increase performance. If this is 2025-08-26T19:56:00.8737112Z undesirable, you can try to make the operation deterministic (potentially at 2025-08-26T19:56:00.8737906Z a performance cost) by setting ``torch.backends.cudnn.deterministic = 2025-08-26T19:56:00.8738350Z True``. 2025-08-26T19:56:00.8738787Z Please see the notes on :doc:`/notes/randomness` for background. 2025-08-26T19:56:00.8739208Z 2025-08-26T19:56:00.8739587Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.8739962Z 2025-08-26T19:56:00.9202960Z msg = Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py line=410. 2025-08-26T19:56:00.9203898Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.9204441Z Computes a partial inverse of :class:`MaxPool2d`. 2025-08-26T19:56:00.9204733Z 2025-08-26T19:56:00.9205002Z :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost. 2025-08-26T19:56:00.9205404Z 2025-08-26T19:56:00.9205636Z :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d` 2025-08-26T19:56:00.9206242Z including the indices of the maximal values and computes a partial inverse 2025-08-26T19:56:00.9206771Z in which all non-maximal values are set to zero. 2025-08-26T19:56:00.9207165Z 2025-08-26T19:56:00.9207254Z Note: 2025-08-26T19:56:00.9207710Z This operation may behave nondeterministically when the input indices has repeat values. 2025-08-26T19:56:00.9208562Z See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information. 2025-08-26T19:56:00.9209128Z 2025-08-26T19:56:00.9209398Z .. note:: :class:`MaxPool2d` can map several input sizes to the same output 2025-08-26T19:56:00.9209935Z sizes. Hence, the inversion process can get ambiguous. 2025-08-26T19:56:00.9210523Z To accommodate this, you can provide the needed output size 2025-08-26T19:56:00.9211065Z as an additional argument :attr:`output_size` in the forward call. 2025-08-26T19:56:00.9211529Z See the Inputs and Example below. 2025-08-26T19:56:00.9211765Z 2025-08-26T19:56:00.9211864Z Args: 2025-08-26T19:56:00.9212186Z kernel_size (int or tuple): Size of the max pooling window. 2025-08-26T19:56:00.9212660Z stride (int or tuple): Stride of the max pooling window. 2025-08-26T19:56:00.9213096Z It is set to :attr:`kernel_size` by default. 2025-08-26T19:56:00.9213540Z padding (int or tuple): Padding that was added to the input 2025-08-26T19:56:00.9213843Z 2025-08-26T19:56:00.9213942Z Inputs: 2025-08-26T19:56:00.9214188Z - `input`: the input Tensor to invert 2025-08-26T19:56:00.9214640Z - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d` 2025-08-26T19:56:00.9215140Z - `output_size` (optional): the targeted output size 2025-08-26T19:56:00.9215417Z 2025-08-26T19:56:00.9215519Z Shape: 2025-08-26T19:56:00.9215830Z - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`. 2025-08-26T19:56:00.9216362Z - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where 2025-08-26T19:56:00.9216712Z 2025-08-26T19:56:00.9216808Z .. math:: 2025-08-26T19:56:00.9217237Z H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]} 2025-08-26T19:56:00.9217628Z 2025-08-26T19:56:00.9217735Z .. math:: 2025-08-26T19:56:00.9218134Z W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]} 2025-08-26T19:56:00.9218530Z 2025-08-26T19:56:00.9218694Z or as given by :attr:`output_size` in the call operator 2025-08-26T19:56:00.9218991Z 2025-08-26T19:56:00.9219083Z Example:: 2025-08-26T19:56:00.9219216Z 2025-08-26T19:56:00.9219398Z >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True) 2025-08-26T19:56:00.9219819Z >>> unpool = nn.MaxUnpool2d(2, stride=2) 2025-08-26T19:56:00.9220189Z >>> input = torch.tensor([[[[ 1., 2., 3., 4.], 2025-08-26T19:56:00.9220554Z [ 5., 6., 7., 8.], 2025-08-26T19:56:00.9220898Z [ 9., 10., 11., 12.], 2025-08-26T19:56:00.9221299Z [13., 14., 15., 16.]]]]) 2025-08-26T19:56:00.9221645Z >>> output, indices = pool(input) 2025-08-26T19:56:00.9221991Z >>> unpool(output, indices) 2025-08-26T19:56:00.9222315Z tensor([[[[ 0., 0., 0., 0.], 2025-08-26T19:56:00.9222640Z [ 0., 6., 0., 8.], 2025-08-26T19:56:00.9222944Z [ 0., 0., 0., 0.], 2025-08-26T19:56:00.9223261Z [ 0., 14., 0., 16.]]]]) 2025-08-26T19:56:00.9223702Z >>> # Now using output_size to resolve an ambiguous size for the inverse 2025-08-26T19:56:00.9224192Z >>> input = torch.tensor([[[[ 1., 2., 3., 4., 5.], 2025-08-26T19:56:00.9224569Z [ 6., 7., 8., 9., 10.], 2025-08-26T19:56:00.9224908Z [11., 12., 13., 14., 15.], 2025-08-26T19:56:00.9225258Z [16., 17., 18., 19., 20.]]]]) 2025-08-26T19:56:00.9225616Z >>> output, indices = pool(input) 2025-08-26T19:56:00.9226057Z >>> # This call will not work without specifying output_size 2025-08-26T19:56:00.9226510Z >>> unpool(output, indices, output_size=input.size()) 2025-08-26T19:56:00.9226901Z tensor([[[[ 0., 0., 0., 0., 0.], 2025-08-26T19:56:00.9227232Z [ 0., 7., 0., 9., 0.], 2025-08-26T19:56:00.9227549Z [ 0., 0., 0., 0., 0.], 2025-08-26T19:56:00.9227860Z [ 0., 17., 0., 19., 0.]]]]) 2025-08-26T19:56:00.9228092Z 2025-08-26T19:56:00.9228096Z 2025-08-26T19:56:00.9228301Z 2025-08-26T19:56:00.9228686Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.9229064Z 2025-08-26T19:56:00.9489092Z msg = Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py line=272. 2025-08-26T19:56:00.9490219Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.9490942Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings. 2025-08-26T19:56:00.9491385Z 2025-08-26T19:56:00.9491717Z For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`, 2025-08-26T19:56:00.9492286Z and with 2D inputs, this class 2025-08-26T19:56:00.9492504Z 2025-08-26T19:56:00.9492822Z * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``, 2025-08-26T19:56:00.9493585Z * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``, 2025-08-26T19:56:00.9494342Z * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``. 2025-08-26T19:56:00.9494769Z 2025-08-26T19:56:00.9495145Z However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these 2025-08-26T19:56:00.9495716Z operations. 2025-08-26T19:56:00.9495872Z 2025-08-26T19:56:00.9496139Z EmbeddingBag also supports per-sample weights as an argument to the forward 2025-08-26T19:56:00.9496777Z pass. This scales the output of the Embedding before performing a weighted 2025-08-26T19:56:00.9497406Z reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the 2025-08-26T19:56:00.9498022Z only supported ``mode`` is ``"sum"``, which computes a weighted sum according to 2025-08-26T19:56:00.9498502Z :attr:`per_sample_weights`. 2025-08-26T19:56:00.9498715Z 2025-08-26T19:56:00.9498807Z Args: 2025-08-26T19:56:00.9499125Z num_embeddings (int): size of the dictionary of embeddings 2025-08-26T19:56:00.9499608Z embedding_dim (int): the size of each embedding vector 2025-08-26T19:56:00.9500216Z max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm` 2025-08-26T19:56:00.9500823Z is renormalized to have norm :attr:`max_norm`. 2025-08-26T19:56:00.9501562Z norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``. 2025-08-26T19:56:00.9502377Z scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of 2025-08-26T19:56:00.9503016Z the words in the mini-batch. Default ``False``. 2025-08-26T19:56:00.9503490Z Note: this option is not supported when ``mode="max"``. 2025-08-26T19:56:00.9504072Z mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag. 2025-08-26T19:56:00.9504686Z ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights` 2025-08-26T19:56:00.9505264Z into consideration. ``"mean"`` computes the average of the values 2025-08-26T19:56:00.9505803Z in the bag, ``"max"`` computes the max value over each bag. 2025-08-26T19:56:00.9506261Z Default: ``"mean"`` 2025-08-26T19:56:00.9506849Z sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See 2025-08-26T19:56:00.9507575Z Notes for more details regarding sparse gradients. Note: this option is not 2025-08-26T19:56:00.9508096Z supported when ``mode="max"``. 2025-08-26T19:56:00.9508807Z include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element 2025-08-26T19:56:00.9509535Z is equivalent to the size of `indices`. This matches the CSR format. 2025-08-26T19:56:00.9510233Z padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the 2025-08-26T19:56:00.9510988Z gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated 2025-08-26T19:56:00.9511654Z during training, i.e. it remains as a fixed "pad". For a newly constructed 2025-08-26T19:56:00.9512308Z EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all 2025-08-26T19:56:00.9512953Z zeros, but can be updated to another value to be used as the padding vector. 2025-08-26T19:56:00.9513596Z Note that the embedding vector at :attr:`padding_idx` is excluded from the 2025-08-26T19:56:00.9514094Z reduction. 2025-08-26T19:56:00.9514335Z 2025-08-26T19:56:00.9514428Z Attributes: 2025-08-26T19:56:00.9514911Z weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)` 2025-08-26T19:56:00.9515497Z initialized from :math:`\mathcal{N}(0, 1)`. 2025-08-26T19:56:00.9515779Z 2025-08-26T19:56:00.9515884Z Examples:: 2025-08-26T19:56:00.9516036Z 2025-08-26T19:56:00.9516211Z >>> # an EmbeddingBag module containing 10 tensors of size 3 2025-08-26T19:56:00.9516671Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum') 2025-08-26T19:56:00.9517085Z >>> # a batch of 2 samples of 4 indices each 2025-08-26T19:56:00.9517513Z >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T19:56:00.9517989Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T19:56:00.9518411Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:00.9518792Z >>> embedding_sum(input, offsets) 2025-08-26T19:56:00.9519129Z tensor([[-0.8861, -5.4350, -0.0523], 2025-08-26T19:56:00.9519462Z [ 1.1306, -2.5798, -1.0044]]) 2025-08-26T19:56:00.9519691Z 2025-08-26T19:56:00.9519805Z >>> # Example with padding_idx 2025-08-26T19:56:00.9520276Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2) 2025-08-26T19:56:00.9520811Z >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T19:56:00.9521274Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T19:56:00.9521661Z >>> embedding_sum(input, offsets) 2025-08-26T19:56:00.9522008Z tensor([[ 0.0000, 0.0000, 0.0000], 2025-08-26T19:56:00.9522337Z [-0.7082, 3.2145, -2.6251]]) 2025-08-26T19:56:00.9522550Z 2025-08-26T19:56:00.9522734Z >>> # An EmbeddingBag can be loaded from an Embedding like so 2025-08-26T19:56:00.9523195Z >>> embedding = nn.Embedding(10, 3, padding_idx=2) 2025-08-26T19:56:00.9523629Z >>> embedding_sum = nn.EmbeddingBag.from_pretrained( 2025-08-26T19:56:00.9524019Z embedding.weight, 2025-08-26T19:56:00.9524359Z padding_idx=embedding.padding_idx, 2025-08-26T19:56:00.9524695Z mode='sum') 2025-08-26T19:56:00.9524965Z 2025-08-26T19:56:00.9525378Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.9525755Z 2025-08-26T19:56:00.9561979Z msg = Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py line=186. 2025-08-26T19:56:00.9563044Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.9563597Z Take in and process masked source/target sequences. 2025-08-26T19:56:00.9563879Z 2025-08-26T19:56:00.9564003Z .. note:: 2025-08-26T19:56:00.9564271Z 2025-08-26T19:56:00.9564676Z If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are 2025-08-26T19:56:00.9565351Z not allowed to participate in the attention, 2025-08-26T19:56:00.9565820Z which is the opposite of the definition for :attr:`attn_mask` 2025-08-26T19:56:00.9566325Z in :func:`torch.nn.functional.scaled_dot_product_attention`. 2025-08-26T19:56:00.9566653Z 2025-08-26T19:56:00.9566740Z Args: 2025-08-26T19:56:00.9567027Z src: the sequence to the encoder (required). 2025-08-26T19:56:00.9567427Z tgt: the sequence to the decoder (required). 2025-08-26T19:56:00.9567872Z src_mask: the additive mask for the src sequence (optional). 2025-08-26T19:56:00.9568359Z tgt_mask: the additive mask for the tgt sequence (optional). 2025-08-26T19:56:00.9568948Z memory_mask: the additive mask for the encoder output (optional). 2025-08-26T19:56:00.9569530Z src_key_padding_mask: the Tensor mask for src keys per batch (optional). 2025-08-26T19:56:00.9570127Z tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional). 2025-08-26T19:56:00.9570736Z memory_key_padding_mask: the Tensor mask for memory keys per batch (optional). 2025-08-26T19:56:00.9571346Z src_is_causal: If specified, applies a causal mask as ``src_mask``. 2025-08-26T19:56:00.9571849Z Default: ``None``; try to detect a causal mask. 2025-08-26T19:56:00.9572216Z Warning: 2025-08-26T19:56:00.9572556Z ``src_is_causal`` provides a hint that ``src_mask`` is 2025-08-26T19:56:00.9573011Z the causal mask. Providing incorrect hints can result in 2025-08-26T19:56:00.9573485Z incorrect execution, including forward and backward 2025-08-26T19:56:00.9573878Z compatibility. 2025-08-26T19:56:00.9574287Z tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``. 2025-08-26T19:56:00.9574762Z Default: ``None``; try to detect a causal mask. 2025-08-26T19:56:00.9575125Z Warning: 2025-08-26T19:56:00.9575460Z ``tgt_is_causal`` provides a hint that ``tgt_mask`` is 2025-08-26T19:56:00.9575927Z the causal mask. Providing incorrect hints can result in 2025-08-26T19:56:00.9576455Z incorrect execution, including forward and backward 2025-08-26T19:56:00.9576854Z compatibility. 2025-08-26T19:56:00.9577235Z memory_is_causal: If specified, applies a causal mask as 2025-08-26T19:56:00.9577648Z ``memory_mask``. 2025-08-26T19:56:00.9577952Z Default: ``False``. 2025-08-26T19:56:00.9578240Z Warning: 2025-08-26T19:56:00.9578550Z ``memory_is_causal`` provides a hint that 2025-08-26T19:56:00.9578982Z ``memory_mask`` is the causal mask. Providing incorrect 2025-08-26T19:56:00.9579455Z hints can result in incorrect execution, including 2025-08-26T19:56:00.9579858Z forward and backward compatibility. 2025-08-26T19:56:00.9580115Z 2025-08-26T19:56:00.9580202Z Shape: 2025-08-26T19:56:00.9580602Z - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or 2025-08-26T19:56:00.9581104Z `(N, S, E)` if `batch_first=True`. 2025-08-26T19:56:00.9581619Z - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T19:56:00.9582114Z `(N, T, E)` if `batch_first=True`. 2025-08-26T19:56:00.9582551Z - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`. 2025-08-26T19:56:00.9583069Z - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`. 2025-08-26T19:56:00.9583511Z - memory_mask: :math:`(T, S)`. 2025-08-26T19:56:00.9584041Z - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T19:56:00.9584669Z - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`. 2025-08-26T19:56:00.9585308Z - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T19:56:00.9585694Z 2025-08-26T19:56:00.9586026Z Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked 2025-08-26T19:56:00.9586692Z positions. If a BoolTensor is provided, positions with ``True`` 2025-08-26T19:56:00.9587287Z are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor 2025-08-26T19:56:00.9587853Z is provided, it will be added to the attention weight. 2025-08-26T19:56:00.9588457Z [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by 2025-08-26T19:56:00.9589118Z the attention. If a BoolTensor is provided, the positions with the 2025-08-26T19:56:00.9589783Z value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. 2025-08-26T19:56:00.9590221Z 2025-08-26T19:56:00.9590485Z - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T19:56:00.9590996Z `(N, T, E)` if `batch_first=True`. 2025-08-26T19:56:00.9591242Z 2025-08-26T19:56:00.9591494Z Note: Due to the multi-head attention architecture in the transformer model, 2025-08-26T19:56:00.9592112Z the output sequence length of a transformer is same as the input sequence 2025-08-26T19:56:00.9592616Z (i.e. target) length of the decoder. 2025-08-26T19:56:00.9592849Z 2025-08-26T19:56:00.9593176Z where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the 2025-08-26T19:56:00.9593771Z batch size, :math:`E` is the feature number 2025-08-26T19:56:00.9594033Z 2025-08-26T19:56:00.9594126Z Examples: 2025-08-26T19:56:00.9594380Z >>> # xdoctest: +SKIP 2025-08-26T19:56:00.9594689Z >>> output = transformer_model( 2025-08-26T19:56:00.9595074Z ... src, tgt, src_mask=src_mask, tgt_mask=tgt_mask 2025-08-26T19:56:00.9595436Z ... ) 2025-08-26T19:56:00.9595670Z 2025-08-26T19:56:00.9596071Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.9596462Z 2025-08-26T19:56:00.9834188Z msg = Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=1766. 2025-08-26T19:56:00.9835466Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.9835873Z 2025-08-26T19:56:00.9836118Z Context manager for training with uneven inputs across processes in DDP. 2025-08-26T19:56:00.9836496Z 2025-08-26T19:56:00.9836731Z This context manager will keep track of already-joined DDP processes, 2025-08-26T19:56:00.9837299Z and "shadow" the forward and backward passes by inserting collective 2025-08-26T19:56:00.9838027Z communication operations to match with the ones created by non-joined 2025-08-26T19:56:00.9838627Z DDP processes. This will ensure each collective call has a corresponding 2025-08-26T19:56:00.9839219Z call by already-joined DDP processes, preventing hangs or errors that 2025-08-26T19:56:00.9839900Z would otherwise happen when training with uneven inputs across 2025-08-26T19:56:00.9840477Z processes. Alternatively, if the flag ``throw_on_early_termination`` is 2025-08-26T19:56:00.9841067Z specified to be ``True``, all trainers will throw an error once one rank 2025-08-26T19:56:00.9841599Z runs out of inputs, allowing these errors to be caught and handled 2025-08-26T19:56:00.9842046Z according to application logic. 2025-08-26T19:56:00.9842249Z 2025-08-26T19:56:00.9842487Z Once all DDP processes have joined, the context manager will broadcast 2025-08-26T19:56:00.9843155Z the model corresponding to the last joined process to all processes to 2025-08-26T19:56:00.9843650Z ensure the model is the same across all processes 2025-08-26T19:56:00.9844028Z (which is guaranteed by DDP). 2025-08-26T19:56:00.9844239Z 2025-08-26T19:56:00.9844447Z To use this to enable training with uneven inputs across processes, 2025-08-26T19:56:00.9845007Z simply wrap this context manager around your training loop. No further 2025-08-26T19:56:00.9845537Z modifications to the model or data loading is required. 2025-08-26T19:56:00.9845830Z 2025-08-26T19:56:00.9845930Z .. warning:: 2025-08-26T19:56:00.9846282Z If the model or training loop this context manager is wrapped around 2025-08-26T19:56:00.9846807Z has additional distributed collective operations, such as 2025-08-26T19:56:00.9847308Z ``SyncBatchNorm`` in the model's forward pass, then the flag 2025-08-26T19:56:00.9847819Z ``throw_on_early_termination`` must be enabled. This is because this 2025-08-26T19:56:00.9848373Z context manager is not aware of non-DDP collective communication. 2025-08-26T19:56:00.9848960Z This flag will cause all ranks to throw when any one rank 2025-08-26T19:56:00.9849477Z exhausts inputs, allowing these errors to be caught and recovered 2025-08-26T19:56:00.9849907Z from across all ranks. 2025-08-26T19:56:00.9850103Z 2025-08-26T19:56:00.9850188Z Args: 2025-08-26T19:56:00.9850502Z divide_by_initial_world_size (bool): If ``True``, will divide 2025-08-26T19:56:00.9851028Z gradients by the initial ``world_size`` DDP training was launched 2025-08-26T19:56:00.9851531Z with. If ``False``, will compute the effective world size 2025-08-26T19:56:00.9852000Z (number of ranks that have not depleted their inputs yet) and 2025-08-26T19:56:00.9852467Z divide gradients by that during allreduce. Set 2025-08-26T19:56:00.9852921Z ``divide_by_initial_world_size=True`` to ensure every input 2025-08-26T19:56:00.9853447Z sample including the uneven inputs have equal weight in terms of 2025-08-26T19:56:00.9853956Z how much they contribute to the global gradient. This is 2025-08-26T19:56:00.9854436Z achieved by always dividing the gradient by the initial 2025-08-26T19:56:00.9854927Z ``world_size`` even when we encounter uneven inputs. If you set 2025-08-26T19:56:00.9855421Z this to ``False``, we divide the gradient by the remaining 2025-08-26T19:56:00.9855971Z number of nodes. This ensures parity with training on a smaller 2025-08-26T19:56:00.9856470Z ``world_size`` although it also means the uneven inputs would 2025-08-26T19:56:00.9856985Z contribute more towards the global gradient. Typically, you 2025-08-26T19:56:00.9857498Z would want to set this to ``True`` for cases where the last few 2025-08-26T19:56:00.9858018Z inputs of your training job are uneven. In extreme cases, where 2025-08-26T19:56:00.9858523Z there is a large discrepancy in the number of inputs, setting 2025-08-26T19:56:00.9858987Z this to ``False`` might provide better results. 2025-08-26T19:56:00.9859468Z enable (bool): Whether to enable uneven input detection or not. Pass 2025-08-26T19:56:00.9859995Z in ``enable=False`` to disable in cases where you know that 2025-08-26T19:56:00.9860500Z inputs are even across participating processes. Default is 2025-08-26T19:56:00.9861006Z ``True``. 2025-08-26T19:56:00.9861574Z throw_on_early_termination (bool): Whether to throw an error 2025-08-26T19:56:00.9862224Z or continue training when at least one rank has exhausted 2025-08-26T19:56:00.9863113Z inputs. If ``True``, will throw upon the first rank reaching end 2025-08-26T19:56:00.9863670Z of data. If ``False``, will continue training with a smaller 2025-08-26T19:56:00.9864171Z effective world size until all ranks are joined. Note that if 2025-08-26T19:56:00.9864628Z this flag is specified, then the flag 2025-08-26T19:56:00.9865126Z ``divide_by_initial_world_size`` would be ignored. Default 2025-08-26T19:56:00.9865512Z is ``False``. 2025-08-26T19:56:00.9865689Z 2025-08-26T19:56:00.9865694Z 2025-08-26T19:56:00.9865791Z Example:: 2025-08-26T19:56:00.9865930Z 2025-08-26T19:56:00.9866046Z >>> # xdoctest: +SKIP("Distributed") 2025-08-26T19:56:00.9866378Z >>> import torch 2025-08-26T19:56:00.9866666Z >>> import torch.distributed as dist 2025-08-26T19:56:00.9866980Z >>> import os 2025-08-26T19:56:00.9867260Z >>> import torch.multiprocessing as mp 2025-08-26T19:56:00.9867613Z >>> import torch.nn as nn 2025-08-26T19:56:00.9867916Z >>> # On each spawned worker 2025-08-26T19:56:00.9868205Z >>> def worker(rank): 2025-08-26T19:56:00.9868563Z >>> dist.init_process_group("nccl", rank=rank, world_size=2) 2025-08-26T19:56:00.9868976Z >>> torch.cuda.set_device(rank) 2025-08-26T19:56:00.9869341Z >>> model = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T19:56:00.9869767Z >>> model = torch.nn.parallel.DistributedDataParallel( 2025-08-26T19:56:00.9870206Z >>> model, device_ids=[rank], output_device=rank 2025-08-26T19:56:00.9870557Z >>> ) 2025-08-26T19:56:00.9870825Z >>> # Rank 1 gets one more input than rank 0. 2025-08-26T19:56:00.9871255Z >>> inputs = [torch.tensor([1]).float() for _ in range(10 + rank)] 2025-08-26T19:56:00.9871679Z >>> with model.join(): 2025-08-26T19:56:00.9871980Z >>> for _ in range(5): 2025-08-26T19:56:00.9872291Z >>> for inp in inputs: 2025-08-26T19:56:00.9872618Z >>> loss = model(inp).sum() 2025-08-26T19:56:00.9872962Z >>> loss.backward() 2025-08-26T19:56:00.9873379Z >>> # Without the join() API, the below synchronization will hang 2025-08-26T19:56:00.9873853Z >>> # blocking for rank 1's allreduce to complete. 2025-08-26T19:56:00.9874240Z >>> torch.cuda.synchronize(device=rank) 2025-08-26T19:56:00.9874493Z 2025-08-26T19:56:00.9874757Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.9875147Z 2025-08-26T19:56:00.9875917Z msg = Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=2057. 2025-08-26T19:56:00.9877043Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:00.9877480Z 2025-08-26T19:56:00.9877797Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction. 2025-08-26T19:56:00.9878238Z 2025-08-26T19:56:00.9878465Z Registers an optimizer with DDP such that the optimization for a 2025-08-26T19:56:00.9879012Z parameter will run immediately when that parameter's gradient is 2025-08-26T19:56:00.9879546Z finished with reduction, instead of waiting for all parameters' 2025-08-26T19:56:00.9880106Z gradients to finish reduction. This can result in a training speedup 2025-08-26T19:56:00.9880679Z depending on your workload since the optimizer can run while gradient 2025-08-26T19:56:00.9881264Z reduction for other parameters are still ongoing. In addition, this has 2025-08-26T19:56:00.9881842Z the potential to reduce peak memory consumption during training, as it 2025-08-26T19:56:00.9882405Z only needs to load the per-parameter optimizer states of a single 2025-08-26T19:56:00.9882956Z parameter at a time, instead of loading all per-parameter optimizer 2025-08-26T19:56:00.9883419Z states at once. 2025-08-26T19:56:00.9883560Z 2025-08-26T19:56:00.9883643Z Args: 2025-08-26T19:56:00.9883971Z optim (Type): a ``torch.optim.Optimizer`` class to be registered 2025-08-26T19:56:00.9884395Z as a fused optimizer. 2025-08-26T19:56:00.9884746Z *args (Sequence[Any]): Arguments to forward to `optim`. 2025-08-26T19:56:00.9885261Z optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters 2025-08-26T19:56:00.9885823Z to optimize, similar to `params` argument of traditional `torch.optim` 2025-08-26T19:56:00.9886447Z Optimizers. If this is omitted, all DDP model parameters will be 2025-08-26T19:56:00.9886874Z optimized. 2025-08-26T19:56:00.9887220Z **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`. 2025-08-26T19:56:00.9887538Z 2025-08-26T19:56:00.9887630Z .. warning :: 2025-08-26T19:56:00.9887996Z _register_fused_optim should only be called once on a DDP instance, 2025-08-26T19:56:00.9888565Z and registering multiple fused optimizers for the same DDP model 2025-08-26T19:56:00.9889151Z is not currently supported. Please ping 2025-08-26T19:56:00.9889634Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T19:56:00.9890093Z for your use case. 2025-08-26T19:56:00.9890274Z 2025-08-26T19:56:00.9890368Z .. warning :: 2025-08-26T19:56:00.9890706Z _register_fused_optim and register_comm_hook currently do not 2025-08-26T19:56:00.9891246Z compose together, meaning that custom DDP communication hooks are 2025-08-26T19:56:00.9891758Z not supported with overlapped optimizers. Please ping 2025-08-26T19:56:00.9892284Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T19:56:00.9892734Z for your use case. 2025-08-26T19:56:00.9892894Z 2025-08-26T19:56:00.9892997Z .. warning :: 2025-08-26T19:56:00.9893356Z Gradient accumulation and DDP `no_sync` are currently not supported 2025-08-26T19:56:00.9893836Z with overlapped optimizer. Please ping 2025-08-26T19:56:00.9894313Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T19:56:00.9894762Z for your use case. 2025-08-26T19:56:00.9894920Z 2025-08-26T19:56:00.9895010Z Example:: 2025-08-26T19:56:00.9895147Z 2025-08-26T19:56:00.9895279Z >>> # xdoctest: +SKIP("No rendezvous handler") 2025-08-26T19:56:00.9895836Z >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...') 2025-08-26T19:56:00.9896476Z >>> net = torch.nn.parallel.DistributedDataParallel(model, pg) 2025-08-26T19:56:00.9896897Z >>> lr = 1e-2 2025-08-26T19:56:00.9897134Z >>> betas = (0.9, 0.99) 2025-08-26T19:56:00.9897412Z >>> eps = 1e-6 2025-08-26T19:56:00.9897797Z >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps) 2025-08-26T19:56:00.9898279Z >>> # Example with subset of parameters 2025-08-26T19:56:00.9898647Z >>> params_to_opt = [list(net.parameters())[0]] 2025-08-26T19:56:00.9899079Z >>> net._register_fused_optim( 2025-08-26T19:56:00.9899527Z ... torch.optim.Adam, lr, optim_params=params_to_opt, betas=betas, eps=eps 2025-08-26T19:56:00.9899975Z ... ) 2025-08-26T19:56:00.9900096Z 2025-08-26T19:56:00.9900352Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:00.9900740Z 2025-08-26T19:56:01.0118530Z msg = Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=14. 2025-08-26T19:56:01.0119626Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.0120251Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``. 2025-08-26T19:56:01.0120606Z 2025-08-26T19:56:01.0120893Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T19:56:01.0121589Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T19:56:01.0122367Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T19:56:01.0123311Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T19:56:01.0123932Z 2025-08-26T19:56:01.0124081Z .. note:: 2025-08-26T19:56:01.0124689Z Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive 2025-08-26T19:56:01.0125709Z than the utility function ``convert_conv2d_weight_memory_format``. Any 2025-08-26T19:56:01.0126398Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T19:56:01.0126966Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T19:56:01.0127558Z One place we are confident in is that NHWC(channels_last) conversion for 2025-08-26T19:56:01.0128146Z convolution in cuDNN, as it is beneficial to run convolution in NHWC, 2025-08-26T19:56:01.0128716Z even in cases where we have to apply permutation to input tensors. 2025-08-26T19:56:01.0129110Z 2025-08-26T19:56:01.0129358Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T19:56:01.0129825Z channels_last. This ensures that; 2025-08-26T19:56:01.0130286Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T19:56:01.0130881Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T19:56:01.0131492Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T19:56:01.0131968Z from memory_format conversion. 2025-08-26T19:56:01.0132200Z 2025-08-26T19:56:01.0132429Z The optimal case is that, layers between convolution layers are channels 2025-08-26T19:56:01.0133029Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T19:56:01.0133638Z encounters the first convolution layer and stay in that memory format. 2025-08-26T19:56:01.0134249Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T19:56:01.0134612Z 2025-08-26T19:56:01.0134841Z In case where a channels last incompatible layer is between convolution 2025-08-26T19:56:01.0135414Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T19:56:01.0135983Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T19:56:01.0136573Z contiguous format and be permuted to channels last when it encounters 2025-08-26T19:56:01.0137139Z another convolution layer. There's no point in propagating that 2025-08-26T19:56:01.0137858Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T19:56:01.0138317Z ``memory_format``. 2025-08-26T19:56:01.0138494Z 2025-08-26T19:56:01.0138745Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T19:56:01.0139423Z there might have been a better spot to fuse the permutation other than 2025-08-26T19:56:01.0139894Z immediately before a convolution. 2025-08-26T19:56:01.0140139Z 2025-08-26T19:56:01.0140226Z Args: 2025-08-26T19:56:01.0140579Z module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container 2025-08-26T19:56:01.0141034Z ``nn.Module`` 2025-08-26T19:56:01.0141400Z memory_format: user specified ``memory_format``, 2025-08-26T19:56:01.0141857Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T19:56:01.0142171Z 2025-08-26T19:56:01.0142261Z Returns: 2025-08-26T19:56:01.0142544Z The original module with updated ``nn.Conv2d`` 2025-08-26T19:56:01.0142801Z 2025-08-26T19:56:01.0142899Z Example: 2025-08-26T19:56:01.0143169Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:01.0143587Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T19:56:01.0143977Z >>> input = torch.randint( 2025-08-26T19:56:01.0144390Z ... 1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T19:56:01.0144742Z ... ) 2025-08-26T19:56:01.0144988Z >>> model = nn.Sequential( 2025-08-26T19:56:01.0145313Z >>> nn.Conv2d(8, 4, 3)).cuda().half() 2025-08-26T19:56:01.0145657Z >>> # This is identical to: 2025-08-26T19:56:01.0146113Z >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last) 2025-08-26T19:56:01.0146664Z >>> model = nn.utils.convert_conv2d_weight_memory_format( 2025-08-26T19:56:01.0147135Z ... model, torch.channels_last 2025-08-26T19:56:01.0147455Z ... ) 2025-08-26T19:56:01.0147683Z >>> out = model(input) 2025-08-26T19:56:01.0147964Z 2025-08-26T19:56:01.0148347Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.0148727Z 2025-08-26T19:56:01.0149419Z msg = Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=93. 2025-08-26T19:56:01.0150461Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.0151077Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format`` 2025-08-26T19:56:01.0151691Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T19:56:01.0152379Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T19:56:01.0153059Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T19:56:01.0153770Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T19:56:01.0154203Z 2025-08-26T19:56:01.0154311Z .. note:: 2025-08-26T19:56:01.0154698Z Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive 2025-08-26T19:56:01.0155305Z than the utility function ``convert_conv3d_weight_memory_format``. Any 2025-08-26T19:56:01.0155882Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T19:56:01.0156454Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T19:56:01.0157051Z One place we are confident in is that NDHWC(channels_last_3d) conversion for 2025-08-26T19:56:01.0157638Z convolution in cuDNN, as it is beneficial to run convolution in NDHWC, 2025-08-26T19:56:01.0158196Z even in cases where we have to apply permutation to input tensors. 2025-08-26T19:56:01.0158538Z 2025-08-26T19:56:01.0158770Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T19:56:01.0159255Z channels_last_3d. This ensures that; 2025-08-26T19:56:01.0159699Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T19:56:01.0160282Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T19:56:01.0160928Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T19:56:01.0161414Z from memory_format conversion. 2025-08-26T19:56:01.0161633Z 2025-08-26T19:56:01.0161876Z The optimal case is that, layers between convolution layers are channels 2025-08-26T19:56:01.0162464Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T19:56:01.0163070Z encounters the first convolution layer and stay in that memory format. 2025-08-26T19:56:01.0163690Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T19:56:01.0164057Z 2025-08-26T19:56:01.0164298Z In case where a channels last incompatible layer is between convolution 2025-08-26T19:56:01.0164873Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T19:56:01.0165437Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T19:56:01.0166030Z contiguous format and be permuted to channels last when it encounters 2025-08-26T19:56:01.0166636Z another convolution layer. There's no point in propagating that 2025-08-26T19:56:01.0167200Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T19:56:01.0167638Z ``memory_format``. 2025-08-26T19:56:01.0167825Z 2025-08-26T19:56:01.0168064Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T19:56:01.0168658Z there might have been a better spot to fuse the permutation other than 2025-08-26T19:56:01.0169271Z immediately before a convolution. 2025-08-26T19:56:01.0169515Z 2025-08-26T19:56:01.0169619Z Args: 2025-08-26T19:56:01.0169961Z module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container 2025-08-26T19:56:01.0170414Z ``nn.Module`` 2025-08-26T19:56:01.0170792Z memory_format: user specified ``memory_format``, 2025-08-26T19:56:01.0171258Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T19:56:01.0171564Z 2025-08-26T19:56:01.0171651Z Returns: 2025-08-26T19:56:01.0171942Z The original module with updated ``nn.Conv3d`` 2025-08-26T19:56:01.0172220Z 2025-08-26T19:56:01.0172310Z Example: 2025-08-26T19:56:01.0172597Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:01.0173021Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T19:56:01.0173403Z >>> input = torch.randint( 2025-08-26T19:56:01.0173779Z ... 1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T19:56:01.0174150Z ... ) 2025-08-26T19:56:01.0174398Z >>> model = nn.Sequential( 2025-08-26T19:56:01.0174714Z >>> nn.Conv3d(8, 4, 3)).cuda().half() 2025-08-26T19:56:01.0175060Z >>> # This is identical to: 2025-08-26T19:56:01.0175539Z >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d) 2025-08-26T19:56:01.0176228Z >>> model = nn.utils.convert_conv3d_weight_memory_format( 2025-08-26T19:56:01.0176637Z ... model, torch.channels_last_3d 2025-08-26T19:56:01.0176963Z ... ) 2025-08-26T19:56:01.0177202Z >>> out = model(input) 2025-08-26T19:56:01.0177479Z 2025-08-26T19:56:01.0177844Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.0178233Z 2025-08-26T19:56:01.0230082Z msg = Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrize.py line=424. 2025-08-26T19:56:01.0231202Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.0231763Z Register a parametrization to a tensor in a module. 2025-08-26T19:56:01.0232051Z 2025-08-26T19:56:01.0232333Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-08-26T19:56:01.0233032Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-08-26T19:56:01.0233793Z If the original tensor requires a gradient, the backward pass will differentiate 2025-08-26T19:56:01.0234480Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-08-26T19:56:01.0234913Z 2025-08-26T19:56:01.0235234Z The first time that a module registers a parametrization, this function will add an attribute 2025-08-26T19:56:01.0235933Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-08-26T19:56:01.0236305Z 2025-08-26T19:56:01.0236583Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-08-26T19:56:01.0237103Z ``module.parametrizations.weight``. 2025-08-26T19:56:01.0237341Z 2025-08-26T19:56:01.0237619Z The original tensor will be accessible under 2025-08-26T19:56:01.0238029Z ``module.parametrizations.weight.original``. 2025-08-26T19:56:01.0238307Z 2025-08-26T19:56:01.0238579Z Parametrizations may be concatenated by registering several parametrizations 2025-08-26T19:56:01.0239152Z on the same attribute. 2025-08-26T19:56:01.0239333Z 2025-08-26T19:56:01.0239596Z The training mode of a registered parametrization is updated on registration 2025-08-26T19:56:01.0240096Z to match the training mode of the host module 2025-08-26T19:56:01.0240358Z 2025-08-26T19:56:01.0240671Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-08-26T19:56:01.0241243Z using the context manager :func:`cached`. 2025-08-26T19:56:01.0241478Z 2025-08-26T19:56:01.0241809Z A :attr:`parametrization` may optionally implement a method with signature 2025-08-26T19:56:01.0242183Z 2025-08-26T19:56:01.0242310Z .. code-block:: python 2025-08-26T19:56:01.0242491Z 2025-08-26T19:56:01.0242714Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-08-26T19:56:01.0243072Z 2025-08-26T19:56:01.0243343Z This method is called on the unparametrized tensor when the first parametrization 2025-08-26T19:56:01.0243967Z is registered to compute the initial value of the original tensor. 2025-08-26T19:56:01.0244623Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-08-26T19:56:01.0244629Z 2025-08-26T19:56:01.0244947Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-08-26T19:56:01.0245255Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-08-26T19:56:01.0245260Z 2025-08-26T19:56:01.0245500Z It is possible for the first parametrization to depend on several inputs. 2025-08-26T19:56:01.0245748Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-08-26T19:56:01.0246000Z (see the example implementation of a ``RankOne`` parametrization below). 2025-08-26T19:56:01.0246004Z 2025-08-26T19:56:01.0246346Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-08-26T19:56:01.0246494Z with names ``original0``, ``original1``,... 2025-08-26T19:56:01.0246498Z 2025-08-26T19:56:01.0246586Z .. note:: 2025-08-26T19:56:01.0246590Z 2025-08-26T19:56:01.0246875Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-08-26T19:56:01.0247025Z once to perform a number of consistency checks. 2025-08-26T19:56:01.0247300Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-08-26T19:56:01.0247436Z and nothing will be called otherwise. 2025-08-26T19:56:01.0247441Z 2025-08-26T19:56:01.0247530Z .. note:: 2025-08-26T19:56:01.0247534Z 2025-08-26T19:56:01.0247755Z In most situations, ``right_inverse`` will be a function such that 2025-08-26T19:56:01.0247879Z ``forward(right_inverse(X)) == X`` (see 2025-08-26T19:56:01.0248186Z `right inverse `_). 2025-08-26T19:56:01.0248484Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-08-26T19:56:01.0248578Z to relax this. 2025-08-26T19:56:01.0248583Z 2025-08-26T19:56:01.0248684Z .. warning:: 2025-08-26T19:56:01.0248688Z 2025-08-26T19:56:01.0249039Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-08-26T19:56:01.0249320Z will register a number of new parameters. If such parametrization is registered 2025-08-26T19:56:01.0249598Z after the optimizer is created, these new parameters will need to be added manually 2025-08-26T19:56:01.0249799Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-08-26T19:56:01.0249803Z 2025-08-26T19:56:01.0249904Z Args: 2025-08-26T19:56:01.0250119Z module (nn.Module): module on which to register the parametrization 2025-08-26T19:56:01.0250355Z tensor_name (str): name of the parameter or buffer on which to register 2025-08-26T19:56:01.0250464Z the parametrization 2025-08-26T19:56:01.0250709Z parametrization (nn.Module): the parametrization to register 2025-08-26T19:56:01.0250813Z Keyword args: 2025-08-26T19:56:01.0251031Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-08-26T19:56:01.0251241Z may change the dtype and shape of the tensor. Default: `False` 2025-08-26T19:56:01.0251516Z Warning: the parametrization is not checked for consistency upon registration. 2025-08-26T19:56:01.0251638Z Enable this flag at your own risk. 2025-08-26T19:56:01.0251717Z 2025-08-26T19:56:01.0251807Z Raises: 2025-08-26T19:56:01.0252105Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-08-26T19:56:01.0252110Z 2025-08-26T19:56:01.0252216Z Examples: 2025-08-26T19:56:01.0252368Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T19:56:01.0252480Z >>> import torch 2025-08-26T19:56:01.0252588Z >>> import torch.nn as nn 2025-08-26T19:56:01.0252728Z >>> import torch.nn.utils.parametrize as P 2025-08-26T19:56:01.0252825Z >>> 2025-08-26T19:56:01.0252935Z >>> class Symmetric(nn.Module): 2025-08-26T19:56:01.0253054Z >>> def forward(self, X): 2025-08-26T19:56:01.0253234Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-08-26T19:56:01.0253317Z >>> 2025-08-26T19:56:01.0253446Z >>> def right_inverse(self, A): 2025-08-26T19:56:01.0253546Z >>> return A.triu() 2025-08-26T19:56:01.0253633Z >>> 2025-08-26T19:56:01.0253746Z >>> m = nn.Linear(5, 5) 2025-08-26T19:56:01.0253920Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-08-26T19:56:01.0254178Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-08-26T19:56:01.0254263Z True 2025-08-26T19:56:01.0254364Z >>> A = torch.rand(5, 5) 2025-08-26T19:56:01.0254493Z >>> A = A + A.T # A is now symmetric 2025-08-26T19:56:01.0254700Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-08-26T19:56:01.0254836Z >>> print(torch.allclose(m.weight, A)) 2025-08-26T19:56:01.0254922Z True 2025-08-26T19:56:01.0254926Z 2025-08-26T19:56:01.0255035Z >>> class RankOne(nn.Module): 2025-08-26T19:56:01.0255157Z >>> def forward(self, x, y): 2025-08-26T19:56:01.0255302Z >>> # Form a rank 1 matrix multiplying two vectors 2025-08-26T19:56:01.0255455Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-08-26T19:56:01.0255542Z >>> 2025-08-26T19:56:01.0255660Z >>> def right_inverse(self, Z): 2025-08-26T19:56:01.0255800Z >>> # Project Z onto the rank 1 matrices 2025-08-26T19:56:01.0255957Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-08-26T19:56:01.0256097Z >>> # Return rescaled singular vectors 2025-08-26T19:56:01.0256251Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-08-26T19:56:01.0256406Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-08-26T19:56:01.0256504Z >>> 2025-08-26T19:56:01.0256657Z >>> linear_rank_one = P.register_parametrization( 2025-08-26T19:56:01.0256798Z ... nn.Linear(4, 4), "weight", RankOne() 2025-08-26T19:56:01.0256884Z ... ) 2025-08-26T19:56:01.0257093Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-08-26T19:56:01.0257189Z 1 2025-08-26T19:56:01.0257193Z 2025-08-26T19:56:01.0257278Z 2025-08-26T19:56:01.0257548Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.0257553Z 2025-08-26T19:56:01.0341027Z msg = Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=979. 2025-08-26T19:56:01.0341359Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.0341780Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension. 2025-08-26T19:56:01.0341785Z 2025-08-26T19:56:01.0342043Z Prunes tensor corresponding to parameter called ``name`` in ``module`` 2025-08-26T19:56:01.0342265Z by removing the specified ``amount`` of (currently unpruned) channels 2025-08-26T19:56:01.0342446Z along the specified ``dim`` with the lowest L\ ``n``-norm. 2025-08-26T19:56:01.0342663Z Modifies module in place (and also return the modified module) 2025-08-26T19:56:01.0342752Z by: 2025-08-26T19:56:01.0342827Z 2025-08-26T19:56:01.0343054Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T19:56:01.0343280Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T19:56:01.0343499Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T19:56:01.0343728Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T19:56:01.0343831Z ``name+'_orig'``. 2025-08-26T19:56:01.0343836Z 2025-08-26T19:56:01.0343938Z Args: 2025-08-26T19:56:01.0344124Z module (nn.Module): module containing the tensor to prune 2025-08-26T19:56:01.0344312Z name (str): parameter name within ``module`` on which pruning 2025-08-26T19:56:01.0344421Z will act. 2025-08-26T19:56:01.0344597Z amount (int or float): quantity of parameters to prune. 2025-08-26T19:56:01.0344788Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T19:56:01.0344998Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T19:56:01.0345135Z absolute number of parameters to prune. 2025-08-26T19:56:01.0345448Z n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid 2025-08-26T19:56:01.0345611Z entries for argument ``p`` in :func:`torch.norm`. 2025-08-26T19:56:01.0345918Z dim (int): index of the dim along which we define channels to prune. 2025-08-26T19:56:01.0346245Z importance_scores (torch.Tensor): tensor of importance scores (of same 2025-08-26T19:56:01.0346561Z shape as module parameter) used to compute mask for pruning. 2025-08-26T19:56:01.0346990Z The values in this tensor indicate the importance of the corresponding 2025-08-26T19:56:01.0347241Z elements in the parameter being pruned. 2025-08-26T19:56:01.0347554Z If unspecified or None, the module parameter will be used in its place. 2025-08-26T19:56:01.0347559Z 2025-08-26T19:56:01.0347653Z Returns: 2025-08-26T19:56:01.0347892Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T19:56:01.0347897Z 2025-08-26T19:56:01.0347988Z Examples: 2025-08-26T19:56:01.0348115Z >>> from torch.nn.utils import prune 2025-08-26T19:56:01.0348239Z >>> m = prune.ln_structured( 2025-08-26T19:56:01.0348482Z ... nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf") 2025-08-26T19:56:01.0348587Z ... ) 2025-08-26T19:56:01.0348671Z 2025-08-26T19:56:01.0348931Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.0348936Z 2025-08-26T19:56:01.0349570Z msg = Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1026. 2025-08-26T19:56:01.0349917Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.0349925Z 2025-08-26T19:56:01.0350543Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``. 2025-08-26T19:56:01.0350552Z 2025-08-26T19:56:01.0350754Z Modifies modules in place by: 2025-08-26T19:56:01.0350780Z 2025-08-26T19:56:01.0351191Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T19:56:01.0351493Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T19:56:01.0351762Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T19:56:01.0351975Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T19:56:01.0352080Z ``name+'_orig'``. 2025-08-26T19:56:01.0352084Z 2025-08-26T19:56:01.0352172Z Args: 2025-08-26T19:56:01.0352381Z parameters (Iterable of (module, name) tuples): parameters of 2025-08-26T19:56:01.0352590Z the model to prune in a global fashion, i.e. by aggregating all 2025-08-26T19:56:01.0352850Z weights prior to deciding which ones to prune. module must be of 2025-08-26T19:56:01.0353017Z type :class:`nn.Module`, and name must be a string. 2025-08-26T19:56:01.0353241Z pruning_method (function): a valid pruning function from this module, 2025-08-26T19:56:01.0353421Z or a custom one implemented by the user that satisfies the 2025-08-26T19:56:01.0353668Z implementation guidelines and has ``PRUNING_TYPE='unstructured'``. 2025-08-26T19:56:01.0353904Z importance_scores (dict): a dictionary mapping (module, name) tuples to 2025-08-26T19:56:01.0354143Z the corresponding parameter's importance scores tensor. The tensor 2025-08-26T19:56:01.0354356Z should be the same shape as the parameter, and is used for computing 2025-08-26T19:56:01.0354456Z mask for pruning. 2025-08-26T19:56:01.0354678Z If unspecified or None, the parameter will be used in place of its 2025-08-26T19:56:01.0354781Z importance scores. 2025-08-26T19:56:01.0354924Z kwargs: other keyword arguments such as: 2025-08-26T19:56:01.0355126Z amount (int or float): quantity of parameters to prune across the 2025-08-26T19:56:01.0355231Z specified parameters. 2025-08-26T19:56:01.0355419Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T19:56:01.0355624Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T19:56:01.0355770Z absolute number of parameters to prune. 2025-08-26T19:56:01.0355776Z 2025-08-26T19:56:01.0355860Z Raises: 2025-08-26T19:56:01.0356014Z TypeError: if ``PRUNING_TYPE != 'unstructured'`` 2025-08-26T19:56:01.0356018Z 2025-08-26T19:56:01.0356115Z Note: 2025-08-26T19:56:01.0356336Z Since global structured pruning doesn't make much sense unless the 2025-08-26T19:56:01.0356550Z norm is normalized by the size of the parameter, we now limit the 2025-08-26T19:56:01.0356705Z scope of global pruning to unstructured methods. 2025-08-26T19:56:01.0356710Z 2025-08-26T19:56:01.0356798Z Examples: 2025-08-26T19:56:01.0356935Z >>> from torch.nn.utils import prune 2025-08-26T19:56:01.0357057Z >>> from collections import OrderedDict 2025-08-26T19:56:01.0357173Z >>> net = nn.Sequential( 2025-08-26T19:56:01.0357270Z ... OrderedDict( 2025-08-26T19:56:01.0357356Z ... [ 2025-08-26T19:56:01.0357487Z ... ("first", nn.Linear(10, 4)), 2025-08-26T19:56:01.0357606Z ... ("second", nn.Linear(4, 1)), 2025-08-26T19:56:01.0357730Z ... ] 2025-08-26T19:56:01.0357816Z ... ) 2025-08-26T19:56:01.0357901Z ... ) 2025-08-26T19:56:01.0358021Z >>> parameters_to_prune = ( 2025-08-26T19:56:01.0358125Z ... (net.first, "weight"), 2025-08-26T19:56:01.0358242Z ... (net.second, "weight"), 2025-08-26T19:56:01.0358324Z ... ) 2025-08-26T19:56:01.0358437Z >>> prune.global_unstructured( 2025-08-26T19:56:01.0358555Z ... parameters_to_prune, 2025-08-26T19:56:01.0358688Z ... pruning_method=prune.L1Unstructured, 2025-08-26T19:56:01.0358783Z ... amount=10, 2025-08-26T19:56:01.0358879Z ... ) 2025-08-26T19:56:01.0359106Z >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0)) 2025-08-26T19:56:01.0359207Z tensor(10) 2025-08-26T19:56:01.0359212Z 2025-08-26T19:56:01.0359216Z 2025-08-26T19:56:01.0359476Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.0359482Z 2025-08-26T19:56:01.0360038Z msg = Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1149. 2025-08-26T19:56:01.0360332Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.0360748Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``. 2025-08-26T19:56:01.0360752Z 2025-08-26T19:56:01.0360972Z Modifies module in place (and also return the modified module) by: 2025-08-26T19:56:01.0360977Z 2025-08-26T19:56:01.0361242Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T19:56:01.0361478Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T19:56:01.0361693Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T19:56:01.0361915Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T19:56:01.0362015Z ``name+'_orig'``. 2025-08-26T19:56:01.0362021Z 2025-08-26T19:56:01.0362105Z Args: 2025-08-26T19:56:01.0362300Z module (nn.Module): module containing the tensor to prune 2025-08-26T19:56:01.0362485Z name (str): parameter name within ``module`` on which pruning 2025-08-26T19:56:01.0362589Z will act. 2025-08-26T19:56:01.0362769Z mask (Tensor): binary mask to be applied to the parameter. 2025-08-26T19:56:01.0362773Z 2025-08-26T19:56:01.0362862Z Returns: 2025-08-26T19:56:01.0363094Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T19:56:01.0363102Z 2025-08-26T19:56:01.0363190Z Examples: 2025-08-26T19:56:01.0363323Z >>> from torch.nn.utils import prune 2025-08-26T19:56:01.0363434Z >>> m = prune.custom_from_mask( 2025-08-26T19:56:01.0363621Z ... nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0]) 2025-08-26T19:56:01.0363708Z ... ) 2025-08-26T19:56:01.0363812Z >>> print(m.bias_mask) 2025-08-26T19:56:01.0363922Z tensor([0., 1., 0.]) 2025-08-26T19:56:01.0363927Z 2025-08-26T19:56:01.0364009Z 2025-08-26T19:56:01.0364267Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.0364284Z 2025-08-26T19:56:01.0407063Z msg = Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py line=350. 2025-08-26T19:56:01.0407393Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.0407565Z Pad a packed batch of variable length sequences. 2025-08-26T19:56:01.0407570Z 2025-08-26T19:56:01.0407751Z It is an inverse operation to :func:`pack_padded_sequence`. 2025-08-26T19:56:01.0407755Z 2025-08-26T19:56:01.0408055Z The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``) 2025-08-26T19:56:01.0408303Z or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest 2025-08-26T19:56:01.0408487Z sequence and ``B`` is the batch size. 2025-08-26T19:56:01.0408492Z 2025-08-26T19:56:01.0408579Z Example: 2025-08-26T19:56:01.0408886Z >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence 2025-08-26T19:56:01.0409049Z >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]]) 2025-08-26T19:56:01.0409146Z >>> lens = [2, 1, 3] 2025-08-26T19:56:01.0409276Z >>> packed = pack_padded_sequence( 2025-08-26T19:56:01.0409431Z ... seq, lens, batch_first=True, enforce_sorted=False 2025-08-26T19:56:01.0409550Z ... ) 2025-08-26T19:56:01.0409636Z >>> packed 2025-08-26T19:56:01.0409886Z PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]), 2025-08-26T19:56:01.0410123Z sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0])) 2025-08-26T19:56:01.0410375Z >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True) 2025-08-26T19:56:01.0410517Z >>> seq_unpacked 2025-08-26T19:56:01.0410612Z tensor([[1, 2, 0], 2025-08-26T19:56:01.0410702Z [3, 0, 0], 2025-08-26T19:56:01.0410802Z [4, 5, 6]]) 2025-08-26T19:56:01.0410896Z >>> lens_unpacked 2025-08-26T19:56:01.0411001Z tensor([2, 1, 3]) 2025-08-26T19:56:01.0411005Z 2025-08-26T19:56:01.0411096Z .. note:: 2025-08-26T19:56:01.0411243Z :attr:`total_length` is useful to implement the 2025-08-26T19:56:01.0411482Z ``pack sequence -> recurrent network -> unpack sequence`` pattern in a 2025-08-26T19:56:01.0411771Z :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`. 2025-08-26T19:56:01.0412026Z See :ref:`this FAQ section ` for 2025-08-26T19:56:01.0412113Z details. 2025-08-26T19:56:01.0412118Z 2025-08-26T19:56:01.0412205Z Args: 2025-08-26T19:56:01.0412349Z sequence (PackedSequence): batch to pad 2025-08-26T19:56:01.0412595Z batch_first (bool, optional): if ``True``, the output will be in ``B x T x *`` 2025-08-26T19:56:01.0412730Z format, ``T x B x *`` otherwise. 2025-08-26T19:56:01.0412928Z padding_value (float, optional): values for padded elements. 2025-08-26T19:56:01.0413162Z total_length (int, optional): if not ``None``, the output will be padded to 2025-08-26T19:56:01.0413419Z have length :attr:`total_length`. This method will throw :class:`ValueError` 2025-08-26T19:56:01.0413613Z if :attr:`total_length` is less than the max sequence length in 2025-08-26T19:56:01.0413733Z :attr:`sequence`. 2025-08-26T19:56:01.0413738Z 2025-08-26T19:56:01.0413833Z Returns: 2025-08-26T19:56:01.0414030Z Tuple of Tensor containing the padded sequence, and a Tensor 2025-08-26T19:56:01.0414245Z containing the list of lengths of each sequence in the batch. 2025-08-26T19:56:01.0414479Z Batch elements will be re-ordered as they were ordered originally when 2025-08-26T19:56:01.0414720Z the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``. 2025-08-26T19:56:01.0414808Z 2025-08-26T19:56:01.0415070Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.0415074Z 2025-08-26T19:56:01.1092355Z msg = Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=808. 2025-08-26T19:56:01.1092670Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.1093022Z Contains a list of schedulers expected to be called sequentially during the optimization process. 2025-08-26T19:56:01.1093030Z 2025-08-26T19:56:01.1093411Z Specifically, the schedulers will be called according to the milestone points, which should provide exact 2025-08-26T19:56:01.1093649Z intervals by which each scheduler should be called at a given epoch. 2025-08-26T19:56:01.1093792Z 2025-08-26T19:56:01.1093880Z Args: 2025-08-26T19:56:01.1094034Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:01.1094185Z schedulers (list): List of chained schedulers. 2025-08-26T19:56:01.1094404Z milestones (list): List of integers that reflects milestone points. 2025-08-26T19:56:01.1094592Z last_epoch (int): The index of last epoch. Default: -1. 2025-08-26T19:56:01.1094596Z 2025-08-26T19:56:01.1094683Z Example: 2025-08-26T19:56:01.1094799Z >>> # xdoctest: +SKIP 2025-08-26T19:56:01.1094957Z >>> # Assuming optimizer uses lr = 0.05 for all groups 2025-08-26T19:56:01.1095070Z >>> # lr = 0.005 if epoch == 0 2025-08-26T19:56:01.1095190Z >>> # lr = 0.005 if epoch == 1 2025-08-26T19:56:01.1095293Z >>> # lr = 0.005 if epoch == 2 2025-08-26T19:56:01.1095392Z >>> # ... 2025-08-26T19:56:01.1095498Z >>> # lr = 0.05 if epoch == 20 2025-08-26T19:56:01.1095621Z >>> # lr = 0.045 if epoch == 21 2025-08-26T19:56:01.1095782Z >>> # lr = 0.0405 if epoch == 22 2025-08-26T19:56:01.1095989Z >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20) 2025-08-26T19:56:01.1096166Z >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9) 2025-08-26T19:56:01.1096279Z >>> scheduler = SequentialLR( 2025-08-26T19:56:01.1096375Z ... optimizer, 2025-08-26T19:56:01.1096526Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T19:56:01.1096627Z ... milestones=[20], 2025-08-26T19:56:01.1096732Z ... ) 2025-08-26T19:56:01.1096926Z >>> for epoch in range(100): 2025-08-26T19:56:01.1097020Z >>> train(...) 2025-08-26T19:56:01.1097132Z >>> validate(...) 2025-08-26T19:56:01.1097236Z >>> scheduler.step() 2025-08-26T19:56:01.1097240Z 2025-08-26T19:56:01.1097447Z .. image:: ../scripts/lr_scheduler_images/SequentialLR.png 2025-08-26T19:56:01.1097534Z 2025-08-26T19:56:01.1097798Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.1097805Z 2025-08-26T19:56:01.1127801Z msg = Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1233. 2025-08-26T19:56:01.1128091Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:01.1128294Z Reduce learning rate when a metric has stopped improving. 2025-08-26T19:56:01.1128299Z 2025-08-26T19:56:01.1128509Z Models often benefit from reducing the learning rate by a factor 2025-08-26T19:56:01.1128722Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-08-26T19:56:01.1128998Z quantity and if no improvement is seen for a 'patience' number 2025-08-26T19:56:01.1129127Z of epochs, the learning rate is reduced. 2025-08-26T19:56:01.1129146Z 2025-08-26T19:56:01.1129235Z Args: 2025-08-26T19:56:01.1129375Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:01.1129556Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-08-26T19:56:01.1129720Z be reduced when the quantity monitored has stopped 2025-08-26T19:56:01.1129890Z decreasing; in `max` mode it will be reduced when the 2025-08-26T19:56:01.1130103Z quantity monitored has stopped increasing. Default: 'min'. 2025-08-26T19:56:01.1130281Z factor (float): Factor by which the learning rate will be 2025-08-26T19:56:01.1130441Z reduced. new_lr = lr * factor. Default: 0.1. 2025-08-26T19:56:01.1130670Z patience (int): The number of allowed epochs with no improvement after 2025-08-26T19:56:01.1130818Z which the learning rate will be reduced. 2025-08-26T19:56:01.1131052Z For example, consider the case of having no patience (`patience = 0`). 2025-08-26T19:56:01.1131429Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-08-26T19:56:01.1131716Z In the second epoch, if the performance is worse than the baseline, 2025-08-26T19:56:01.1131877Z we have what is considered an intolerable epoch. 2025-08-26T19:56:01.1132164Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-08-26T19:56:01.1132337Z the learning rate is reduced at the end of this epoch. 2025-08-26T19:56:01.1132672Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-08-26T19:56:01.1133033Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-08-26T19:56:01.1133161Z the learning rate is not adjusted. 2025-08-26T19:56:01.1133269Z Default: 10. 2025-08-26T19:56:01.1133463Z threshold (float): Threshold for measuring the new optimum, 2025-08-26T19:56:01.1133637Z to only focus on significant changes. Default: 1e-4. 2025-08-26T19:56:01.1133815Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-08-26T19:56:01.1134013Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-08-26T19:56:01.1134172Z mode or best * ( 1 - threshold ) in `min` mode. 2025-08-26T19:56:01.1134332Z In `abs` mode, dynamic_threshold = best + threshold in 2025-08-26T19:56:01.1134526Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-08-26T19:56:01.1134702Z cooldown (int): Number of epochs to wait before resuming 2025-08-26T19:56:01.1134939Z normal operation after lr has been reduced. Default: 0. 2025-08-26T19:56:01.1135119Z min_lr (float or list): A scalar or a list of scalars. A 2025-08-26T19:56:01.1135285Z lower bound on the learning rate of all param groups 2025-08-26T19:56:01.1135428Z or each group respectively. Default: 0. 2025-08-26T19:56:01.1135609Z eps (float): Minimal decay applied to lr. If the difference 2025-08-26T19:56:01.1135791Z between new and old lr is smaller than eps, the update is 2025-08-26T19:56:01.1135913Z ignored. Default: 1e-8. 2025-08-26T19:56:01.1135917Z 2025-08-26T19:56:01.1136007Z Example: 2025-08-26T19:56:01.1136150Z >>> # xdoctest: +SKIP 2025-08-26T19:56:01.1136530Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T19:56:01.1136750Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-08-26T19:56:01.1136904Z >>> for epoch in range(10): 2025-08-26T19:56:01.1137041Z >>> train(...) 2025-08-26T19:56:01.1137191Z >>> val_loss = validate(...) 2025-08-26T19:56:01.1137590Z >>> # Note that step should be called after validate() 2025-08-26T19:56:01.1137783Z >>> scheduler.step(val_loss) 2025-08-26T19:56:01.1137789Z 2025-08-26T19:56:01.1138100Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-08-26T19:56:01.1138261Z 2025-08-26T19:56:01.1139000Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-08-26T19:56:01.1139009Z 2025-08-26T19:56:01.1139117Z scheduler.step(val_loss) 2025-08-26T19:56:01.1139217Z ^ 2025-08-26T19:56:01.1139775Z msg = Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1430. 2025-08-26T19:56:01.1140055Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.1140389Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR). 2025-08-26T19:56:01.1140394Z 2025-08-26T19:56:01.1140696Z The policy cycles the learning rate between two boundaries with a constant frequency, 2025-08-26T19:56:01.1140959Z as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_. 2025-08-26T19:56:01.1141194Z The distance between the two boundaries can be scaled on a per-iteration 2025-08-26T19:56:01.1141391Z or per-cycle basis. 2025-08-26T19:56:01.1141398Z 2025-08-26T19:56:01.1141649Z Cyclical learning rate policy changes the learning rate after every batch. 2025-08-26T19:56:01.1141863Z `step` should be called after a batch has been used for training. 2025-08-26T19:56:01.1141867Z 2025-08-26T19:56:01.1142080Z This class has three built-in policies, as put forth in the paper: 2025-08-26T19:56:01.1142085Z 2025-08-26T19:56:01.1142309Z * "triangular": A basic triangular cycle without amplitude scaling. 2025-08-26T19:56:01.1142619Z * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle. 2025-08-26T19:56:01.1142956Z * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}` 2025-08-26T19:56:01.1143079Z at each cycle iteration. 2025-08-26T19:56:01.1143084Z 2025-08-26T19:56:01.1143330Z This implementation was adapted from the github repo: `bckenstler/CLR`_ 2025-08-26T19:56:01.1143336Z 2025-08-26T19:56:01.1143440Z Args: 2025-08-26T19:56:01.1143618Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:01.1143802Z base_lr (float or list): Initial learning rate which is the 2025-08-26T19:56:01.1143990Z lower boundary in the cycle for each parameter group. 2025-08-26T19:56:01.1144194Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T19:56:01.1144342Z for each parameter group. Functionally, 2025-08-26T19:56:01.1144599Z it defines the cycle amplitude (max_lr - base_lr). 2025-08-26T19:56:01.1144822Z The lr at any cycle is the sum of base_lr 2025-08-26T19:56:01.1145060Z and some scaling of the amplitude; therefore 2025-08-26T19:56:01.1145228Z max_lr may not actually be reached depending on 2025-08-26T19:56:01.1145392Z scaling function. 2025-08-26T19:56:01.1145666Z step_size_up (int): Number of training iterations in the 2025-08-26T19:56:01.1145899Z increasing half of a cycle. Default: 2000 2025-08-26T19:56:01.1146272Z step_size_down (int): Number of training iterations in the 2025-08-26T19:56:01.1146583Z decreasing half of a cycle. If step_size_down is None, 2025-08-26T19:56:01.1146734Z it is set to step_size_up. Default: None 2025-08-26T19:56:01.1146902Z mode (str): One of {triangular, triangular2, exp_range}. 2025-08-26T19:56:01.1147052Z Values correspond to policies detailed above. 2025-08-26T19:56:01.1147218Z If scale_fn is not None, this argument is ignored. 2025-08-26T19:56:01.1147328Z Default: 'triangular' 2025-08-26T19:56:01.1147515Z gamma (float): Constant in 'exp_range' scaling function: 2025-08-26T19:56:01.1147624Z gamma**(cycle iterations) 2025-08-26T19:56:01.1147718Z Default: 1.0 2025-08-26T19:56:01.1147927Z scale_fn (function): Custom scaling policy defined by a single 2025-08-26T19:56:01.1148050Z argument lambda function, where 2025-08-26T19:56:01.1148185Z 0 <= scale_fn(x) <= 1 for all x >= 0. 2025-08-26T19:56:01.1148306Z If specified, then 'mode' is ignored. 2025-08-26T19:56:01.1148402Z Default: None 2025-08-26T19:56:01.1148543Z scale_mode (str): {'cycle', 'iterations'}. 2025-08-26T19:56:01.1148675Z Defines whether scale_fn is evaluated on 2025-08-26T19:56:01.1148825Z cycle number or cycle iterations (training 2025-08-26T19:56:01.1148947Z iterations since start of cycle). 2025-08-26T19:56:01.1149047Z Default: 'cycle' 2025-08-26T19:56:01.1149267Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T19:56:01.1149455Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T19:56:01.1149563Z Default: True 2025-08-26T19:56:01.1149786Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T19:56:01.1150037Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T19:56:01.1150219Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T19:56:01.1150364Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T19:56:01.1150474Z Default: 0.8 2025-08-26T19:56:01.1150693Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T19:56:01.1150828Z for each parameter group. Functionally, 2025-08-26T19:56:01.1151038Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T19:56:01.1151226Z The momentum at any cycle is the difference of max_momentum 2025-08-26T19:56:01.1151386Z and some scaling of the amplitude; therefore 2025-08-26T19:56:01.1151562Z base_momentum may not actually be reached depending on 2025-08-26T19:56:01.1151744Z scaling function. Note that momentum is cycled inversely 2025-08-26T19:56:01.1151978Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T19:56:01.1152143Z and learning rate is 'base_lr' 2025-08-26T19:56:01.1152252Z Default: 0.9 2025-08-26T19:56:01.1152480Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T19:56:01.1152701Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T19:56:01.1152932Z batch instead of after each epoch, this number represents the total 2025-08-26T19:56:01.1153215Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T19:56:01.1153425Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T19:56:01.1153520Z Default: -1 2025-08-26T19:56:01.1153525Z 2025-08-26T19:56:01.1153629Z Example: 2025-08-26T19:56:01.1153730Z >>> # xdoctest: +SKIP 2025-08-26T19:56:01.1153963Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T19:56:01.1154136Z >>> scheduler = torch.optim.lr_scheduler.CyclicLR( 2025-08-26T19:56:01.1154232Z ... optimizer, 2025-08-26T19:56:01.1154329Z ... base_lr=0.01, 2025-08-26T19:56:01.1154434Z ... max_lr=0.1, 2025-08-26T19:56:01.1154536Z ... step_size_up=10, 2025-08-26T19:56:01.1154636Z ... ) 2025-08-26T19:56:01.1154795Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T19:56:01.1154901Z >>> for epoch in range(10): 2025-08-26T19:56:01.1155025Z >>> for batch in data_loader: 2025-08-26T19:56:01.1155130Z >>> train_batch(...) 2025-08-26T19:56:01.1155252Z >>> scheduler.step() 2025-08-26T19:56:01.1155256Z 2025-08-26T19:56:01.1155422Z .. image:: ../scripts/lr_scheduler_images/CyclicLR.png 2025-08-26T19:56:01.1155427Z 2025-08-26T19:56:01.1155758Z .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186 2025-08-26T19:56:01.1155930Z .. _bckenstler/CLR: https://github.com/bckenstler/CLR 2025-08-26T19:56:01.1156015Z 2025-08-26T19:56:01.1156291Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.1156296Z 2025-08-26T19:56:01.1156971Z msg = Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1722. 2025-08-26T19:56:01.1157251Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.1157511Z Set the learning rate of each parameter group using a cosine annealing schedule. 2025-08-26T19:56:01.1157515Z 2025-08-26T19:56:01.1157707Z The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}` 2025-08-26T19:56:01.1167601Z is the number of epochs since the last restart and :math:`T_{i}` is the number 2025-08-26T19:56:01.1167747Z of epochs between two warm restarts in SGDR: 2025-08-26T19:56:01.1167754Z 2025-08-26T19:56:01.1167967Z .. math:: 2025-08-26T19:56:01.1168234Z \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + 2025-08-26T19:56:01.1168401Z \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right) 2025-08-26T19:56:01.1168407Z 2025-08-26T19:56:01.1168582Z When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`. 2025-08-26T19:56:01.1168848Z When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`. 2025-08-26T19:56:01.1168855Z 2025-08-26T19:56:01.1168980Z It has been proposed in 2025-08-26T19:56:01.1169160Z `SGDR: Stochastic Gradient Descent with Warm Restarts`_. 2025-08-26T19:56:01.1169171Z 2025-08-26T19:56:01.1169271Z Args: 2025-08-26T19:56:01.1169416Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:01.1169583Z T_0 (int): Number of iterations until the first restart. 2025-08-26T19:56:01.1169891Z T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1. 2025-08-26T19:56:01.1170085Z eta_min (float, optional): Minimum learning rate. Default: 0. 2025-08-26T19:56:01.1170365Z last_epoch (int, optional): The index of the last epoch. Default: -1. 2025-08-26T19:56:01.1170370Z 2025-08-26T19:56:01.1170546Z .. _SGDR\: Stochastic Gradient Descent with Warm Restarts: 2025-08-26T19:56:01.1170685Z https://arxiv.org/abs/1608.03983 2025-08-26T19:56:01.1170689Z 2025-08-26T19:56:01.1170782Z Example: 2025-08-26T19:56:01.1170884Z >>> # xdoctest: +SKIP 2025-08-26T19:56:01.1171090Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05) 2025-08-26T19:56:01.1171385Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( 2025-08-26T19:56:01.1171503Z ... optimizer, T_0=20 2025-08-26T19:56:01.1171589Z ... ) 2025-08-26T19:56:01.1171697Z >>> for epoch in range(100): 2025-08-26T19:56:01.1171806Z >>> train(...) 2025-08-26T19:56:01.1171904Z >>> validate(...) 2025-08-26T19:56:01.1172011Z >>> scheduler.step() 2025-08-26T19:56:01.1172032Z 2025-08-26T19:56:01.1172277Z .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png 2025-08-26T19:56:01.1172363Z 2025-08-26T19:56:01.1172637Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.1172642Z 2025-08-26T19:56:01.1173246Z msg = Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1872. 2025-08-26T19:56:01.1173514Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.1173828Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy. 2025-08-26T19:56:01.1173833Z 2025-08-26T19:56:01.1174150Z The 1cycle policy anneals the learning rate from an initial learning rate to some maximum 2025-08-26T19:56:01.1174452Z learning rate and then from that maximum learning rate to some minimum learning rate much 2025-08-26T19:56:01.1174592Z lower than the initial learning rate. 2025-08-26T19:56:01.1174824Z This policy was initially described in the paper `Super-Convergence: 2025-08-26T19:56:01.1175040Z Very Fast Training of Neural Networks Using Large Learning Rates`_. 2025-08-26T19:56:01.1175058Z 2025-08-26T19:56:01.1175308Z The 1cycle learning rate policy changes the learning rate after every batch. 2025-08-26T19:56:01.1175510Z `step` should be called after a batch has been used for training. 2025-08-26T19:56:01.1175514Z 2025-08-26T19:56:01.1175641Z This scheduler is not chainable. 2025-08-26T19:56:01.1175645Z 2025-08-26T19:56:01.1175895Z Note also that the total number of steps in the cycle can be determined in one 2025-08-26T19:56:01.1176047Z of two ways (listed in order of precedence): 2025-08-26T19:56:01.1176051Z 2025-08-26T19:56:01.1176204Z #. A value for total_steps is explicitly provided. 2025-08-26T19:56:01.1176392Z #. A number of epochs (epochs) and a number of steps per epoch 2025-08-26T19:56:01.1176549Z (steps_per_epoch) are provided. 2025-08-26T19:56:01.1176713Z In this case, the number of total steps is inferred by 2025-08-26T19:56:01.1176851Z total_steps = epochs * steps_per_epoch 2025-08-26T19:56:01.1176855Z 2025-08-26T19:56:01.1177098Z You must either provide a value for total_steps or provide a value for both 2025-08-26T19:56:01.1177206Z epochs and steps_per_epoch. 2025-08-26T19:56:01.1177223Z 2025-08-26T19:56:01.1177536Z The default behaviour of this scheduler follows the fastai implementation of 1cycle, which 2025-08-26T19:56:01.1177845Z claims that "unpublished work has shown even better results by using only two phases". To 2025-08-26T19:56:01.1178105Z mimic the behaviour of the original paper instead, set ``three_phase=True``. 2025-08-26T19:56:01.1178109Z 2025-08-26T19:56:01.1178196Z Args: 2025-08-26T19:56:01.1178346Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:01.1178549Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T19:56:01.1178694Z for each parameter group. 2025-08-26T19:56:01.1178918Z total_steps (int): The total number of steps in the cycle. Note that 2025-08-26T19:56:01.1179135Z if a value is not provided here, then it must be inferred by providing 2025-08-26T19:56:01.1179280Z a value for epochs and steps_per_epoch. 2025-08-26T19:56:01.1179376Z Default: None 2025-08-26T19:56:01.1179581Z epochs (int): The number of epochs to train for. This is used along 2025-08-26T19:56:01.1179891Z with steps_per_epoch in order to infer the total number of steps in the cycle 2025-08-26T19:56:01.1180032Z if a value for total_steps is not provided. 2025-08-26T19:56:01.1180144Z Default: None 2025-08-26T19:56:01.1180375Z steps_per_epoch (int): The number of steps per epoch to train for. This is 2025-08-26T19:56:01.1180608Z used along with epochs in order to infer the total number of steps in the 2025-08-26T19:56:01.1180779Z cycle if a value for total_steps is not provided. 2025-08-26T19:56:01.1180878Z Default: None 2025-08-26T19:56:01.1181125Z pct_start (float): The percentage of the cycle (in number of steps) spent 2025-08-26T19:56:01.1181243Z increasing the learning rate. 2025-08-26T19:56:01.1181339Z Default: 0.3 2025-08-26T19:56:01.1181480Z anneal_strategy (str): {'cos', 'linear'} 2025-08-26T19:56:01.1181733Z Specifies the annealing strategy: "cos" for cosine annealing, "linear" for 2025-08-26T19:56:01.1181850Z linear annealing. 2025-08-26T19:56:01.1181948Z Default: 'cos' 2025-08-26T19:56:01.1182156Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T19:56:01.1182359Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T19:56:01.1182456Z Default: True 2025-08-26T19:56:01.1182695Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T19:56:01.1182905Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T19:56:01.1183074Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T19:56:01.1183236Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T19:56:01.1183331Z Default: 0.85 2025-08-26T19:56:01.1183562Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T19:56:01.1183694Z for each parameter group. Functionally, 2025-08-26T19:56:01.1183896Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T19:56:01.1184036Z Note that momentum is cycled inversely 2025-08-26T19:56:01.1184250Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T19:56:01.1184376Z and learning rate is 'base_lr' 2025-08-26T19:56:01.1184472Z Default: 0.95 2025-08-26T19:56:01.1184688Z div_factor (float): Determines the initial learning rate via 2025-08-26T19:56:01.1184820Z initial_lr = max_lr/div_factor 2025-08-26T19:56:01.1184911Z Default: 25 2025-08-26T19:56:01.1185136Z final_div_factor (float): Determines the minimum learning rate via 2025-08-26T19:56:01.1185254Z min_lr = initial_lr/final_div_factor 2025-08-26T19:56:01.1185343Z Default: 1e4 2025-08-26T19:56:01.1185613Z three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the 2025-08-26T19:56:01.1185877Z learning rate according to 'final_div_factor' instead of modifying the second 2025-08-26T19:56:01.1186133Z phase (the first two phases will be symmetrical about the step indicated by 2025-08-26T19:56:01.1186230Z 'pct_start'). 2025-08-26T19:56:01.1186458Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T19:56:01.1186694Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T19:56:01.1186943Z batch instead of after each epoch, this number represents the total 2025-08-26T19:56:01.1187184Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T19:56:01.1187381Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T19:56:01.1187480Z Default: -1 2025-08-26T19:56:01.1187497Z 2025-08-26T19:56:01.1187586Z Example: 2025-08-26T19:56:01.1187689Z >>> # xdoctest: +SKIP 2025-08-26T19:56:01.1187908Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T19:56:01.1188147Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) 2025-08-26T19:56:01.1188324Z >>> scheduler = torch.optim.lr_scheduler.OneCycleLR( 2025-08-26T19:56:01.1188540Z ... optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10 2025-08-26T19:56:01.1188627Z ... ) 2025-08-26T19:56:01.1188748Z >>> for epoch in range(10): 2025-08-26T19:56:01.1188861Z >>> for batch in data_loader: 2025-08-26T19:56:01.1188962Z >>> train_batch(...) 2025-08-26T19:56:01.1189078Z >>> optimizer.step() 2025-08-26T19:56:01.1189181Z >>> scheduler.step() 2025-08-26T19:56:01.1189185Z 2025-08-26T19:56:01.1189368Z .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png 2025-08-26T19:56:01.1189372Z 2025-08-26T19:56:01.1189673Z .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates: 2025-08-26T19:56:01.1189810Z https://arxiv.org/abs/1708.07120 2025-08-26T19:56:01.1189891Z 2025-08-26T19:56:01.1190153Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.1190158Z 2025-08-26T19:56:01.1295538Z msg = Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/optimizer.py line=867. 2025-08-26T19:56:01.1295814Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.1295937Z Load the optimizer state. 2025-08-26T19:56:01.1295942Z 2025-08-26T19:56:01.1296029Z Args: 2025-08-26T19:56:01.1296249Z state_dict (dict): optimizer state. Should be an object returned 2025-08-26T19:56:01.1296373Z from a call to :meth:`state_dict`. 2025-08-26T19:56:01.1296377Z 2025-08-26T19:56:01.1296479Z .. warning:: 2025-08-26T19:56:01.1296839Z Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`, 2025-08-26T19:56:01.1297054Z as calling it beforehand will overwrite the loaded learning rates. 2025-08-26T19:56:01.1297058Z 2025-08-26T19:56:01.1297160Z .. note:: 2025-08-26T19:56:01.1297458Z The names of the parameters (if they exist under the "param_names" key of each param group 2025-08-26T19:56:01.1297649Z in :meth:`state_dict`) will not affect the loading process. 2025-08-26T19:56:01.1298105Z To use the parameters' names for custom cases (such as when the parameters in the loaded state dict 2025-08-26T19:56:01.1298267Z differ from those initialized in the optimizer), 2025-08-26T19:56:01.1298594Z a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict 2025-08-26T19:56:01.1298693Z accordingly. 2025-08-26T19:56:01.1299007Z If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override 2025-08-26T19:56:01.1299335Z the current names, if present, in the optimizer state. If they do not exist in loaded state dict, 2025-08-26T19:56:01.1299531Z the optimizer ``param_names`` will remain unchanged. 2025-08-26T19:56:01.1299536Z 2025-08-26T19:56:01.1299627Z Example: 2025-08-26T19:56:01.1299730Z >>> # xdoctest: +SKIP 2025-08-26T19:56:01.1299864Z >>> model = torch.nn.Linear(10, 10) 2025-08-26T19:56:01.1300082Z >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4) 2025-08-26T19:56:01.1300257Z >>> scheduler1 = torch.optim.lr_scheduler.LinearLR( 2025-08-26T19:56:01.1300352Z ... optim, 2025-08-26T19:56:01.1300457Z ... start_factor=0.1, 2025-08-26T19:56:01.1300569Z ... end_factor=1, 2025-08-26T19:56:01.1300670Z ... total_iters=20, 2025-08-26T19:56:01.1300755Z ... ) 2025-08-26T19:56:01.1300962Z >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR( 2025-08-26T19:56:01.1301136Z ... optim, 2025-08-26T19:56:01.1301246Z ... T_max=80, 2025-08-26T19:56:01.1301344Z ... eta_min=3e-5, 2025-08-26T19:56:01.1301432Z ... ) 2025-08-26T19:56:01.1301594Z >>> lr = torch.optim.lr_scheduler.SequentialLR( 2025-08-26T19:56:01.1301684Z ... optim, 2025-08-26T19:56:01.1301838Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T19:56:01.1301943Z ... milestones=[20], 2025-08-26T19:56:01.1302028Z ... ) 2025-08-26T19:56:01.1302192Z >>> lr.load_state_dict(torch.load("./save_seq.pt")) 2025-08-26T19:56:01.1302399Z >>> # now load the optimizer checkpoint after loading the LRScheduler 2025-08-26T19:56:01.1302582Z >>> optim.load_state_dict(torch.load("./save_optim.pt")) 2025-08-26T19:56:01.1302587Z 2025-08-26T19:56:01.1302670Z 2025-08-26T19:56:01.1302928Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.1302936Z 2025-08-26T19:56:01.1463399Z msg = Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=120. 2025-08-26T19:56:01.1463666Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.1464050Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA). 2025-08-26T19:56:01.1464061Z 2025-08-26T19:56:01.1464308Z Stochastic Weight Averaging was proposed in `Averaging Weights Leads to 2025-08-26T19:56:01.1464546Z Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii 2025-08-26T19:56:01.1464773Z Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson 2025-08-26T19:56:01.1464863Z (UAI 2018). 2025-08-26T19:56:01.1464880Z 2025-08-26T19:56:01.1465101Z Exponential Moving Average is a variation of `Polyak averaging`_, 2025-08-26T19:56:01.1465387Z but using exponential weights instead of equal weights across iterations. 2025-08-26T19:56:01.1465392Z 2025-08-26T19:56:01.1465636Z AveragedModel class creates a copy of the provided module :attr:`model` 2025-08-26T19:56:01.1465865Z on the device :attr:`device` and allows to compute running averages of the 2025-08-26T19:56:01.1465989Z parameters of the :attr:`model`. 2025-08-26T19:56:01.1465993Z 2025-08-26T19:56:01.1466147Z Args: 2025-08-26T19:56:01.1466320Z model (torch.nn.Module): model to use with SWA/EMA 2025-08-26T19:56:01.1466562Z device (torch.device, optional): if provided, the averaged model will be 2025-08-26T19:56:01.1466684Z stored on the :attr:`device` 2025-08-26T19:56:01.1466893Z avg_fn (function, optional): the averaging function used to update 2025-08-26T19:56:01.1467098Z parameters; the function must take in the current value of the 2025-08-26T19:56:01.1467336Z :class:`AveragedModel` parameter, the current value of :attr:`model` 2025-08-26T19:56:01.1467540Z parameter, and the number of models already averaged; if None, 2025-08-26T19:56:01.1467716Z an equally weighted average is used (default: None) 2025-08-26T19:56:01.1467948Z multi_avg_fn (function, optional): the averaging function used to update 2025-08-26T19:56:01.1468191Z parameters inplace; the function must take in the current values of the 2025-08-26T19:56:01.1468477Z :class:`AveragedModel` parameters as a list, the current values of :attr:`model` 2025-08-26T19:56:01.1468749Z parameters as a list, and the number of models already averaged; if None, 2025-08-26T19:56:01.1468925Z an equally weighted average is used (default: None) 2025-08-26T19:56:01.1469134Z use_buffers (bool): if ``True``, it will compute running averages for 2025-08-26T19:56:01.1469363Z both the parameters and the buffers of the model. (default: ``False``) 2025-08-26T19:56:01.1469380Z 2025-08-26T19:56:01.1469468Z Example: 2025-08-26T19:56:01.1469667Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:01.1469811Z >>> loader, optimizer, model, loss_fn = ... 2025-08-26T19:56:01.1469987Z >>> swa_model = torch.optim.swa_utils.AveragedModel(model) 2025-08-26T19:56:01.1470220Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, 2025-08-26T19:56:01.1470346Z >>> T_max=300) 2025-08-26T19:56:01.1470453Z >>> swa_start = 160 2025-08-26T19:56:01.1470613Z >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05) 2025-08-26T19:56:01.1470717Z >>> for i in range(300): 2025-08-26T19:56:01.1470836Z >>> for input, target in loader: 2025-08-26T19:56:01.1470965Z >>> optimizer.zero_grad() 2025-08-26T19:56:01.1471103Z >>> loss_fn(model(input), target).backward() 2025-08-26T19:56:01.1471225Z >>> optimizer.step() 2025-08-26T19:56:01.1471322Z >>> if i > swa_start: 2025-08-26T19:56:01.1471457Z >>> swa_model.update_parameters(model) 2025-08-26T19:56:01.1471584Z >>> swa_scheduler.step() 2025-08-26T19:56:01.1471672Z >>> else: 2025-08-26T19:56:01.1471792Z >>> scheduler.step() 2025-08-26T19:56:01.1471876Z >>> 2025-08-26T19:56:01.1472034Z >>> # Update bn statistics for the swa_model at the end 2025-08-26T19:56:01.1472215Z >>> torch.optim.swa_utils.update_bn(loader, swa_model) 2025-08-26T19:56:01.1472222Z 2025-08-26T19:56:01.1472547Z You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters. 2025-08-26T19:56:01.1472861Z If no averaging function is provided, the default is to compute 2025-08-26T19:56:01.1473042Z equally-weighted average of the weights (SWA). 2025-08-26T19:56:01.1473048Z 2025-08-26T19:56:01.1473174Z Example: 2025-08-26T19:56:01.1473325Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:01.1473541Z >>> # Compute exponential moving averages of the weights and buffers 2025-08-26T19:56:01.1473730Z >>> ema_model = torch.optim.swa_utils.AveragedModel(model, 2025-08-26T19:56:01.1473950Z >>> torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True) 2025-08-26T19:56:01.1473954Z 2025-08-26T19:56:01.1474060Z .. note:: 2025-08-26T19:56:01.1474322Z When using SWA/EMA with models containing Batch Normalization you may 2025-08-26T19:56:01.1474533Z need to update the activation statistics for Batch Normalization. 2025-08-26T19:56:01.1474783Z This can be done either by using the :meth:`torch.optim.swa_utils.update_bn` 2025-08-26T19:56:01.1475010Z or by setting :attr:`use_buffers` to `True`. The first approach updates the 2025-08-26T19:56:01.1475270Z statistics in a post-training step by passing data through the model. The 2025-08-26T19:56:01.1475513Z second does it during the parameter update phase by averaging all buffers. 2025-08-26T19:56:01.1475768Z Empirical evidence has shown that updating the statistics in normalization 2025-08-26T19:56:01.1476018Z layers increases accuracy, but you may wish to empirically test which 2025-08-26T19:56:01.1476176Z approach yields the best results in your problem. 2025-08-26T19:56:01.1476181Z 2025-08-26T19:56:01.1476285Z .. note:: 2025-08-26T19:56:01.1476546Z :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model. 2025-08-26T19:56:01.1476580Z 2025-08-26T19:56:01.1476681Z .. note:: 2025-08-26T19:56:01.1476888Z When :meth:`update_parameters` is called for the first time (i.e. 2025-08-26T19:56:01.1477075Z :attr:`n_averaged` is `0`) the parameters of `model` are copied 2025-08-26T19:56:01.1477293Z to the parameters of :class:`AveragedModel`. For every subsequent 2025-08-26T19:56:01.1477485Z call of :meth:`update_parameters` the function `avg_fn` is used 2025-08-26T19:56:01.1477660Z to update the parameters. 2025-08-26T19:56:01.1477665Z 2025-08-26T19:56:01.1477893Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T19:56:01.1478021Z https://arxiv.org/abs/1803.05407 2025-08-26T19:56:01.1478274Z .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should 2025-08-26T19:56:01.1478360Z Average: 2025-08-26T19:56:01.1478491Z https://arxiv.org/abs/1806.05594 2025-08-26T19:56:01.1478697Z .. _SWALP: Stochastic Weight Averaging in Low-Precision Training: 2025-08-26T19:56:01.1478812Z https://arxiv.org/abs/1904.11943 2025-08-26T19:56:01.1479054Z .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That 2025-08-26T19:56:01.1479154Z Generalizes Well: 2025-08-26T19:56:01.1479282Z https://arxiv.org/abs/2001.02312 2025-08-26T19:56:01.1479379Z .. _Polyak averaging: 2025-08-26T19:56:01.1479549Z https://paperswithcode.com/method/polyak-averaging 2025-08-26T19:56:01.1479647Z 2025-08-26T19:56:01.1479907Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.1479913Z 2025-08-26T19:56:01.1480438Z msg = Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=375. 2025-08-26T19:56:01.1480707Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.1480938Z Anneals the learning rate in each parameter group to a fixed value. 2025-08-26T19:56:01.1480945Z 2025-08-26T19:56:01.1481180Z This learning rate scheduler is meant to be used with Stochastic Weight 2025-08-26T19:56:01.1481396Z Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`). 2025-08-26T19:56:01.1481412Z 2025-08-26T19:56:01.1481498Z Args: 2025-08-26T19:56:01.1481674Z optimizer (torch.optim.Optimizer): wrapped optimizer 2025-08-26T19:56:01.1481895Z swa_lrs (float or list): the learning rate value for all param groups 2025-08-26T19:56:01.1482027Z together or separately for each group. 2025-08-26T19:56:01.1482234Z annealing_epochs (int): number of epochs in the annealing phase 2025-08-26T19:56:01.1482345Z (default: 10) 2025-08-26T19:56:01.1482565Z annealing_strategy (str): "cos" or "linear"; specifies the annealing 2025-08-26T19:56:01.1482789Z strategy: "cos" for cosine annealing, "linear" for linear annealing 2025-08-26T19:56:01.1482919Z (default: "cos") 2025-08-26T19:56:01.1483102Z last_epoch (int): the index of the last epoch (default: -1) 2025-08-26T19:56:01.1483122Z 2025-08-26T19:56:01.1483304Z The :class:`SWALR` scheduler can be used together with other 2025-08-26T19:56:01.1483526Z schedulers to switch to a constant learning rate late in the training 2025-08-26T19:56:01.1483643Z as in the example below. 2025-08-26T19:56:01.1483647Z 2025-08-26T19:56:01.1483735Z Example: 2025-08-26T19:56:01.1483882Z >>> # xdoctest: +SKIP("Undefined variables") 2025-08-26T19:56:01.1484001Z >>> loader, optimizer, model = ... 2025-08-26T19:56:01.1484116Z >>> lr_lambda = lambda epoch: 0.9 2025-08-26T19:56:01.1484353Z >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer, 2025-08-26T19:56:01.1484463Z >>> lr_lambda=lr_lambda) 2025-08-26T19:56:01.1484650Z >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer, 2025-08-26T19:56:01.1484859Z >>> anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05) 2025-08-26T19:56:01.1484957Z >>> swa_start = 160 2025-08-26T19:56:01.1485073Z >>> for i in range(300): 2025-08-26T19:56:01.1485189Z >>> for input, target in loader: 2025-08-26T19:56:01.1485314Z >>> optimizer.zero_grad() 2025-08-26T19:56:01.1485451Z >>> loss_fn(model(input), target).backward() 2025-08-26T19:56:01.1485560Z >>> optimizer.step() 2025-08-26T19:56:01.1485673Z >>> if i > swa_start: 2025-08-26T19:56:01.1485833Z >>> swa_scheduler.step() 2025-08-26T19:56:01.1485922Z >>> else: 2025-08-26T19:56:01.1486043Z >>> scheduler.step() 2025-08-26T19:56:01.1486047Z 2025-08-26T19:56:01.1486276Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T19:56:01.1486406Z https://arxiv.org/abs/1803.05407 2025-08-26T19:56:01.1486493Z 2025-08-26T19:56:01.1486763Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.1486768Z 2025-08-26T19:56:01.6352490Z msg = Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_comparison.py line=1331. 2025-08-26T19:56:01.6353621Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:01.6354178Z Asserts that ``actual`` and ``expected`` are close. 2025-08-26T19:56:01.6354463Z 2025-08-26T19:56:01.6354860Z If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if 2025-08-26T19:56:01.6355352Z 2025-08-26T19:56:01.6355468Z .. math:: 2025-08-26T19:56:01.6355601Z 2025-08-26T19:56:01.6355992Z \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert 2025-08-26T19:56:01.6356485Z 2025-08-26T19:56:01.6356837Z Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are 2025-08-26T19:56:01.6357540Z only considered equal to each other if ``equal_nan`` is ``True``. 2025-08-26T19:56:01.6357876Z 2025-08-26T19:56:01.6358079Z In addition, they are only considered close if they have the same 2025-08-26T19:56:01.6358413Z 2025-08-26T19:56:01.6358609Z - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``), 2025-08-26T19:56:01.6359063Z - ``dtype`` (if ``check_dtype`` is ``True``), 2025-08-26T19:56:01.6359449Z - ``layout`` (if ``check_layout`` is ``True``), and 2025-08-26T19:56:01.6359841Z - stride (if ``check_stride`` is ``True``). 2025-08-26T19:56:01.6360092Z 2025-08-26T19:56:01.6360400Z If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed. 2025-08-26T19:56:01.6360824Z 2025-08-26T19:56:01.6361204Z If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are 2025-08-26T19:56:01.6362239Z checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR, 2025-08-26T19:56:01.6362968Z or ``ccol_indices`` and ``row_indices`` for CSC and BSC layouts, respectively, 2025-08-26T19:56:01.6363725Z are always checked for equality whereas the values are checked for closeness according to the definition above. 2025-08-26T19:56:01.6364256Z 2025-08-26T19:56:01.6364544Z If ``actual`` and ``expected`` are quantized, they are considered close if they have the same 2025-08-26T19:56:01.6365325Z :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the 2025-08-26T19:56:01.6365913Z definition above. 2025-08-26T19:56:01.6366075Z 2025-08-26T19:56:01.6366399Z ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which 2025-08-26T19:56:01.6367214Z :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types 2025-08-26T19:56:01.6368170Z have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s 2025-08-26T19:56:01.6369121Z or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all 2025-08-26T19:56:01.6369873Z their elements are considered close according to the above definition. 2025-08-26T19:56:01.6370231Z 2025-08-26T19:56:01.6370338Z .. note:: 2025-08-26T19:56:01.6370471Z 2025-08-26T19:56:01.6370915Z Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e. 2025-08-26T19:56:01.6371721Z :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus, 2025-08-26T19:56:01.6372464Z Python scalars of different types can be checked, but require ``check_dtype=False``. 2025-08-26T19:56:01.6372867Z 2025-08-26T19:56:01.6372969Z Args: 2025-08-26T19:56:01.6373208Z actual (Any): Actual input. 2025-08-26T19:56:01.6373532Z expected (Any): Expected input. 2025-08-26T19:56:01.6374128Z allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types 2025-08-26T19:56:01.6374781Z are allowed. Otherwise type equality is required. 2025-08-26T19:56:01.6375443Z rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default 2025-08-26T19:56:01.6376199Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T19:56:01.6376969Z atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default 2025-08-26T19:56:01.6377731Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T19:56:01.6378383Z equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal. 2025-08-26T19:56:01.6379066Z check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same 2025-08-26T19:56:01.6379733Z :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different 2025-08-26T19:56:01.6380358Z :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared. 2025-08-26T19:56:01.6381091Z check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this 2025-08-26T19:56:01.6381933Z check is disabled, tensors with different ``dtype``'s are promoted to a common ``dtype`` (according to 2025-08-26T19:56:01.6382582Z :func:`torch.promote_types`) before being compared. 2025-08-26T19:56:01.6383221Z check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this 2025-08-26T19:56:01.6384055Z check is disabled, tensors with different ``layout``'s are converted to strided tensors before being 2025-08-26T19:56:01.6384655Z compared. 2025-08-26T19:56:01.6385190Z check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride. 2025-08-26T19:56:01.6386053Z msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during 2025-08-26T19:56:01.6386892Z the comparison. Can also passed as callable in which case it will be called with the generated message and 2025-08-26T19:56:01.6387503Z should return the new message. 2025-08-26T19:56:01.6387748Z 2025-08-26T19:56:01.6387835Z Raises: 2025-08-26T19:56:01.6388210Z ValueError: If no :class:`torch.Tensor` can be constructed from an input. 2025-08-26T19:56:01.6388745Z ValueError: If only ``rtol`` or ``atol`` is specified. 2025-08-26T19:56:01.6389359Z AssertionError: If corresponding inputs are not Python scalars and are not directly related. 2025-08-26T19:56:01.6390199Z AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have 2025-08-26T19:56:01.6390832Z different types. 2025-08-26T19:56:01.6391401Z AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match. 2025-08-26T19:56:01.6392266Z AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match. 2025-08-26T19:56:01.6393093Z AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`. 2025-08-26T19:56:01.6393923Z AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same 2025-08-26T19:56:01.6394478Z :attr:`~torch.Tensor.layout`. 2025-08-26T19:56:01.6394939Z AssertionError: If only one of corresponding tensors is quantized. 2025-08-26T19:56:01.6395676Z AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s. 2025-08-26T19:56:01.6396509Z AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same 2025-08-26T19:56:01.6397061Z :attr:`~torch.Tensor.device`. 2025-08-26T19:56:01.6397637Z AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``. 2025-08-26T19:56:01.6398463Z AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride. 2025-08-26T19:56:01.6399348Z AssertionError: If the values of corresponding tensors are not close according to the definition above. 2025-08-26T19:56:01.6399855Z 2025-08-26T19:56:01.6400229Z The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching 2025-08-26T19:56:01.6400880Z ``dtype``'s, the maximum of both tolerances is used. 2025-08-26T19:56:01.6401146Z 2025-08-26T19:56:01.6401293Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6401670Z | ``dtype`` | ``rtol`` | ``atol`` | 2025-08-26T19:56:01.6402035Z +===========================+============+==========+ 2025-08-26T19:56:01.6402412Z | :attr:`~torch.float16` | ``1e-3`` | ``1e-5`` | 2025-08-26T19:56:01.6402801Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6403198Z | :attr:`~torch.bfloat16` | ``1.6e-2`` | ``1e-5`` | 2025-08-26T19:56:01.6403572Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6403961Z | :attr:`~torch.float32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:01.6404342Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6404726Z | :attr:`~torch.float64` | ``1e-7`` | ``1e-7`` | 2025-08-26T19:56:01.6405099Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6405486Z | :attr:`~torch.complex32` | ``1e-3`` | ``1e-5`` | 2025-08-26T19:56:01.6405906Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6406299Z | :attr:`~torch.complex64` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:01.6406671Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6407056Z | :attr:`~torch.complex128` | ``1e-7`` | ``1e-7`` | 2025-08-26T19:56:01.6407446Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6407827Z | :attr:`~torch.quint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:01.6408206Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6408583Z | :attr:`~torch.quint2x4` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:01.6409049Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6409439Z | :attr:`~torch.quint4x2` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:01.6409828Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6410200Z | :attr:`~torch.qint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:01.6410591Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6411018Z | :attr:`~torch.qint32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:01.6411402Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6411762Z | other | ``0.0`` | ``0.0`` | 2025-08-26T19:56:01.6412133Z +---------------------------+------------+----------+ 2025-08-26T19:56:01.6412383Z 2025-08-26T19:56:01.6412479Z .. note:: 2025-08-26T19:56:01.6412612Z 2025-08-26T19:56:01.6413079Z :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged 2025-08-26T19:56:01.6413957Z to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might 2025-08-26T19:56:01.6414699Z define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default: 2025-08-26T19:56:01.6415098Z 2025-08-26T19:56:01.6415200Z >>> import functools 2025-08-26T19:56:01.6415657Z >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0) 2025-08-26T19:56:01.6416168Z >>> assert_equal(1e-9, 1e-10) 2025-08-26T19:56:01.6416511Z Traceback (most recent call last): 2025-08-26T19:56:01.6416820Z ... 2025-08-26T19:56:01.6417081Z AssertionError: Scalars are not equal! 2025-08-26T19:56:01.6417423Z 2025-08-26T19:56:01.6417690Z Expected 1e-10 but got 1e-09. 2025-08-26T19:56:01.6418027Z Absolute difference: 9.000000000000001e-10 2025-08-26T19:56:01.6418394Z Relative difference: 9.0 2025-08-26T19:56:01.6418590Z 2025-08-26T19:56:01.6418693Z Examples: 2025-08-26T19:56:01.6418949Z >>> # tensor to tensor comparison 2025-08-26T19:56:01.6419305Z >>> expected = torch.tensor([1e0, 1e-1, 1e-2]) 2025-08-26T19:56:01.6419701Z >>> actual = torch.acos(torch.cos(expected)) 2025-08-26T19:56:01.6420104Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:01.6420371Z 2025-08-26T19:56:01.6420508Z >>> # scalar to scalar comparison 2025-08-26T19:56:01.6420820Z >>> import math 2025-08-26T19:56:01.6421102Z >>> expected = math.sqrt(2.0) 2025-08-26T19:56:01.6421432Z >>> actual = 2.0 / math.sqrt(2.0) 2025-08-26T19:56:01.6421807Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:01.6422065Z 2025-08-26T19:56:01.6422194Z >>> # numpy array to numpy array comparison 2025-08-26T19:56:01.6422554Z >>> import numpy as np 2025-08-26T19:56:01.6422880Z >>> expected = np.array([1e0, 1e-1, 1e-2]) 2025-08-26T19:56:01.6423253Z >>> actual = np.arccos(np.cos(expected)) 2025-08-26T19:56:01.6423650Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:01.6423910Z 2025-08-26T19:56:01.6424029Z >>> # sequence to sequence comparison 2025-08-26T19:56:01.6424371Z >>> import numpy as np 2025-08-26T19:56:01.6424820Z >>> # The types of the sequences do not have to match. They only have to have the same 2025-08-26T19:56:01.6425377Z >>> # length and their elements have to match. 2025-08-26T19:56:01.6425777Z >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)] 2025-08-26T19:56:01.6426164Z >>> actual = tuple(expected) 2025-08-26T19:56:01.6426533Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:01.6426792Z 2025-08-26T19:56:01.6426925Z >>> # mapping to mapping comparison 2025-08-26T19:56:01.6427274Z >>> from collections import OrderedDict 2025-08-26T19:56:01.6427628Z >>> import numpy as np 2025-08-26T19:56:01.6427931Z >>> foo = torch.tensor(1.0) 2025-08-26T19:56:01.6428241Z >>> bar = 2.0 2025-08-26T19:56:01.6428492Z >>> baz = np.array(3.0) 2025-08-26T19:56:01.6428948Z >>> # The types and a possible ordering of mappings do not have to match. They only 2025-08-26T19:56:01.6429547Z >>> # have to have the same set of keys and their elements have to match. 2025-08-26T19:56:01.6430128Z >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)]) 2025-08-26T19:56:01.6430607Z >>> actual = {"baz": baz, "bar": bar, "foo": foo} 2025-08-26T19:56:01.6431001Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:01.6431273Z 2025-08-26T19:56:01.6431406Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T19:56:01.6431765Z >>> actual = expected.clone() 2025-08-26T19:56:01.6432157Z >>> # By default, directly related instances can be compared 2025-08-26T19:56:01.6432727Z >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected) 2025-08-26T19:56:01.6433279Z >>> # This check can be made more strict with allow_subclasses=False 2025-08-26T19:56:01.6433721Z >>> torch.testing.assert_close( 2025-08-26T19:56:01.6434159Z ... torch.nn.Parameter(actual), expected, allow_subclasses=False 2025-08-26T19:56:01.6434584Z ... ) 2025-08-26T19:56:01.6434836Z Traceback (most recent call last): 2025-08-26T19:56:01.6435166Z ... 2025-08-26T19:56:01.6435509Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T19:56:01.6436070Z and . 2025-08-26T19:56:01.6436636Z >>> # If the inputs are not directly related, they are never considered close 2025-08-26T19:56:01.6437176Z >>> torch.testing.assert_close(actual.numpy(), expected) 2025-08-26T19:56:01.6437810Z Traceback (most recent call last): 2025-08-26T19:56:01.6438135Z ... 2025-08-26T19:56:01.6438561Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T19:56:01.6439100Z and . 2025-08-26T19:56:01.6439593Z >>> # Exceptions to these rules are Python scalars. They can be checked regardless of 2025-08-26T19:56:01.6440112Z >>> # their type if check_dtype=False. 2025-08-26T19:56:01.6440518Z >>> torch.testing.assert_close(1.0, 1, check_dtype=False) 2025-08-26T19:56:01.6440825Z 2025-08-26T19:56:01.6440927Z >>> # NaN != NaN by default. 2025-08-26T19:56:01.6441264Z >>> expected = torch.tensor(float("Nan")) 2025-08-26T19:56:01.6441626Z >>> actual = expected.clone() 2025-08-26T19:56:01.6442003Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:01.6442379Z Traceback (most recent call last): 2025-08-26T19:56:01.6442699Z ... 2025-08-26T19:56:01.6442955Z AssertionError: Scalars are not close! 2025-08-26T19:56:01.6443295Z 2025-08-26T19:56:01.6443542Z Expected nan but got nan. 2025-08-26T19:56:01.6443894Z Absolute difference: nan (up to 1e-05 allowed) 2025-08-26T19:56:01.6444306Z Relative difference: nan (up to 1.3e-06 allowed) 2025-08-26T19:56:01.6444783Z >>> torch.testing.assert_close(actual, expected, equal_nan=True) 2025-08-26T19:56:01.6445201Z 2025-08-26T19:56:01.6445331Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T19:56:01.6445703Z >>> actual = torch.tensor([1.0, 4.0, 5.0]) 2025-08-26T19:56:01.6446096Z >>> # The default error message can be overwritten. 2025-08-26T19:56:01.6446484Z >>> torch.testing.assert_close( 2025-08-26T19:56:01.6446888Z ... actual, expected, msg="Argh, the tensors are not close!" 2025-08-26T19:56:01.6447289Z ... ) 2025-08-26T19:56:01.6447550Z Traceback (most recent call last): 2025-08-26T19:56:01.6447874Z ... 2025-08-26T19:56:01.6448153Z AssertionError: Argh, the tensors are not close! 2025-08-26T19:56:01.6448657Z >>> # If msg is a callable, it can be used to augment the generated message with 2025-08-26T19:56:01.6449188Z >>> # extra information 2025-08-26T19:56:01.6449498Z >>> torch.testing.assert_close( 2025-08-26T19:56:01.6449934Z ... actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter" 2025-08-26T19:56:01.6450342Z ... ) 2025-08-26T19:56:01.6450661Z Traceback (most recent call last): 2025-08-26T19:56:01.6450979Z ... 2025-08-26T19:56:01.6451221Z AssertionError: Header 2025-08-26T19:56:01.6451497Z 2025-08-26T19:56:01.6451762Z Tensor-likes are not close! 2025-08-26T19:56:01.6452074Z 2025-08-26T19:56:01.6452338Z Mismatched elements: 2 / 3 (66.7%) 2025-08-26T19:56:01.6452796Z Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed) 2025-08-26T19:56:01.6453469Z Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed) 2025-08-26T19:56:01.6453924Z 2025-08-26T19:56:01.6454167Z Footer 2025-08-26T19:56:01.6454384Z 2025-08-26T19:56:01.6454764Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:01.6455157Z 2025-08-26T19:56:03.0535163Z msg = Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py line=134. 2025-08-26T19:56:03.0536212Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.0536764Z Register a container-like type as pytree node. 2025-08-26T19:56:03.0537025Z 2025-08-26T19:56:03.0537132Z Args: 2025-08-26T19:56:03.0537593Z cls (type): A Python type to treat as an internal pytree node. 2025-08-26T19:56:03.0538193Z flatten_fn (callable): A function to be used during flattening, taking an instance of 2025-08-26T19:56:03.0538877Z ``cls`` and returning a pair, with (1) an iterable for the children to be flattened 2025-08-26T19:56:03.0539560Z recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be 2025-08-26T19:56:03.0540110Z passed to the ``unflatten_fn``. 2025-08-26T19:56:03.0540621Z unflatten_fn (callable): A function taking two arguments: the auxiliary data that was 2025-08-26T19:56:03.0541304Z returned by ``flatten_fn`` and stored in the treespec, and the unflattened children. 2025-08-26T19:56:03.0541862Z The function should return an instance of ``cls``. 2025-08-26T19:56:03.0542410Z serialized_type_name (str, optional): A keyword argument used to specify the fully 2025-08-26T19:56:03.0542966Z qualified name used when serializing the tree spec. 2025-08-26T19:56:03.0543571Z to_dumpable_context (callable, optional): An optional keyword argument to custom specify how 2025-08-26T19:56:03.0544307Z to convert the context of the pytree to a custom json dumpable representation. This is 2025-08-26T19:56:03.0544994Z used for json serialization, which is being used in :mod:`torch.export` right now. 2025-08-26T19:56:03.0545707Z from_dumpable_context (callable, optional): An optional keyword argument to custom specify 2025-08-26T19:56:03.0546404Z how to convert the custom json dumpable representation of the context back to the 2025-08-26T19:56:03.0547309Z original context. This is used for json deserialization, which is being used in 2025-08-26T19:56:03.0547822Z :mod:`torch.export` right now. 2025-08-26T19:56:03.0548049Z 2025-08-26T19:56:03.0548177Z Example:: 2025-08-26T19:56:03.0548310Z 2025-08-26T19:56:03.0548426Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.0548753Z >>> # Registry a Python type with lambda functions 2025-08-26T19:56:03.0549127Z >>> register_pytree_node( 2025-08-26T19:56:03.0549424Z ... set, 2025-08-26T19:56:03.0549713Z ... lambda s: (sorted(s), None, None), 2025-08-26T19:56:03.0550081Z ... lambda children, _: set(children), 2025-08-26T19:56:03.0550411Z ... ) 2025-08-26T19:56:03.0550628Z 2025-08-26T19:56:03.0551006Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.0551384Z 2025-08-26T19:56:03.1112666Z msg = Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1218. 2025-08-26T19:56:03.1113948Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1114350Z 2025-08-26T19:56:03.1114571Z Context passed to policy function during selective checkpointing. 2025-08-26T19:56:03.1114917Z 2025-08-26T19:56:03.1115149Z This class is used to pass relevant metadata to the policy function during 2025-08-26T19:56:03.1115784Z selective checkpointing. The metadata includes whether the current invocation 2025-08-26T19:56:03.1116461Z of the policy function is during recomputation or not. 2025-08-26T19:56:03.1116742Z 2025-08-26T19:56:03.1116831Z Example: 2025-08-26T19:56:03.1117069Z >>> # xdoctest: +SKIP(stub) 2025-08-26T19:56:03.1117359Z >>> 2025-08-26T19:56:03.1117640Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T19:56:03.1118031Z >>> print(ctx.is_recompute) 2025-08-26T19:56:03.1118326Z >>> 2025-08-26T19:56:03.1118900Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T19:56:03.1119710Z >>> 2025-08-26T19:56:03.1119963Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T19:56:03.1120313Z >>> fn, x, y, 2025-08-26T19:56:03.1120579Z >>> use_reentrant=False, 2025-08-26T19:56:03.1120884Z >>> context_fn=context_fn, 2025-08-26T19:56:03.1121161Z >>> ) 2025-08-26T19:56:03.1121292Z 2025-08-26T19:56:03.1121548Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1121936Z 2025-08-26T19:56:03.1122606Z msg = Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1358. 2025-08-26T19:56:03.1123636Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1124021Z 2025-08-26T19:56:03.1124273Z Helper to avoid recomputing certain ops during activation checkpointing. 2025-08-26T19:56:03.1124632Z 2025-08-26T19:56:03.1124864Z Use this with `torch.utils.checkpoint.checkpoint` to control which 2025-08-26T19:56:03.1125352Z operations are recomputed during the backward pass. 2025-08-26T19:56:03.1125639Z 2025-08-26T19:56:03.1125721Z Args: 2025-08-26T19:56:03.1125960Z policy_fn_or_list (Callable or List): 2025-08-26T19:56:03.1126367Z - If a policy function is provided, it should accept a 2025-08-26T19:56:03.1126891Z :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and 2025-08-26T19:56:03.1127478Z kwargs to the op, and return a :class:`CheckpointPolicy` enum value 2025-08-26T19:56:03.1128059Z indicating whether the execution of the op should be recomputed or not. 2025-08-26T19:56:03.1128633Z - If a list of operations is provided, it is equivalent to a policy 2025-08-26T19:56:03.1129218Z returning `CheckpointPolicy.MUST_SAVE` for the specified 2025-08-26T19:56:03.1129739Z operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other 2025-08-26T19:56:03.1130277Z operations. 2025-08-26T19:56:03.1130654Z allow_cache_entry_mutation (bool, optional): By default, an error is 2025-08-26T19:56:03.1131223Z raised if any tensors cached by selective activation checkpoint are 2025-08-26T19:56:03.1131770Z mutated in order to ensure correctness. If set to `True`, this check 2025-08-26T19:56:03.1132203Z is disabled. 2025-08-26T19:56:03.1132453Z Returns: 2025-08-26T19:56:03.1132691Z A tuple of two context managers. 2025-08-26T19:56:03.1132904Z 2025-08-26T19:56:03.1132994Z Example: 2025-08-26T19:56:03.1133231Z >>> # xdoctest: +REQUIRES(LINUX) 2025-08-26T19:56:03.1133540Z >>> import functools 2025-08-26T19:56:03.1133800Z >>> 2025-08-26T19:56:03.1134037Z >>> x = torch.rand(10, 10, requires_grad=True) 2025-08-26T19:56:03.1134406Z >>> y = torch.rand(10, 10, requires_grad=True) 2025-08-26T19:56:03.1134735Z >>> 2025-08-26T19:56:03.1134951Z >>> ops_to_save = [ 2025-08-26T19:56:03.1135222Z >>> torch.ops.aten.mm.default, 2025-08-26T19:56:03.1135573Z >>> ] 2025-08-26T19:56:03.1135785Z >>> 2025-08-26T19:56:03.1136037Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T19:56:03.1136373Z >>> if op in ops_to_save: 2025-08-26T19:56:03.1136708Z >>> return CheckpointPolicy.MUST_SAVE 2025-08-26T19:56:03.1137047Z >>> else: 2025-08-26T19:56:03.1137339Z >>> return CheckpointPolicy.PREFER_RECOMPUTE 2025-08-26T19:56:03.1137879Z >>> 2025-08-26T19:56:03.1138380Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T19:56:03.1138874Z >>> 2025-08-26T19:56:03.1139099Z >>> # or equivalently 2025-08-26T19:56:03.1139545Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save) 2025-08-26T19:56:03.1140046Z >>> 2025-08-26T19:56:03.1140266Z >>> def fn(x, y): 2025-08-26T19:56:03.1140638Z >>> return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y 2025-08-26T19:56:03.1141046Z >>> 2025-08-26T19:56:03.1141309Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T19:56:03.1141660Z >>> fn, x, y, 2025-08-26T19:56:03.1141925Z >>> use_reentrant=False, 2025-08-26T19:56:03.1142220Z >>> context_fn=context_fn, 2025-08-26T19:56:03.1142516Z >>> ) 2025-08-26T19:56:03.1142648Z 2025-08-26T19:56:03.1142902Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1143278Z 2025-08-26T19:56:03.1377546Z msg = Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1159. 2025-08-26T19:56:03.1378519Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1378907Z 2025-08-26T19:56:03.1379069Z Create a :class:`setuptools.Extension` for C++. 2025-08-26T19:56:03.1379327Z 2025-08-26T19:56:03.1379571Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T19:56:03.1380177Z bare minimum (but often sufficient) arguments to build a C++ extension. 2025-08-26T19:56:03.1380536Z 2025-08-26T19:56:03.1380750Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T19:56:03.1381239Z constructor. Full list arguments can be found at 2025-08-26T19:56:03.1381849Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T19:56:03.1382299Z 2025-08-26T19:56:03.1382405Z .. warning:: 2025-08-26T19:56:03.1382778Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T19:56:03.1383561Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T19:56:03.1384329Z the user's responsibility in their library to not use APIs from 2025-08-26T19:56:03.1385337Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T19:56:03.1385936Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T19:56:03.1386641Z example, to give access to custom ops from python, the library should 2025-08-26T19:56:03.1387120Z register the ops through the dispatcher. 2025-08-26T19:56:03.1387358Z 2025-08-26T19:56:03.1387602Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T19:56:03.1388154Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T19:56:03.1388704Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T19:56:03.1389354Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T19:56:03.1390377Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T19:56:03.1390941Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T19:56:03.1391383Z CPython version of choice. 2025-08-26T19:56:03.1391588Z 2025-08-26T19:56:03.1391675Z Example: 2025-08-26T19:56:03.1391903Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.1392240Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:03.1392687Z >>> from setuptools import setup 2025-08-26T19:56:03.1393139Z >>> from torch.utils.cpp_extension import BuildExtension, CppExtension 2025-08-26T19:56:03.1393585Z >>> setup( 2025-08-26T19:56:03.1393833Z ... name='extension', 2025-08-26T19:56:03.1394108Z ... ext_modules=[ 2025-08-26T19:56:03.1394388Z ... CppExtension( 2025-08-26T19:56:03.1394685Z ... name='extension', 2025-08-26T19:56:03.1395017Z ... sources=['extension.cpp'], 2025-08-26T19:56:03.1395445Z ... extra_compile_args=['-g'], 2025-08-26T19:56:03.1395839Z ... extra_link_args=['-Wl,--no-as-needed', '-lm']) 2025-08-26T19:56:03.1396206Z ... ], 2025-08-26T19:56:03.1396447Z ... cmdclass={ 2025-08-26T19:56:03.1396712Z ... 'build_ext': BuildExtension 2025-08-26T19:56:03.1397030Z ... }) 2025-08-26T19:56:03.1397176Z 2025-08-26T19:56:03.1397433Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1397810Z 2025-08-26T19:56:03.1398764Z msg = Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1229. 2025-08-26T19:56:03.1400383Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1400966Z 2025-08-26T19:56:03.1401129Z Create a :class:`setuptools.Extension` for CUDA/C++. 2025-08-26T19:56:03.1401403Z 2025-08-26T19:56:03.1401669Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T19:56:03.1402246Z bare minimum (but often sufficient) arguments to build a CUDA/C++ 2025-08-26T19:56:03.1402804Z extension. This includes the CUDA include path, library path and runtime 2025-08-26T19:56:03.1403253Z library. 2025-08-26T19:56:03.1403372Z 2025-08-26T19:56:03.1403594Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T19:56:03.1404080Z constructor. Full list arguments can be found at 2025-08-26T19:56:03.1404670Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T19:56:03.1405133Z 2025-08-26T19:56:03.1405230Z .. warning:: 2025-08-26T19:56:03.1405601Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T19:56:03.1406177Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T19:56:03.1406707Z the user's responsibility in their library to not use APIs from 2025-08-26T19:56:03.1407276Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T19:56:03.1407862Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T19:56:03.1408447Z example, to give access to custom ops from python, the library should 2025-08-26T19:56:03.1409299Z register the ops through the dispatcher. 2025-08-26T19:56:03.1409693Z 2025-08-26T19:56:03.1410216Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T19:56:03.1410929Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T19:56:03.1411476Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T19:56:03.1412030Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T19:56:03.1412588Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T19:56:03.1413138Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T19:56:03.1413601Z CPython version of choice. 2025-08-26T19:56:03.1413798Z 2025-08-26T19:56:03.1413899Z Example: 2025-08-26T19:56:03.1414132Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.1414449Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:03.1414837Z >>> from setuptools import setup 2025-08-26T19:56:03.1415285Z >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension 2025-08-26T19:56:03.1415733Z >>> setup( 2025-08-26T19:56:03.1416012Z ... name='cuda_extension', 2025-08-26T19:56:03.1416323Z ... ext_modules=[ 2025-08-26T19:56:03.1416602Z ... CUDAExtension( 2025-08-26T19:56:03.1416915Z ... name='cuda_extension', 2025-08-26T19:56:03.1417308Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T19:56:03.1417745Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T19:56:03.1418130Z ... 'nvcc': ['-O2']}, 2025-08-26T19:56:03.1418629Z ... extra_link_args=['-Wl,--no-as-needed', '-lcuda']) 2025-08-26T19:56:03.1418991Z ... ], 2025-08-26T19:56:03.1419226Z ... cmdclass={ 2025-08-26T19:56:03.1419500Z ... 'build_ext': BuildExtension 2025-08-26T19:56:03.1419818Z ... }) 2025-08-26T19:56:03.1419951Z 2025-08-26T19:56:03.1420053Z Compute capabilities: 2025-08-26T19:56:03.1420231Z 2025-08-26T19:56:03.1420540Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T19:56:03.1421271Z building process of the extension, plus PTX. If down the road a new card is installed the 2025-08-26T19:56:03.1421999Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's 2025-08-26T19:56:03.1422738Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch 2025-08-26T19:56:03.1423452Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does 2025-08-26T19:56:03.1423994Z support (see below for details on PTX). 2025-08-26T19:56:03.1424232Z 2025-08-26T19:56:03.1424547Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which 2025-08-26T19:56:03.1425115Z CCs you want the extension to support: 2025-08-26T19:56:03.1425336Z 2025-08-26T19:56:03.1425540Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py`` 2025-08-26T19:56:03.1426082Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py`` 2025-08-26T19:56:03.1426458Z 2025-08-26T19:56:03.1426782Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified 2025-08-26T19:56:03.1427559Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >= 2025-08-26T19:56:03.1428316Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with 2025-08-26T19:56:03.1429060Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to 2025-08-26T19:56:03.1429805Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on 2025-08-26T19:56:03.1430541Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better 2025-08-26T19:56:03.1431279Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6, 2025-08-26T19:56:03.1432057Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but 2025-08-26T19:56:03.1432636Z "8.0 8.6" would be better. 2025-08-26T19:56:03.1432810Z 2025-08-26T19:56:03.1433119Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T19:56:03.1433844Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T19:56:03.1434270Z 2025-08-26T19:56:03.1434606Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows. 2025-08-26T19:56:03.1435295Z To workaround the issue, move python binding logic to pure C++ file. 2025-08-26T19:56:03.1435625Z 2025-08-26T19:56:03.1435727Z Example use: 2025-08-26T19:56:03.1435955Z #include 2025-08-26T19:56:03.1436293Z at::Tensor SigmoidAlphaBlendForwardCuda(....) 2025-08-26T19:56:03.1436569Z 2025-08-26T19:56:03.1436657Z Instead of: 2025-08-26T19:56:03.1436900Z #include 2025-08-26T19:56:03.1437257Z torch::Tensor SigmoidAlphaBlendForwardCuda(...) 2025-08-26T19:56:03.1437817Z 2025-08-26T19:56:03.1438104Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460 2025-08-26T19:56:03.1439040Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48 2025-08-26T19:56:03.1439677Z 2025-08-26T19:56:03.1439800Z Relocatable device code linking: 2025-08-26T19:56:03.1440003Z 2025-08-26T19:56:03.1440302Z If you want to reference device symbols across compilation units (across object files), 2025-08-26T19:56:03.1441075Z the object files need to be built with `relocatable device code` (-rdc=true or -dc). 2025-08-26T19:56:03.1441842Z An exception to this rule is "dynamic parallelism" (nested kernel launches) which is not used a lot anymore. 2025-08-26T19:56:03.1442682Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it. 2025-08-26T19:56:03.1443476Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step 2025-08-26T19:56:03.1444125Z helps reduce the protentional perf degradation of `-rdc`. 2025-08-26T19:56:03.1444586Z Note that it needs to be used at both steps to be useful. 2025-08-26T19:56:03.1444879Z 2025-08-26T19:56:03.1445253Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step. 2025-08-26T19:56:03.1445928Z There is also a case where `-dlink` is used without `-rdc`: 2025-08-26T19:56:03.1446487Z when an extension is linked against a static lib containing rdc-compiled objects 2025-08-26T19:56:03.1447092Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem). 2025-08-26T19:56:03.1447427Z 2025-08-26T19:56:03.1447633Z Note: Ninja is required to build a CUDA Extension with RDC linking. 2025-08-26T19:56:03.1447966Z 2025-08-26T19:56:03.1448053Z Example: 2025-08-26T19:56:03.1448279Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.1448608Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:03.1449041Z >>> CUDAExtension( 2025-08-26T19:56:03.1449319Z ... name='cuda_extension', 2025-08-26T19:56:03.1449700Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T19:56:03.1450083Z ... dlink=True, 2025-08-26T19:56:03.1450366Z ... dlink_libraries=["dlink_lib"], 2025-08-26T19:56:03.1450726Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T19:56:03.1451096Z ... 'nvcc': ['-O2', '-rdc=true']}) 2025-08-26T19:56:03.1451337Z 2025-08-26T19:56:03.1451609Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1451986Z 2025-08-26T19:56:03.1452558Z msg = Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1420. 2025-08-26T19:56:03.1453492Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1453937Z 2025-08-26T19:56:03.1454104Z Creates a :class:`setuptools.Extension` for SYCL/C++. 2025-08-26T19:56:03.1454392Z 2025-08-26T19:56:03.1454638Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T19:56:03.1455213Z bare minimum (but often sufficient) arguments to build a SYCL/C++ 2025-08-26T19:56:03.1455635Z extension. 2025-08-26T19:56:03.1455760Z 2025-08-26T19:56:03.1455969Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T19:56:03.1456399Z constructor. 2025-08-26T19:56:03.1456542Z 2025-08-26T19:56:03.1456635Z .. warning:: 2025-08-26T19:56:03.1457012Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T19:56:03.1457574Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T19:56:03.1458119Z the user's responsibility in their library to not use APIs from 2025-08-26T19:56:03.1458679Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T19:56:03.1459265Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T19:56:03.1459871Z example, to give access to custom ops from python, the library should 2025-08-26T19:56:03.1460336Z register the ops through the dispatcher. 2025-08-26T19:56:03.1460589Z 2025-08-26T19:56:03.1460818Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T19:56:03.1461384Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T19:56:03.1461936Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T19:56:03.1462552Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T19:56:03.1463111Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T19:56:03.1463716Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T19:56:03.1464170Z CPython version of choice. 2025-08-26T19:56:03.1464363Z 2025-08-26T19:56:03.1464471Z Example: 2025-08-26T19:56:03.1464691Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.1465025Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:03.1465531Z >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension 2025-08-26T19:56:03.1465980Z >>> setup( 2025-08-26T19:56:03.1466220Z ... name='xpu_extension', 2025-08-26T19:56:03.1466529Z ... ext_modules=[ 2025-08-26T19:56:03.1466806Z ... SyclExtension( 2025-08-26T19:56:03.1467106Z ... name='xpu_extension', 2025-08-26T19:56:03.1467495Z ... sources=['extension.cpp', 'extension_kernel.cpp'], 2025-08-26T19:56:03.1467973Z ... extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']}) 2025-08-26T19:56:03.1468373Z ... ], 2025-08-26T19:56:03.1468610Z ... cmdclass={ 2025-08-26T19:56:03.1468879Z ... 'build_ext': BuildExtension 2025-08-26T19:56:03.1469198Z ... }) 2025-08-26T19:56:03.1469348Z 2025-08-26T19:56:03.1469653Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T19:56:03.1470347Z building process of the extension. If down the road a new card is installed the 2025-08-26T19:56:03.1470993Z extension may need to be recompiled. You can override the default behavior using 2025-08-26T19:56:03.1471679Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension 2025-08-26T19:56:03.1472208Z to support: 2025-08-26T19:56:03.1472349Z 2025-08-26T19:56:03.1472557Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py`` 2025-08-26T19:56:03.1472879Z 2025-08-26T19:56:03.1473194Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T19:56:03.1473919Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T19:56:03.1474334Z 2025-08-26T19:56:03.1474475Z Note: Ninja is required to build SyclExtension. 2025-08-26T19:56:03.1474783Z 2025-08-26T19:56:03.1475039Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1475427Z 2025-08-26T19:56:03.1476019Z msg = Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1597. 2025-08-26T19:56:03.1476905Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1477302Z 2025-08-26T19:56:03.1477449Z Load a PyTorch C++ extension just-in-time (JIT). 2025-08-26T19:56:03.1477721Z 2025-08-26T19:56:03.1477934Z To load an extension, a Ninja build file is emitted, which is used to 2025-08-26T19:56:03.1478477Z compile the given sources into a dynamic library. This library is 2025-08-26T19:56:03.1479038Z subsequently loaded into the current Python process as a module and 2025-08-26T19:56:03.1479501Z returned from this function, ready for use. 2025-08-26T19:56:03.1479752Z 2025-08-26T19:56:03.1479963Z By default, the directory to which the build file is emitted and the 2025-08-26T19:56:03.1480568Z resulting library compiled to is ``/torch_extensions/``, where 2025-08-26T19:56:03.1481144Z ```` is the temporary folder on the current platform and ```` 2025-08-26T19:56:03.1481680Z the name of the extension. This location can be overridden in two ways. 2025-08-26T19:56:03.1482235Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it 2025-08-26T19:56:03.1482795Z replaces ``/torch_extensions`` and all extensions will be compiled 2025-08-26T19:56:03.1483419Z into subfolders of this directory. Second, if the ``build_directory`` 2025-08-26T19:56:03.1484002Z argument to this function is supplied, it overrides the entire path, i.e. 2025-08-26T19:56:03.1484521Z the library will be compiled into that folder directly. 2025-08-26T19:56:03.1484812Z 2025-08-26T19:56:03.1485032Z To compile the sources, the default system compiler (``c++``) is used, 2025-08-26T19:56:03.1485619Z which can be overridden by setting the ``CXX`` environment variable. To pass 2025-08-26T19:56:03.1486231Z additional arguments to the compilation process, ``extra_cflags`` or 2025-08-26T19:56:03.1486802Z ``extra_ldflags`` can be provided. For example, to compile your extension 2025-08-26T19:56:03.1487372Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use 2025-08-26T19:56:03.1487868Z ``extra_cflags`` to pass further include directories. 2025-08-26T19:56:03.1488137Z 2025-08-26T19:56:03.1488389Z CUDA support with mixed compilation is provided. Simply pass CUDA source 2025-08-26T19:56:03.1489039Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be 2025-08-26T19:56:03.1489596Z detected and compiled with nvcc rather than the C++ compiler. This includes 2025-08-26T19:56:03.1490190Z passing the CUDA lib64 directory as a library directory, and linking 2025-08-26T19:56:03.1490692Z ``cudart``. You can pass additional flags to nvcc via 2025-08-26T19:56:03.1491179Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various 2025-08-26T19:56:03.1491748Z heuristics for finding the CUDA install directory are used, which usually 2025-08-26T19:56:03.1492333Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the 2025-08-26T19:56:03.1492763Z safest option. 2025-08-26T19:56:03.1492902Z 2025-08-26T19:56:03.1493154Z SYCL support with mixed compilation is provided. Simply pass SYCL source 2025-08-26T19:56:03.1493725Z files (``.sycl``) along with other sources. Such files will be detected 2025-08-26T19:56:03.1494269Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather 2025-08-26T19:56:03.1494829Z than the C++ compiler. You can pass additional flags to SYCL compiler 2025-08-26T19:56:03.1495361Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++. 2025-08-26T19:56:03.1495891Z SYCL compiler is expected to be found via system PATH environment 2025-08-26T19:56:03.1496299Z variable. 2025-08-26T19:56:03.1496432Z 2025-08-26T19:56:03.1496515Z Args: 2025-08-26T19:56:03.1496939Z name: The name of the extension to build. This MUST be the same as the 2025-08-26T19:56:03.1497388Z name of the pybind11 module! 2025-08-26T19:56:03.1497799Z sources: A list of relative or absolute paths to C++ source files. 2025-08-26T19:56:03.1498361Z extra_cflags: optional list of compiler flags to forward to the build. 2025-08-26T19:56:03.1498941Z extra_cuda_cflags: optional list of compiler flags to forward to nvcc 2025-08-26T19:56:03.1499401Z when building CUDA sources. 2025-08-26T19:56:03.1499838Z extra_sycl_cflags: optional list of compiler flags to forward to SYCL 2025-08-26T19:56:03.1500303Z compiler when building SYCL sources. 2025-08-26T19:56:03.1500764Z extra_ldflags: optional list of linker flags to forward to the build. 2025-08-26T19:56:03.1501341Z extra_include_paths: optional list of include directories to forward 2025-08-26T19:56:03.1501789Z to the build. 2025-08-26T19:56:03.1502128Z build_directory: optional path to use as build workspace. 2025-08-26T19:56:03.1502621Z verbose: If ``True``, turns on verbose logging of load steps. 2025-08-26T19:56:03.1503188Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T19:56:03.1503702Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:03.1504197Z automatically determined based on the existence of ``.cu`` or 2025-08-26T19:56:03.1504691Z ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers 2025-08-26T19:56:03.1505101Z and libraries to be included. 2025-08-26T19:56:03.1505612Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T19:56:03.1506129Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:03.1506617Z automatically determined based on the existence of ``.sycl`` in 2025-08-26T19:56:03.1507126Z ``sources``. Set it to `True`` to force SYCL headers and 2025-08-26T19:56:03.1507540Z libraries to be included. 2025-08-26T19:56:03.1507968Z is_python_module: If ``True`` (default), imports the produced shared 2025-08-26T19:56:03.1508491Z library as a Python module. If ``False``, behavior depends on 2025-08-26T19:56:03.1508918Z ``is_standalone``. 2025-08-26T19:56:03.1509314Z is_standalone: If ``False`` (default) loads the constructed extension 2025-08-26T19:56:03.1509858Z into the process as a plain dynamic library. If ``True``, build a 2025-08-26T19:56:03.1510295Z standalone executable. 2025-08-26T19:56:03.1510486Z 2025-08-26T19:56:03.1510574Z Returns: 2025-08-26T19:56:03.1510822Z If ``is_python_module`` is ``True``: 2025-08-26T19:56:03.1511235Z Returns the loaded PyTorch extension as a Python module. 2025-08-26T19:56:03.1511534Z 2025-08-26T19:56:03.1511754Z If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``: 2025-08-26T19:56:03.1512296Z Returns nothing. (The shared library is loaded into the process as 2025-08-26T19:56:03.1512738Z a side effect.) 2025-08-26T19:56:03.1512919Z 2025-08-26T19:56:03.1513030Z If ``is_standalone`` is ``True``. 2025-08-26T19:56:03.1513463Z Return the path to the executable. (On Windows, TORCH_LIB_PATH is 2025-08-26T19:56:03.1513965Z added to the PATH environment variable as a side effect.) 2025-08-26T19:56:03.1514276Z 2025-08-26T19:56:03.1514365Z Example: 2025-08-26T19:56:03.1514594Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.1514918Z >>> from torch.utils.cpp_extension import load 2025-08-26T19:56:03.1515268Z >>> module = load( 2025-08-26T19:56:03.1515518Z ... name='extension', 2025-08-26T19:56:03.1515873Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T19:56:03.1516257Z ... extra_cflags=['-O2'], 2025-08-26T19:56:03.1516551Z ... verbose=True) 2025-08-26T19:56:03.1516719Z 2025-08-26T19:56:03.1516974Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1517360Z 2025-08-26T19:56:03.1517937Z msg = Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1882. 2025-08-26T19:56:03.1518863Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1519247Z 2025-08-26T19:56:03.1519472Z Load a PyTorch C++ extension just-in-time (JIT) from string sources. 2025-08-26T19:56:03.1519798Z 2025-08-26T19:56:03.1520046Z This function behaves exactly like :func:`load`, but takes its sources as 2025-08-26T19:56:03.1520627Z strings rather than filenames. These strings are stored to files in the 2025-08-26T19:56:03.1521205Z build directory, after which the behavior of :func:`load_inline` is 2025-08-26T19:56:03.1521648Z identical to :func:`load`. 2025-08-26T19:56:03.1521830Z 2025-08-26T19:56:03.1521927Z See `the 2025-08-26T19:56:03.1522378Z tests `_ 2025-08-26T19:56:03.1522959Z for good examples of using this function. 2025-08-26T19:56:03.1523209Z 2025-08-26T19:56:03.1523477Z Sources may omit two required parts of a typical non-inline C++ extension: 2025-08-26T19:56:03.1524086Z the necessary header includes, as well as the (pybind11) binding code. More 2025-08-26T19:56:03.1524710Z precisely, strings passed to ``cpp_sources`` are first concatenated into a 2025-08-26T19:56:03.1525264Z single ``.cpp`` file. This file is then prepended with ``#include 2025-08-26T19:56:03.1525675Z `` 2025-08-26T19:56:03.1525850Z 2025-08-26T19:56:03.1526079Z Furthermore, if the ``functions`` argument is supplied, bindings will be 2025-08-26T19:56:03.1526733Z automatically generated for each function specified. ``functions`` can 2025-08-26T19:56:03.1527324Z either be a list of function names, or a dictionary mapping from function 2025-08-26T19:56:03.1527892Z names to docstrings. If a list is given, the name of each function is used 2025-08-26T19:56:03.1528339Z as its docstring. 2025-08-26T19:56:03.1528489Z 2025-08-26T19:56:03.1528722Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu`` 2025-08-26T19:56:03.1529327Z file and prepended with ``torch/types.h``, ``cuda.h`` and 2025-08-26T19:56:03.1529827Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled 2025-08-26T19:56:03.1530400Z separately, but ultimately linked into a single library. Note that no 2025-08-26T19:56:03.1530991Z bindings are generated for functions in ``cuda_sources`` per se. To bind 2025-08-26T19:56:03.1531580Z to a CUDA kernel, you must create a C++ function that calls it, and either 2025-08-26T19:56:03.1532154Z declare or define this C++ function in one of the ``cpp_sources`` (and 2025-08-26T19:56:03.1532595Z include its name in ``functions``). 2025-08-26T19:56:03.1532819Z 2025-08-26T19:56:03.1533040Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl`` 2025-08-26T19:56:03.1533611Z file and prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes. 2025-08-26T19:56:03.1534158Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately 2025-08-26T19:56:03.1534693Z linked into a single library. Note that no bindings are generated for 2025-08-26T19:56:03.1535256Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must 2025-08-26T19:56:03.1535814Z create a C++ function that calls it, and either declare or define this 2025-08-26T19:56:03.1536339Z C++ function in one of the ``cpp_sources`` (and include its name 2025-08-26T19:56:03.1536744Z in ``functions``). 2025-08-26T19:56:03.1536892Z 2025-08-26T19:56:03.1536896Z 2025-08-26T19:56:03.1536900Z 2025-08-26T19:56:03.1537091Z See :func:`load` for a description of arguments omitted below. 2025-08-26T19:56:03.1537571Z 2025-08-26T19:56:03.1537658Z Args: 2025-08-26T19:56:03.1538008Z cpp_sources: A string, or list of strings, containing C++ source code. 2025-08-26T19:56:03.1538591Z cuda_sources: A string, or list of strings, containing CUDA source code. 2025-08-26T19:56:03.1539173Z sycl_sources: A string, or list of strings, containing SYCL source code. 2025-08-26T19:56:03.1539805Z functions: A list of function names for which to generate function 2025-08-26T19:56:03.1540360Z bindings. If a dictionary is given, it should map function names to 2025-08-26T19:56:03.1540894Z docstrings (which are otherwise just the function names). 2025-08-26T19:56:03.1541431Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T19:56:03.1541933Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:03.1542431Z automatically determined based on whether ``cuda_sources`` is 2025-08-26T19:56:03.1542917Z provided. Set it to ``True`` to force CUDA headers 2025-08-26T19:56:03.1543307Z and libraries to be included. 2025-08-26T19:56:03.1543741Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T19:56:03.1544255Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:03.1544746Z automatically determined based on whether ``sycl_sources`` is 2025-08-26T19:56:03.1545282Z provided. Set it to ``True`` to force SYCL headers 2025-08-26T19:56:03.1545672Z and libraries to be included. 2025-08-26T19:56:03.1546093Z with_pytorch_error_handling: Determines whether pytorch error and 2025-08-26T19:56:03.1546643Z warning macros are handled by pytorch instead of pybind. To do 2025-08-26T19:56:03.1547194Z this, each function ``foo`` is called via an intermediary ``_safe_foo`` 2025-08-26T19:56:03.1547748Z function. This redirection might cause issues in obscure cases 2025-08-26T19:56:03.1548334Z of cpp. This flag should be set to ``False`` when this redirect 2025-08-26T19:56:03.1548745Z causes issues. 2025-08-26T19:56:03.1549166Z no_implicit_headers: If ``True``, skips automatically adding headers, most notably 2025-08-26T19:56:03.1549850Z ``#include `` and ``#include `` lines. 2025-08-26T19:56:03.1550590Z Use this option to improve cold start times when you 2025-08-26T19:56:03.1551436Z already include the necessary headers in your source code. Default: ``False``. 2025-08-26T19:56:03.1552121Z 2025-08-26T19:56:03.1560030Z Example: 2025-08-26T19:56:03.1560608Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:03.1561419Z >>> from torch.utils.cpp_extension import load_inline 2025-08-26T19:56:03.1561830Z >>> source = """ 2025-08-26T19:56:03.1562157Z at::Tensor sin_add(at::Tensor x, at::Tensor y) { 2025-08-26T19:56:03.1562527Z return x.sin() + y.sin(); 2025-08-26T19:56:03.1562823Z } 2025-08-26T19:56:03.1563020Z """ 2025-08-26T19:56:03.1563291Z >>> module = load_inline(name='inline_extension', 2025-08-26T19:56:03.1563673Z ... cpp_sources=[source], 2025-08-26T19:56:03.1564036Z ... functions=['sin_add']) 2025-08-26T19:56:03.1564275Z 2025-08-26T19:56:03.1564376Z .. note:: 2025-08-26T19:56:03.1564740Z Since load_inline will just-in-time compile the source code, please ensure 2025-08-26T19:56:03.1565349Z that you have the right toolchains installed in the runtime. For example, 2025-08-26T19:56:03.1565935Z when loading C++, make sure a C++ compiler is available. If you're loading 2025-08-26T19:56:03.1566538Z a CUDA extension, you will need to additionally install the corresponding CUDA 2025-08-26T19:56:03.1567153Z toolkit (nvcc and any other dependencies your code has). Compiling toolchains 2025-08-26T19:56:03.1567777Z are not included when you install torch and must be additionally installed. 2025-08-26T19:56:03.1568151Z 2025-08-26T19:56:03.1568409Z During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build 2025-08-26T19:56:03.1569101Z the extension. This may use up too many resources on some systems. One 2025-08-26T19:56:03.1569679Z can control the number of workers by setting the `MAX_JOBS` environment 2025-08-26T19:56:03.1570210Z variable to a non-negative number. 2025-08-26T19:56:03.1570448Z 2025-08-26T19:56:03.1570704Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1571093Z 2025-08-26T19:56:03.1608947Z msg = Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/throughput_benchmark.py line=61. 2025-08-26T19:56:03.1609967Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.1610355Z 2025-08-26T19:56:03.1610681Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark. 2025-08-26T19:56:03.1611097Z 2025-08-26T19:56:03.1611417Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible 2025-08-26T19:56:03.1612086Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference 2025-08-26T19:56:03.1612703Z server like load. It can emulate multiple calling threads to a single module 2025-08-26T19:56:03.1613319Z provided. In the future we plan to enhance this component to support inter and 2025-08-26T19:56:03.1614009Z intra-op parallelism as well as multiple models running in a single process. 2025-08-26T19:56:03.1614378Z 2025-08-26T19:56:03.1614653Z Please note that even though nn.Module is supported, it might incur an overhead 2025-08-26T19:56:03.1615251Z from the need to hold GIL every time we execute Python code or pass around 2025-08-26T19:56:03.1615852Z inputs as Python objects. As soon as you have a ScriptModule version of your 2025-08-26T19:56:03.1616522Z model for inference deployment it is better to switch to using it in this 2025-08-26T19:56:03.1616985Z benchmark. 2025-08-26T19:56:03.1617112Z 2025-08-26T19:56:03.1617202Z Example:: 2025-08-26T19:56:03.1617340Z 2025-08-26T19:56:03.1617460Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:03.1617843Z >>> from torch.utils import ThroughputBenchmark 2025-08-26T19:56:03.1618241Z >>> bench = ThroughputBenchmark(my_module) 2025-08-26T19:56:03.1618644Z >>> # Pre-populate benchmark's data set with the inputs 2025-08-26T19:56:03.1619043Z >>> for input in inputs: 2025-08-26T19:56:03.1619461Z ... # Both args and kwargs work, same as any PyTorch Module / ScriptModule 2025-08-26T19:56:03.1619942Z ... bench.add_input(input[0], x2=input[1]) 2025-08-26T19:56:03.1620396Z >>> # Inputs supplied above are randomly used during the execution 2025-08-26T19:56:03.1620813Z >>> stats = bench.benchmark( 2025-08-26T19:56:03.1621120Z ... num_calling_threads=4, 2025-08-26T19:56:03.1621437Z ... num_warmup_iters = 100, 2025-08-26T19:56:03.1621752Z ... num_iters = 1000, 2025-08-26T19:56:03.1622010Z ... ) 2025-08-26T19:56:03.1622345Z >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms)) 2025-08-26T19:56:03.1622827Z >>> print("Number of iterations: {}".format(stats.num_iters)) 2025-08-26T19:56:03.1623122Z 2025-08-26T19:56:03.1623391Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.1623769Z 2025-08-26T19:56:03.2570883Z msg = Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/distributed.py line=18. 2025-08-26T19:56:03.2571875Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.2572471Z Sampler that restricts data loading to a subset of the dataset. 2025-08-26T19:56:03.2572824Z 2025-08-26T19:56:03.2572961Z It is especially useful in conjunction with 2025-08-26T19:56:03.2573482Z :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each 2025-08-26T19:56:03.2574130Z process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a 2025-08-26T19:56:03.2574744Z :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the 2025-08-26T19:56:03.2575236Z original dataset that is exclusive to it. 2025-08-26T19:56:03.2575490Z 2025-08-26T19:56:03.2575589Z .. note:: 2025-08-26T19:56:03.2576158Z Dataset is assumed to be of constant size and that any instance of it always 2025-08-26T19:56:03.2576673Z returns the same elements in the same order. 2025-08-26T19:56:03.2576924Z 2025-08-26T19:56:03.2577010Z Args: 2025-08-26T19:56:03.2577260Z dataset: Dataset used for sampling. 2025-08-26T19:56:03.2577713Z num_replicas (int, optional): Number of processes participating in 2025-08-26T19:56:03.2578316Z distributed training. By default, :attr:`world_size` is retrieved from the 2025-08-26T19:56:03.2578799Z current distributed group. 2025-08-26T19:56:03.2579276Z rank (int, optional): Rank of the current process within :attr:`num_replicas`. 2025-08-26T19:56:03.2579853Z By default, :attr:`rank` is retrieved from the current distributed 2025-08-26T19:56:03.2580274Z group. 2025-08-26T19:56:03.2580654Z shuffle (bool, optional): If ``True`` (default), sampler will shuffle the 2025-08-26T19:56:03.2581091Z indices. 2025-08-26T19:56:03.2581504Z seed (int, optional): random seed used to shuffle the sampler if 2025-08-26T19:56:03.2582022Z :attr:`shuffle=True`. This number should be identical across all 2025-08-26T19:56:03.2582522Z processes in the distributed group. Default: ``0``. 2025-08-26T19:56:03.2583023Z drop_last (bool, optional): if ``True``, then the sampler will drop the 2025-08-26T19:56:03.2583571Z tail of the data to make it evenly divisible across the number of 2025-08-26T19:56:03.2584198Z replicas. If ``False``, the sampler will add extra indices to make 2025-08-26T19:56:03.2584738Z the data evenly divisible across the replicas. Default: ``False``. 2025-08-26T19:56:03.2585069Z 2025-08-26T19:56:03.2585177Z .. warning:: 2025-08-26T19:56:03.2585507Z In distributed mode, calling the :meth:`set_epoch` method at 2025-08-26T19:56:03.2586080Z the beginning of each epoch **before** creating the :class:`DataLoader` iterator 2025-08-26T19:56:03.2586731Z is necessary to make shuffling work properly across multiple epochs. Otherwise, 2025-08-26T19:56:03.2587250Z the same ordering will be always used. 2025-08-26T19:56:03.2587485Z 2025-08-26T19:56:03.2587574Z Example:: 2025-08-26T19:56:03.2587719Z 2025-08-26T19:56:03.2587818Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.2588232Z >>> sampler = DistributedSampler(dataset) if is_distributed else None 2025-08-26T19:56:03.2588761Z >>> loader = DataLoader(dataset, shuffle=(sampler is None), 2025-08-26T19:56:03.2589178Z ... sampler=sampler) 2025-08-26T19:56:03.2589537Z >>> for epoch in range(start_epoch, n_epochs): 2025-08-26T19:56:03.2589899Z ... if is_distributed: 2025-08-26T19:56:03.2590217Z ... sampler.set_epoch(epoch) 2025-08-26T19:56:03.2590542Z ... train(loader) 2025-08-26T19:56:03.2590799Z 2025-08-26T19:56:03.2591171Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.2591549Z 2025-08-26T19:56:03.2631618Z msg = Cannot scrape callname=WeightedRandomSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=227. 2025-08-26T19:56:03.2632627Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.2633354Z Samples elements from ``[0,..,len(weights)-1]`` with given probabilities (weights). 2025-08-26T19:56:03.2633791Z 2025-08-26T19:56:03.2633917Z Args: 2025-08-26T19:56:03.2634625Z weights (sequence) : a sequence of weights, not necessary summing up to one 2025-08-26T19:56:03.2635246Z num_samples (int): number of samples to draw 2025-08-26T19:56:03.2635725Z replacement (bool): if ``True``, samples are drawn with replacement. 2025-08-26T19:56:03.2636260Z If not, they are drawn without replacement, which means that when a 2025-08-26T19:56:03.2636819Z sample index is drawn for a row, it cannot be drawn again for that row. 2025-08-26T19:56:03.2637576Z generator (Generator): Generator used in sampling. 2025-08-26T19:56:03.2637851Z 2025-08-26T19:56:03.2637954Z Example: 2025-08-26T19:56:03.2638235Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:03.2638576Z >>> list( 2025-08-26T19:56:03.2638840Z ... WeightedRandomSampler( 2025-08-26T19:56:03.2639217Z ... [0.1, 0.9, 0.4, 0.7, 3.0, 0.6], 5, replacement=True 2025-08-26T19:56:03.2639572Z ... ) 2025-08-26T19:56:03.2639792Z ... ) 2025-08-26T19:56:03.2640021Z [4, 4, 1, 4, 5] 2025-08-26T19:56:03.2640272Z >>> list( 2025-08-26T19:56:03.2640531Z ... WeightedRandomSampler( 2025-08-26T19:56:03.2640886Z ... [0.9, 0.4, 0.05, 0.2, 0.3, 0.1], 5, replacement=False 2025-08-26T19:56:03.2641246Z ... ) 2025-08-26T19:56:03.2641477Z ... ) 2025-08-26T19:56:03.2641702Z [0, 1, 4, 3, 2] 2025-08-26T19:56:03.2641935Z 2025-08-26T19:56:03.2642398Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.2642774Z 2025-08-26T19:56:03.2643352Z msg = Cannot scrape callname=BatchSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=300. 2025-08-26T19:56:03.2644291Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.2644856Z Wraps another sampler to yield a mini-batch of indices. 2025-08-26T19:56:03.2645138Z 2025-08-26T19:56:03.2645223Z Args: 2025-08-26T19:56:03.2645663Z sampler (Sampler or Iterable): Base sampler. Can be any iterable object 2025-08-26T19:56:03.2646144Z batch_size (int): Size of mini-batch. 2025-08-26T19:56:03.2646589Z drop_last (bool): If ``True``, the sampler will drop the last batch if 2025-08-26T19:56:03.2647040Z its size would be less than ``batch_size`` 2025-08-26T19:56:03.2647303Z 2025-08-26T19:56:03.2647394Z Example: 2025-08-26T19:56:03.2647622Z >>> list( 2025-08-26T19:56:03.2647868Z ... BatchSampler( 2025-08-26T19:56:03.2648251Z ... SequentialSampler(range(10)), batch_size=3, drop_last=False 2025-08-26T19:56:03.2648669Z ... ) 2025-08-26T19:56:03.2648972Z ... ) 2025-08-26T19:56:03.2649212Z [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] 2025-08-26T19:56:03.2649506Z >>> list( 2025-08-26T19:56:03.2649915Z ... BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=True) 2025-08-26T19:56:03.2650388Z ... ) 2025-08-26T19:56:03.2650626Z [[0, 1, 2], [3, 4, 5], [6, 7, 8]] 2025-08-26T19:56:03.2650912Z 2025-08-26T19:56:03.2651291Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.2651676Z 2025-08-26T19:56:03.2828024Z msg = Cannot scrape callname=IterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py line=56. 2025-08-26T19:56:03.2829167Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.2829551Z 2025-08-26T19:56:03.2829670Z Iterable-style DataPipe. 2025-08-26T19:56:03.2829847Z 2025-08-26T19:56:03.2830120Z All DataPipes that represent an iterable of data samples should subclass this. 2025-08-26T19:56:03.2830758Z This style of DataPipes is particularly useful when data come from a stream, or 2025-08-26T19:56:03.2831504Z when the number of samples is too large to fit them all in memory. ``IterDataPipe`` is lazily initialized and its 2025-08-26T19:56:03.2832300Z elements are computed only when ``next()`` is called on the iterator of an ``IterDataPipe``. 2025-08-26T19:56:03.2832717Z 2025-08-26T19:56:03.2832967Z All subclasses should overwrite :meth:`__iter__`, which would return an 2025-08-26T19:56:03.2833676Z iterator of samples in this DataPipe. Calling ``__iter__`` of an ``IterDataPipe`` automatically invokes its 2025-08-26T19:56:03.2834614Z method ``reset()``, which by default performs no operation. When writing a custom ``IterDataPipe``, users should 2025-08-26T19:56:03.2835401Z override ``reset()`` if necessary. The common usages include resetting buffers, pointers, 2025-08-26T19:56:03.2836019Z and various state variables within the custom ``IterDataPipe``. 2025-08-26T19:56:03.2836338Z 2025-08-26T19:56:03.2836437Z Note: 2025-08-26T19:56:03.2836777Z Only `one` iterator can be valid for each ``IterDataPipe`` at a time, 2025-08-26T19:56:03.2837636Z and the creation a second iterator will invalidate the first one. This constraint is necessary because 2025-08-26T19:56:03.2838520Z some ``IterDataPipe`` have internal buffers, whose states can become invalid if there are multiple iterators. 2025-08-26T19:56:03.2839311Z The code example below presents details on how this constraint looks in practice. 2025-08-26T19:56:03.2840093Z If you have any feedback related to this constraint, please see `GitHub IterDataPipe Single Iterator Issue`_. 2025-08-26T19:56:03.2840594Z 2025-08-26T19:56:03.2840964Z These DataPipes can be invoked in two ways, using the class constructor or applying their 2025-08-26T19:56:03.2841744Z functional form onto an existing ``IterDataPipe`` (recommended, available to most but not all DataPipes). 2025-08-26T19:56:03.2842589Z You can chain multiple `IterDataPipe` together to form a pipeline that will perform multiple 2025-08-26T19:56:03.2843149Z operations in succession. 2025-08-26T19:56:03.2843342Z 2025-08-26T19:56:03.2843479Z .. _GitHub IterDataPipe Single Iterator Issue: 2025-08-26T19:56:03.2843984Z https://github.com/pytorch/data/issues/45 2025-08-26T19:56:03.2844234Z 2025-08-26T19:56:03.2844319Z Note: 2025-08-26T19:56:03.2844678Z When a subclass is used with :class:`~torch.utils.data.DataLoader`, each 2025-08-26T19:56:03.2845310Z item in the DataPipe will be yielded from the :class:`~torch.utils.data.DataLoader` 2025-08-26T19:56:03.2845934Z iterator. When :attr:`num_workers > 0`, each worker process will have a 2025-08-26T19:56:03.2846527Z different copy of the DataPipe object, so it is often desired to configure 2025-08-26T19:56:03.2847125Z each copy independently to avoid having duplicate data returned from the 2025-08-26T19:56:03.2847735Z workers. :func:`~torch.utils.data.get_worker_info`, when called in a worker 2025-08-26T19:56:03.2848360Z process, returns information about the worker. It can be used in either the 2025-08-26T19:56:03.2849086Z dataset's :meth:`__iter__` method or the :class:`~torch.utils.data.DataLoader` 's 2025-08-26T19:56:03.2849649Z :attr:`worker_init_fn` option to modify each copy's behavior. 2025-08-26T19:56:03.2849963Z 2025-08-26T19:56:03.2850053Z Examples: 2025-08-26T19:56:03.2850279Z General Usage: 2025-08-26T19:56:03.2850538Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.2850945Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T19:56:03.2851389Z >>> dp = IterableWrapper(range(10)) 2025-08-26T19:56:03.2851818Z >>> map_dp_1 = Mapper(dp, lambda x: x + 1) # Using class constructor 2025-08-26T19:56:03.2852239Z >>> map_dp_2 = dp.map( 2025-08-26T19:56:03.2852530Z ... lambda x: x + 1 2025-08-26T19:56:03.2852843Z ... ) # Using functional form (recommended) 2025-08-26T19:56:03.2853194Z >>> list(map_dp_1) 2025-08-26T19:56:03.2853466Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T19:56:03.2853772Z >>> list(map_dp_2) 2025-08-26T19:56:03.2854031Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T19:56:03.2854402Z >>> filter_dp = map_dp_1.filter(lambda x: x % 2 == 0) 2025-08-26T19:56:03.2854777Z >>> list(filter_dp) 2025-08-26T19:56:03.2855050Z [2, 4, 6, 8, 10] 2025-08-26T19:56:03.2855323Z Single Iterator Constraint Example: 2025-08-26T19:56:03.2855776Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T19:56:03.2856242Z >>> source_dp = IterableWrapper(range(10)) 2025-08-26T19:56:03.2856651Z >>> it1 = iter(source_dp) 2025-08-26T19:56:03.2856936Z >>> list(it1) 2025-08-26T19:56:03.2857191Z [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] 2025-08-26T19:56:03.2857501Z >>> it1 = iter(source_dp) 2025-08-26T19:56:03.2857845Z >>> it2 = iter( 2025-08-26T19:56:03.2858091Z ... source_dp 2025-08-26T19:56:03.2858423Z ... ) # The creation of a new iterator invalidates `it1` 2025-08-26T19:56:03.2858796Z >>> next(it2) 2025-08-26T19:56:03.2859037Z 0 2025-08-26T19:56:03.2859343Z >>> next(it1) # Further usage of `it1` will raise a `RunTimeError` 2025-08-26T19:56:03.2859668Z 2025-08-26T19:56:03.2859927Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.2860314Z 2025-08-26T19:56:03.3047055Z msg = Cannot scrape callname=DemultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=375. 2025-08-26T19:56:03.3048206Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.3048750Z 2025-08-26T19:56:03.3049314Z Splits the input DataPipe into multiple child DataPipes, using the given classification function (functional name: ``demux``). 2025-08-26T19:56:03.3050120Z 2025-08-26T19:56:03.3050504Z A list of the child DataPipes is returned from this operation. 2025-08-26T19:56:03.3050934Z 2025-08-26T19:56:03.3051032Z Args: 2025-08-26T19:56:03.3051280Z datapipe: Iterable DataPipe being filtered 2025-08-26T19:56:03.3051727Z num_instances: number of instances of the DataPipe to create 2025-08-26T19:56:03.3052547Z classifier_fn: a function that maps values to an integer within the range ``[0, num_instances - 1]`` or ``None`` 2025-08-26T19:56:03.3053631Z drop_none: defaults to ``False``, if ``True``, the function will skip over elements classified as ``None`` 2025-08-26T19:56:03.3054750Z buffer_size: this defines the maximum number of inputs that the buffer can hold across all child 2025-08-26T19:56:03.3055393Z DataPipes while waiting for their values to be yielded. 2025-08-26T19:56:03.3055871Z Defaults to ``1000``. Use ``-1`` for the unlimited buffer. 2025-08-26T19:56:03.3056158Z 2025-08-26T19:56:03.3056259Z Examples: 2025-08-26T19:56:03.3056513Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T19:56:03.3056923Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:03.3057319Z >>> def odd_or_even(n): 2025-08-26T19:56:03.3057597Z ... return n % 2 2025-08-26T19:56:03.3057897Z >>> source_dp = IterableWrapper(range(5)) 2025-08-26T19:56:03.3058361Z >>> dp1, dp2 = source_dp.demux(num_instances=2, classifier_fn=odd_or_even) 2025-08-26T19:56:03.3058782Z >>> list(dp1) 2025-08-26T19:56:03.3059015Z [0, 2, 4] 2025-08-26T19:56:03.3059239Z >>> list(dp2) 2025-08-26T19:56:03.3059470Z [1, 3] 2025-08-26T19:56:03.3059824Z >>> # It can also filter out any element that gets `None` from the `classifier_fn` 2025-08-26T19:56:03.3060301Z >>> def odd_or_even_no_zero(n): 2025-08-26T19:56:03.3060637Z ... return n % 2 if n != 0 else None 2025-08-26T19:56:03.3060973Z >>> dp1, dp2 = source_dp.demux( 2025-08-26T19:56:03.3061392Z ... num_instances=2, classifier_fn=odd_or_even_no_zero, drop_none=True 2025-08-26T19:56:03.3061821Z ... ) 2025-08-26T19:56:03.3062037Z >>> list(dp1) 2025-08-26T19:56:03.3062268Z [2, 4] 2025-08-26T19:56:03.3062469Z >>> list(dp2) 2025-08-26T19:56:03.3062697Z [1, 3] 2025-08-26T19:56:03.3062821Z 2025-08-26T19:56:03.3063094Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.3063468Z 2025-08-26T19:56:03.3064214Z msg = Cannot scrape callname=MultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=594. 2025-08-26T19:56:03.3065310Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.3065781Z 2025-08-26T19:56:03.3066112Z Yields one element at a time from each of the input Iterable DataPipes (functional name: ``mux``). 2025-08-26T19:56:03.3066548Z 2025-08-26T19:56:03.3066902Z As in, one element from the 1st input DataPipe, then one element from the 2nd DataPipe in the next iteration, 2025-08-26T19:56:03.3067576Z and so on. It ends when the shortest input DataPipe is exhausted. 2025-08-26T19:56:03.3067894Z 2025-08-26T19:56:03.3067977Z Args: 2025-08-26T19:56:03.3068514Z datapipes: Iterable DataPipes that will take turn to yield their elements, until the shortest DataPipe is exhausted 2025-08-26T19:56:03.3069053Z 2025-08-26T19:56:03.3069153Z Example: 2025-08-26T19:56:03.3069396Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T19:56:03.3069824Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:03.3070226Z >>> dp1, dp2, dp3 = ( 2025-08-26T19:56:03.3070525Z ... IterableWrapper(range(3)), 2025-08-26T19:56:03.3070856Z ... IterableWrapper(range(10, 15)), 2025-08-26T19:56:03.3071211Z ... IterableWrapper(range(20, 25)), 2025-08-26T19:56:03.3071574Z ... ) 2025-08-26T19:56:03.3071900Z >>> list(dp1.mux(dp2, dp3)) 2025-08-26T19:56:03.3072186Z [0, 10, 20, 1, 11, 21, 2, 12, 22] 2025-08-26T19:56:03.3072393Z 2025-08-26T19:56:03.3072656Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.3073284Z 2025-08-26T19:56:03.3074265Z msg = Cannot scrape callname=ZipperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=665. 2025-08-26T19:56:03.3075399Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.3075790Z 2025-08-26T19:56:03.3076116Z Aggregates elements into a tuple from each of the input DataPipes (functional name: ``zip``). 2025-08-26T19:56:03.3076547Z 2025-08-26T19:56:03.3076782Z The output is stopped as soon as the shortest input DataPipe is exhausted. 2025-08-26T19:56:03.3077154Z 2025-08-26T19:56:03.3077241Z Args: 2025-08-26T19:56:03.3077528Z *datapipes: Iterable DataPipes being aggregated 2025-08-26T19:56:03.3077793Z 2025-08-26T19:56:03.3077896Z Example: 2025-08-26T19:56:03.3078154Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T19:56:03.3078568Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:03.3078966Z >>> dp1, dp2, dp3 = ( 2025-08-26T19:56:03.3079259Z ... IterableWrapper(range(5)), 2025-08-26T19:56:03.3079606Z ... IterableWrapper(range(10, 15)), 2025-08-26T19:56:03.3079949Z ... IterableWrapper(range(20, 25)), 2025-08-26T19:56:03.3080269Z ... ) 2025-08-26T19:56:03.3080500Z >>> list(dp1.zip(dp2, dp3)) 2025-08-26T19:56:03.3080835Z [(0, 10, 20), (1, 11, 21), (2, 12, 22), (3, 13, 23), (4, 14, 24)] 2025-08-26T19:56:03.3081082Z 2025-08-26T19:56:03.3081342Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.3081730Z 2025-08-26T19:56:03.3082452Z msg = Cannot scrape callname=FileOpenerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/fileopener.py line=18. 2025-08-26T19:56:03.3083540Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.3083939Z 2025-08-26T19:56:03.3084316Z Given pathnames, opens files and yield pathname and file stream in a tuple (functional name: ``open_files``). 2025-08-26T19:56:03.3084831Z 2025-08-26T19:56:03.3084916Z Args: 2025-08-26T19:56:03.3085208Z datapipe: Iterable datapipe that provides pathnames 2025-08-26T19:56:03.3085660Z mode: An optional string that specifies the mode in which 2025-08-26T19:56:03.3086175Z the file is opened by ``open()``. It defaults to ``r``, other options are 2025-08-26T19:56:03.3086681Z ``b`` for reading in binary mode and ``t`` for text mode. 2025-08-26T19:56:03.3087172Z encoding: An optional string that specifies the encoding of the 2025-08-26T19:56:03.3087785Z underlying file. It defaults to ``None`` to match the default encoding of ``open``. 2025-08-26T19:56:03.3088306Z length: Nominal length of the datapipe 2025-08-26T19:56:03.3088552Z 2025-08-26T19:56:03.3088639Z Note: 2025-08-26T19:56:03.3089116Z The opened file handles will be closed by Python's GC periodically. Users can choose 2025-08-26T19:56:03.3089628Z to close them explicitly. 2025-08-26T19:56:03.3089818Z 2025-08-26T19:56:03.3089905Z Example: 2025-08-26T19:56:03.3090129Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.3090441Z >>> from torchdata.datapipes.iter import ( 2025-08-26T19:56:03.3090792Z ... FileLister, 2025-08-26T19:56:03.3091036Z ... FileOpener, 2025-08-26T19:56:03.3091303Z ... StreamReader, 2025-08-26T19:56:03.3091567Z ... ) 2025-08-26T19:56:03.3091912Z >>> dp = FileLister(root=".").filter(lambda fname: fname.endswith(".txt")) 2025-08-26T19:56:03.3092346Z >>> dp = FileOpener(dp) 2025-08-26T19:56:03.3092641Z >>> dp = StreamReader(dp) 2025-08-26T19:56:03.3092929Z >>> list(dp) 2025-08-26T19:56:03.3093210Z [('./abc.txt', 'abc')] 2025-08-26T19:56:03.3093379Z 2025-08-26T19:56:03.3093638Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.3094025Z 2025-08-26T19:56:03.3107319Z msg = Cannot scrape callname=GrouperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py line=155. 2025-08-26T19:56:03.3108391Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:03.3108788Z 2025-08-26T19:56:03.3109287Z Groups data from IterDataPipe by keys from ``group_key_fn``, yielding a ``DataChunk`` with batch size up to ``group_size``. 2025-08-26T19:56:03.3109818Z 2025-08-26T19:56:03.3109941Z (functional name: ``groupby``). 2025-08-26T19:56:03.3110139Z 2025-08-26T19:56:03.3110546Z The samples are read sequentially from the source ``datapipe``, and a batch of samples belonging to the same group 2025-08-26T19:56:03.3111354Z will be yielded as soon as the size of the batch reaches ``group_size``. When the buffer is full, 2025-08-26T19:56:03.3112099Z the DataPipe will yield the largest batch with the same key, provided that its size is larger 2025-08-26T19:56:03.3112878Z than ``guaranteed_group_size``. If its size is smaller, it will be dropped if ``drop_remaining=True``. 2025-08-26T19:56:03.3113337Z 2025-08-26T19:56:03.3113726Z After iterating through the entirety of source ``datapipe``, everything not dropped due to the buffer capacity 2025-08-26T19:56:03.3114569Z will be yielded from the buffer, even if the group sizes are smaller than ``guaranteed_group_size``. 2025-08-26T19:56:03.3115016Z 2025-08-26T19:56:03.3115113Z Args: 2025-08-26T19:56:03.3115358Z datapipe: Iterable datapipe to be grouped 2025-08-26T19:56:03.3115889Z group_key_fn: Function used to generate group key from the data of the source datapipe 2025-08-26T19:56:03.3116532Z keep_key: Option to yield the matching key along with the items in a tuple, 2025-08-26T19:56:03.3117078Z resulting in `(key, [items])` otherwise returning [items] 2025-08-26T19:56:03.3117521Z buffer_size: The size of buffer for ungrouped data 2025-08-26T19:56:03.3118074Z group_size: The max size of each group, a batch is yielded as soon as it reaches this size 2025-08-26T19:56:03.3118822Z guaranteed_group_size: The guaranteed minimum group size to be yielded in case the buffer is full 2025-08-26T19:56:03.3119652Z drop_remaining: Specifies if the group smaller than ``guaranteed_group_size`` will be dropped from buffer 2025-08-26T19:56:03.3120254Z when the buffer is full 2025-08-26T19:56:03.3120442Z 2025-08-26T19:56:03.3120530Z Example: 2025-08-26T19:56:03.3120745Z >>> import os 2025-08-26T19:56:03.3120995Z >>> # xdoctest: +SKIP 2025-08-26T19:56:03.3121351Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:03.3121735Z >>> def group_fn(file): 2025-08-26T19:56:03.3122100Z ... return os.path.basename(file).split(".")[0] 2025-08-26T19:56:03.3122481Z >>> source_dp = IterableWrapper( 2025-08-26T19:56:03.3122863Z ... ["a.png", "b.png", "a.json", "b.json", "a.jpg", "c.json"] 2025-08-26T19:56:03.3123222Z ... ) 2025-08-26T19:56:03.3123489Z >>> dp0 = source_dp.groupby(group_key_fn=group_fn) 2025-08-26T19:56:03.3123838Z >>> list(dp0) 2025-08-26T19:56:03.3124149Z [['a.png', 'a.json', 'a.jpg'], ['b.png', 'b.json'], ['c.json']] 2025-08-26T19:56:03.3124610Z >>> # A group is yielded as soon as its size equals to `group_size` 2025-08-26T19:56:03.3125118Z >>> dp1 = source_dp.groupby(group_key_fn=group_fn, group_size=2) 2025-08-26T19:56:03.3125514Z >>> list(dp1) 2025-08-26T19:56:03.3125823Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T19:56:03.3126465Z >>> # Scenario where `buffer` is full, and group 'a' needs to be yielded since its size > `guaranteed_group_size` 2025-08-26T19:56:03.3127042Z >>> dp2 = source_dp.groupby( 2025-08-26T19:56:03.3127357Z ... group_key_fn=group_fn, 2025-08-26T19:56:03.3127722Z ... buffer_size=3, 2025-08-26T19:56:03.3127995Z ... group_size=3, 2025-08-26T19:56:03.3128269Z ... guaranteed_group_size=2, 2025-08-26T19:56:03.3128572Z ... ) 2025-08-26T19:56:03.3128867Z >>> list(dp2) 2025-08-26T19:56:03.3129191Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T19:56:03.3129472Z 2025-08-26T19:56:03.3129726Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:03.3130110Z 2025-08-26T19:56:03.4568120Z gathering tests 2025-08-26T19:56:03.4579700Z running 731 test(s) 2025-08-26T19:56:03.4597379Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::typename:0, line 1082 <- wrt source file 2025-08-26T19:56:03.4605457Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::typename:0 2025-08-26T19:56:03.4606739Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::is_tensor:0, line 1118 <- wrt source file 2025-08-26T19:56:03.4610307Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::is_tensor:0 2025-08-26T19:56:03.4611754Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_device:0, line 1203 <- wrt source file 2025-08-26T19:56:03.4613654Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_device:0 2025-08-26T19:56:03.4615323Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_tensor_type:0, line 1252 <- wrt source file 2025-08-26T19:56:03.4617329Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_tensor_type:0 2025-08-26T19:56:03.4618582Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_dtype:0, line 1289 <- wrt source file 2025-08-26T19:56:03.4619812Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::set_default_dtype:0 2025-08-26T19:56:03.4621587Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::use_deterministic_algorithms:0, line 1444 <- wrt source file 2025-08-26T19:56:03.4623948Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::use_deterministic_algorithms:0 2025-08-26T19:56:03.4625592Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::compile:0, line 2567 <- wrt source file 2025-08-26T19:56:03.4626720Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::compile:0 2025-08-26T19:56:03.4627973Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0, line 2840 <- wrt source file 2025-08-26T19:56:03.4629487Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/__init__.py::_is_device_backend_autoload_enabled:0 2025-08-26T19:56:03.4630827Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::Generator:0, line 15 <- wrt source file 2025-08-26T19:56:03.4632210Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::Generator:0 2025-08-26T19:56:03.4633569Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::_LinAlgError:0, line 5 <- wrt source file 2025-08-26T19:56:03.4634975Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_C.cpython-313-x86_64-linux-gnu.so::_LinAlgError:0 2025-08-26T19:56:03.4636219Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::custom_op:0, line 55 <- wrt source file 2025-08-26T19:56:03.4637640Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::custom_op:0 2025-08-26T19:56:03.4638754Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl:0, line 138 <- wrt source file 2025-08-26T19:56:03.4639886Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl:0 2025-08-26T19:56:03.4641130Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl_abstract:0, line 208 <- wrt source file 2025-08-26T19:56:03.5048414Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_custom_ops.py::impl_abstract:0 2025-08-26T19:56:03.5050102Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_namedtensor_internals.py::update_names:0, line 118 <- wrt source file 2025-08-26T19:56:03.5051451Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_namedtensor_internals.py::update_names:0 2025-08-26T19:56:03.5052696Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_hook:0, line 649 <- wrt source file 2025-08-26T19:56:03.5061290Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_hook:0 2025-08-26T19:56:03.5062634Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0, line 706 <- wrt source file 2025-08-26T19:56:03.5081426Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.register_post_accumulate_grad_hook:0 2025-08-26T19:56:03.5082745Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.refine_names:0, line 1333 <- wrt source file 2025-08-26T19:56:03.5193974Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.refine_names:0 2025-08-26T19:56:03.5197829Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.align_to:0, line 1378 <- wrt source file 2025-08-26T19:56:03.5202404Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.align_to:0 2025-08-26T19:56:03.5203581Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.rename:0, line 1451 <- wrt source file 2025-08-26T19:56:03.5209620Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.rename:0 2025-08-26T19:56:03.5210814Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0, line 1481 <- wrt source file 2025-08-26T19:56:03.5215273Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py::Tensor.to_sparse_coo:0 2025-08-26T19:56:03.5216496Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor_str.py::set_printoptions:0, line 53 <- wrt source file 2025-08-26T19:56:03.5235985Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor_str.py::set_printoptions:0 2025-08-26T19:56:03.5237235Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_tensors:0, line 64 <- wrt source file 2025-08-26T19:56:03.5242870Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_tensors:0 2025-08-26T19:56:03.5244102Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_shapes:0, line 92 <- wrt source file 2025-08-26T19:56:03.5246204Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::broadcast_shapes:0 2025-08-26T19:56:03.5247480Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::split:0, line 144 <- wrt source file 2025-08-26T19:56:03.5259079Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::split:0 2025-08-26T19:56:03.5260215Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::einsum:0, line 258 <- wrt source file 2025-08-26T19:56:03.5275618Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::einsum:0 2025-08-26T19:56:03.5276856Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_unique_consecutive_impl:0, line 992 <- wrt source file 2025-08-26T19:56:03.5295465Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_unique_consecutive_impl:0 2025-08-26T19:56:03.5296722Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::tensordot:0, line 1267 <- wrt source file 2025-08-26T19:56:03.5306242Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::tensordot:0 2025-08-26T19:56:03.5307431Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cartesian_prod:0, line 1351 <- wrt source file 2025-08-26T19:56:03.5313618Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cartesian_prod:0 2025-08-26T19:56:03.5314819Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::block_diag:0, line 1385 <- wrt source file 2025-08-26T19:56:03.5323793Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::block_diag:0 2025-08-26T19:56:03.5324953Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cdist:0, line 1441 <- wrt source file 2025-08-26T19:56:03.5338432Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::cdist:0 2025-08-26T19:56:03.5339577Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_1d:0, line 1482 <- wrt source file 2025-08-26T19:56:03.5355938Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_1d:0 2025-08-26T19:56:03.5357125Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_2d:0, line 1520 <- wrt source file 2025-08-26T19:56:03.5373943Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_2d:0 2025-08-26T19:56:03.5375112Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_3d:0, line 1560 <- wrt source file 2025-08-26T19:56:03.5396284Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::atleast_3d:0 2025-08-26T19:56:03.5397411Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::norm:0, line 1735 <- wrt source file 2025-08-26T19:56:03.5429586Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::norm:0 2025-08-26T19:56:03.5430769Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::unravel_index:0, line 1903 <- wrt source file 2025-08-26T19:56:03.5457061Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::unravel_index:0 2025-08-26T19:56:03.5458911Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::chain_matmul:0, line 2003 <- wrt source file 2025-08-26T19:56:03.5460864Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::chain_matmul:0 2025-08-26T19:56:03.5462102Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_lu_impl:0, line 2104 <- wrt source file 2025-08-26T19:56:03.5463268Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py::_lu_impl:0 2025-08-26T19:56:03.5464898Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::list:0, line 473 <- wrt source file 2025-08-26T19:56:03.5466066Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::list:0 2025-08-26T19:56:03.5467105Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::help:0, line 533 <- wrt source file 2025-08-26T19:56:03.5468157Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py::help:0 2025-08-26T19:56:03.5469266Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.define:0, line 153 <- wrt source file 2025-08-26T19:56:03.5470458Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.define:0 2025-08-26T19:56:03.5471715Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library._impl_with_aoti_compile:0, line 247 <- wrt source file 2025-08-26T19:56:03.5476497Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library._impl_with_aoti_compile:0 2025-08-26T19:56:03.5477750Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.impl:0, line 307 <- wrt source file 2025-08-26T19:56:03.5480827Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::Library.impl:0 2025-08-26T19:56:03.5481950Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::define:0, line 512 <- wrt source file 2025-08-26T19:56:03.5502544Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::define:0 2025-08-26T19:56:03.5503625Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::impl:0, line 618 <- wrt source file 2025-08-26T19:56:03.5518041Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::impl:0 2025-08-26T19:56:03.5519901Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_kernel:0, line 799 <- wrt source file 2025-08-26T19:56:03.5521104Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_kernel:0 2025-08-26T19:56:03.5522281Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_autocast:0, line 867 <- wrt source file 2025-08-26T19:56:03.5523595Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_autocast:0 2025-08-26T19:56:03.5524841Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_torch_dispatch:0, line 1232 <- wrt source file 2025-08-26T19:56:03.5612709Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_torch_dispatch:0 2025-08-26T19:56:03.5613940Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_vmap:0, line 1321 <- wrt source file 2025-08-26T19:56:03.5766460Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py::register_vmap:0 2025-08-26T19:56:03.5767693Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_ignored_functions:0, line 116 <- wrt source file 2025-08-26T19:56:03.5773016Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_ignored_functions:0 2025-08-26T19:56:03.5774443Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_testing_overrides:0, line 422 <- wrt source file 2025-08-26T19:56:03.5811864Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::get_testing_overrides:0 2025-08-26T19:56:03.5813257Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::wrap_torch_function:0, line 1577 <- wrt source file 2025-08-26T19:56:03.5815013Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::wrap_torch_function:0 2025-08-26T19:56:03.5816277Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::handle_torch_function:0, line 1712 <- wrt source file 2025-08-26T19:56:03.5818017Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::handle_torch_function:0 2025-08-26T19:56:03.5819332Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_method_or_property:0, line 1960 <- wrt source file 2025-08-26T19:56:03.5845168Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_method_or_property:0 2025-08-26T19:56:03.5846444Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_like:0, line 1979 <- wrt source file 2025-08-26T19:56:03.5852373Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/overrides.py::is_tensor_like:0 2025-08-26T19:56:03.5854426Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/quasirandom.py::SobolEngine:0, line 39 <- wrt source file 2025-08-26T19:56:03.5856193Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/quasirandom.py::SobolEngine:0 2025-08-26T19:56:03.5857590Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::add_safe_globals:0, line 299 <- wrt source file 2025-08-26T19:56:03.5858872Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::add_safe_globals:0 2025-08-26T19:56:03.5860990Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::safe_globals:0, line 324 <- wrt source file 2025-08-26T19:56:03.5862629Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::safe_globals:0 2025-08-26T19:56:03.5864124Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::skip_data:0, line 400 <- wrt source file 2025-08-26T19:56:03.5865479Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::skip_data:0 2025-08-26T19:56:03.5866796Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::register_package:0, line 472 <- wrt source file 2025-08-26T19:56:03.5868073Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::register_package:0 2025-08-26T19:56:03.5869266Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::save:0, line 950 <- wrt source file 2025-08-26T19:56:03.5870428Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py::save:0 2025-08-26T19:56:03.5871602Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/torch_version.py::TorchVersion:0, line 19 <- wrt source file 2025-08-26T19:56:03.5872830Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/torch_version.py::TorchVersion:0 2025-08-26T19:56:03.5874125Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_mode_options:0, line 320 <- wrt source file 2025-08-26T19:56:03.5875435Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_mode_options:0 2025-08-26T19:56:03.5876697Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_options:0, line 357 <- wrt source file 2025-08-26T19:56:03.5878590Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/__init__.py::list_options:0 2025-08-26T19:56:03.5879909Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::current_accelerator:0, line 113 <- wrt source file 2025-08-26T19:56:03.5883816Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::current_accelerator:0 2025-08-26T19:56:03.5885259Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::device_index:0, line 249 <- wrt source file 2025-08-26T19:56:03.5886574Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py::device_index:0 2025-08-26T19:56:03.5887833Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::allow_in_graph:0, line 125 <- wrt source file 2025-08-26T19:56:03.5889176Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::allow_in_graph:0 2025-08-26T19:56:03.5890467Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::substitute_in_graph:0, line 181 <- wrt source file 2025-08-26T19:56:04.7430986Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::substitute_in_graph:0 2025-08-26T19:56:04.7432423Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::wrap_numpy:0, line 411 <- wrt source file 2025-08-26T19:56:04.7433743Z * SKIPPED: 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::is_exporting:0 2025-08-26T19:56:04.7443941Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0, line 497 <- wrt source file 2025-08-26T19:56:04.7445394Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::save_cache_artifacts:0 2025-08-26T19:56:04.7446861Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0, line 512 <- wrt source file 2025-08-26T19:56:04.7448303Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/compiler/__init__.py::load_cache_artifacts:0 2025-08-26T19:56:04.7449737Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py::_compile_kernel:0, line 1760 <- wrt source file 2025-08-26T19:56:04.7450988Z * SKIPPED: 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DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.add_done_callback:0, line 197 <- wrt source file 2025-08-26T19:56:04.7460943Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.add_done_callback:0 2025-08-26T19:56:04.7462338Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.set_exception:0, line 261 <- wrt source file 2025-08-26T19:56:04.7463766Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::Future.set_exception:0 2025-08-26T19:56:04.7465020Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::collect_all:0, line 295 <- wrt source file 2025-08-26T19:56:04.7466260Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py::collect_all:0 2025-08-26T19:56:04.7467416Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/__init__.py::annotate:0, line 147 <- wrt source file 2025-08-26T19:56:04.7468581Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/__init__.py::annotate:0 2025-08-26T19:56:04.7469846Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0, line 22 <- wrt source file 2025-08-26T19:56:04.7471239Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/monitor/__init__.py::TensorboardEventHandler:0 2025-08-26T19:56:04.7472579Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::as_nested_tensor:0, line 61 <- wrt source file 2025-08-26T19:56:04.7502889Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::as_nested_tensor:0 2025-08-26T19:56:04.7504135Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor:0, line 240 <- wrt source file 2025-08-26T19:56:04.7508749Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor:0 2025-08-26T19:56:04.7509955Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::narrow:0, line 315 <- wrt source file 2025-08-26T19:56:04.7588674Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::narrow:0 2025-08-26T19:56:04.7591213Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0, line 405 <- wrt source file 2025-08-26T19:56:04.7614166Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::nested_tensor_from_jagged:0 2025-08-26T19:56:04.7616747Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::masked_select:0, line 481 <- wrt source file 2025-08-26T19:56:04.7636284Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py::masked_select:0 2025-08-26T19:56:04.7639279Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0, line 475 <- wrt source file 2025-08-26T19:56:04.7649257Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py::check_sparse_tensor_invariants:0 2025-08-26T19:56:04.7652007Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0, line 349 <- wrt source file 2025-08-26T19:56:04.7654742Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/decorators.py::substitute_in_graph:0 2025-08-26T19:56:04.7657551Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0, line 322 <- wrt source file 2025-08-26T19:56:04.7660559Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_dynamo/variables/base.py::VariableTracker.python_type:0 2025-08-26T19:56:04.7663474Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0, line 1410 <- wrt source file 2025-08-26T19:56:04.7666416Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/utils.py::register_module_as_pytree_input_node:0 2025-08-26T19:56:04.7669553Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0, line 158 <- wrt source file 2025-08-26T19:56:04.7672860Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_export/wrappers.py::mark_subclass_constructor_exportable_experimental:0 2025-08-26T19:56:04.7675756Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/aot_autograd.py::aot_function:0, line 768 <- wrt source file 2025-08-26T19:56:04.8066888Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/aot_autograd.py::aot_function:0 2025-08-26T19:56:04.8069672Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0, line 184 <- wrt source file 2025-08-26T19:56:04.8072840Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/benchmark_utils.py::benchmark_utilization:0 2025-08-26T19:56:04.8075523Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::vjp:0, line 233 <- wrt source file 2025-08-26T19:56:04.8119625Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::vjp:0 2025-08-26T19:56:04.8120979Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacrev:0, line 475 <- wrt source file 2025-08-26T19:56:04.8197517Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacrev:0 2025-08-26T19:56:04.8198822Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jvp:0, line 1023 <- wrt source file 2025-08-26T19:56:04.8921503Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jvp:0 2025-08-26T19:56:04.8924290Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0, line 1181 <- wrt source file 2025-08-26T19:56:04.9001661Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::jacfwd:0 2025-08-26T19:56:04.9004450Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::hessian:0, line 1341 <- wrt source file 2025-08-26T19:56:04.9035326Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::hessian:0 2025-08-26T19:56:04.9038175Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::functionalize:0, line 1505 <- wrt source file 2025-08-26T19:56:04.9041026Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::functionalize:0 2025-08-26T19:56:04.9043712Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::linearize:0, line 1704 <- wrt source file 2025-08-26T19:56:04.9281312Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/eager_transforms.py::linearize:0 2025-08-26T19:56:04.9284028Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/functional_call.py::functional_call:0, line 36 <- wrt source file 2025-08-26T19:56:04.9286820Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/functional_call.py::functional_call:0 2025-08-26T19:56:04.9289485Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/fx_minifier.py::minifier:0, line 194 <- wrt source file 2025-08-26T19:56:04.9292086Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/fx_minifier.py::minifier:0 2025-08-26T19:56:04.9294949Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0, line 1131 <- wrt source file 2025-08-26T19:56:04.9298133Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::CompilerWrapper.post_compile:0 2025-08-26T19:56:04.9301280Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0, line 1186 <- wrt source file 2025-08-26T19:56:04.9304484Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/_aot_autograd/schemas.py::InductorWrapper.post_compile:0 2025-08-26T19:56:04.9307485Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0, line 186 <- wrt source file 2025-08-26T19:56:04.9310601Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::associative_scan:0 2025-08-26T19:56:04.9313598Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0, line 322 <- wrt source file 2025-08-26T19:56:04.9316707Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/associative_scan.py::generic_associative_scan:0 2025-08-26T19:56:04.9319406Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/cond.py::cond:0, line 155 <- wrt source file 2025-08-26T19:56:04.9321869Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/cond.py::cond:0 2025-08-26T19:56:04.9324474Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0, line 80 <- wrt source file 2025-08-26T19:56:04.9327399Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/flat_apply.py::FlatApply.__call__:0 2025-08-26T19:56:04.9330026Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/map.py::map:0, line 79 <- wrt source file 2025-08-26T19:56:04.9332559Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/map.py::map:0 2025-08-26T19:56:04.9334929Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::scan:0, line 156 <- wrt source file 2025-08-26T19:56:04.9337502Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::scan:0 2025-08-26T19:56:04.9340054Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0, line 474 <- wrt source file 2025-08-26T19:56:04.9342760Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_higher_order_ops/scan.py::ScanAutogradOp:0 2025-08-26T19:56:04.9345421Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/codecache.py::WritableTempFile:0, line 372 <- wrt source file 2025-08-26T19:56:04.9348117Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/codecache.py::WritableTempFile:0 2025-08-26T19:56:04.9350946Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0, line 1721 <- wrt source file 2025-08-26T19:56:04.9354029Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/cpp_builder.py::get_name_and_dir_from_output_file_path:0 2025-08-26T19:56:04.9356997Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0, line 3418 <- wrt source file 2025-08-26T19:56:04.9359903Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/select_algorithm.py::add_preprocessing_fn:0 2025-08-26T19:56:04.9362843Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/template_registry.py::register_template_heuristic:0, line 45 <- wrt source file 2025-08-26T19:56:04.9365929Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_inductor/template_registry.py::register_template_heuristic:0 2025-08-26T19:56:04.9368617Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::custom_op:0, line 98 <- wrt source file 2025-08-26T19:56:04.9966251Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::custom_op:0 2025-08-26T19:56:04.9967678Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0, line 238 <- wrt source file 2025-08-26T19:56:05.0056964Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.set_kernel_enabled:0 2025-08-26T19:56:05.0058455Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0, line 307 <- wrt source file 2025-08-26T19:56:05.0059941Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_kernel:0 2025-08-26T19:56:05.0061367Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0, line 541 <- wrt source file 2025-08-26T19:56:05.0231960Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autograd:0 2025-08-26T19:56:05.0233404Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0, line 709 <- wrt source file 2025-08-26T19:56:05.0403899Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_vmap:0 2025-08-26T19:56:05.0405840Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0, line 795 <- wrt source file 2025-08-26T19:56:05.0407334Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py::CustomOpDef.register_autocast:0 2025-08-26T19:56:05.0408762Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0, line 230 <- wrt source file 2025-08-26T19:56:05.0410296Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_class_registry.py::register_fake_class:0 2025-08-26T19:56:05.0411693Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0, line 175 <- wrt source file 2025-08-26T19:56:05.0482497Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_impl.py::FakeImplCtx.new_dynamic_size:0 2025-08-26T19:56:05.0483850Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/infer_schema.py::infer_schema:0, line 51 <- wrt source file 2025-08-26T19:56:05.0488578Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/infer_schema.py::infer_schema:0 2025-08-26T19:56:05.0489957Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_logging/_internal.py::set_logs:0, line 459 <- wrt source file 2025-08-26T19:56:05.0491196Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_logging/_internal.py::set_logs:0 2025-08-26T19:56:05.0492432Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_equal:0, line 171 <- wrt source file 2025-08-26T19:56:05.0527843Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_equal:0 2025-08-26T19:56:05.0529227Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0, line 1008 <- wrt source file 2025-08-26T19:56:05.0584529Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_less:0 2025-08-26T19:56:05.0586002Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0, line 1073 <- wrt source file 2025-08-26T19:56:05.0587399Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_string_equal:0 2025-08-26T19:56:05.0588736Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0, line 1294 <- wrt source file 2025-08-26T19:56:05.0633966Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_allclose:0 2025-08-26T19:56:05.0635369Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0, line 1360 <- wrt source file 2025-08-26T19:56:05.0637627Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_almost_equal_nulp:0 2025-08-26T19:56:05.0639142Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0, line 1423 <- wrt source file 2025-08-26T19:56:05.0642190Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_array_max_ulp:0 2025-08-26T19:56:05.0643499Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0, line 1468 <- wrt source file 2025-08-26T19:56:05.0644894Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::nulp_diff:0 2025-08-26T19:56:05.0646155Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_warns:0, line 1578 <- wrt source file 2025-08-26T19:56:05.0647721Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py::assert_warns:0 2025-08-26T19:56:05.0649147Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims/context.py::TorchRefsMode:0, line 95 <- wrt source file 2025-08-26T19:56:05.0650665Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims/context.py::TorchRefsMode:0 2025-08-26T19:56:05.0652053Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/amp/grad_scaler.py::GradScaler:0, line 64 <- wrt source file 2025-08-26T19:56:05.0653303Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/amp/grad_scaler.py::GradScaler:0 2025-08-26T19:56:05.0654672Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0, line 30 <- wrt source file 2025-08-26T19:56:05.0656213Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/qat/modules/linear_relu.py::LinearReLU:0 2025-08-26T19:56:05.0657828Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0, line 24 <- wrt source file 2025-08-26T19:56:05.0659561Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/dynamic/modules/linear_relu.py::LinearReLU:0 2025-08-26T19:56:05.0661199Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0, line 25 <- wrt source file 2025-08-26T19:56:05.0663001Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearReLU:0 2025-08-26T19:56:05.0664629Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0, line 67 <- wrt source file 2025-08-26T19:56:05.0666397Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearLeakyReLU:0 2025-08-26T19:56:05.0668023Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0, line 142 <- wrt source file 2025-08-26T19:56:05.0669646Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/intrinsic/quantized/modules/linear_relu.py::LinearTanh:0 2025-08-26T19:56:05.0671119Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0, line 30 <- wrt source file 2025-08-26T19:56:05.0673101Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTMCell:0 2025-08-26T19:56:05.0674526Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0, line 413 <- wrt source file 2025-08-26T19:56:05.0705366Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantizable/modules/rnn.py::LSTM:0 2025-08-26T19:56:05.0707398Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0, line 211 <- wrt source file 2025-08-26T19:56:05.0708915Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv1d:0 2025-08-26T19:56:05.0710386Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0, line 283 <- wrt source file 2025-08-26T19:56:05.0711728Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv2d:0 2025-08-26T19:56:05.0713028Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0, line 359 <- wrt source file 2025-08-26T19:56:05.0714366Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/functional.py::conv3d:0 2025-08-26T19:56:05.0715683Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0, line 95 <- wrt source file 2025-08-26T19:56:05.0717080Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::Quantize:0 2025-08-26T19:56:05.0718477Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0, line 145 <- wrt source file 2025-08-26T19:56:05.0719974Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/__init__.py::DeQuantize:0 2025-08-26T19:56:05.0721818Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0, line 43 <- wrt source file 2025-08-26T19:56:05.0723414Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv1d:0 2025-08-26T19:56:05.0725118Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0, line 124 <- wrt source file 2025-08-26T19:56:05.0726590Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv2d:0 2025-08-26T19:56:05.0728057Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0, line 209 <- wrt source file 2025-08-26T19:56:05.0729738Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::Conv3d:0 2025-08-26T19:56:05.0731412Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0, line 296 <- wrt source file 2025-08-26T19:56:05.0733057Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose1d:0 2025-08-26T19:56:05.0734602Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0, line 378 <- wrt source file 2025-08-26T19:56:05.0736185Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose2d:0 2025-08-26T19:56:05.0737864Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0, line 460 <- wrt source file 2025-08-26T19:56:05.0739444Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/conv.py::ConvTranspose3d:0 2025-08-26T19:56:05.0741021Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0, line 30 <- wrt source file 2025-08-26T19:56:05.0742512Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/linear.py::Linear:0 2025-08-26T19:56:05.0744027Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0, line 515 <- wrt source file 2025-08-26T19:56:05.0745464Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTM:0 2025-08-26T19:56:05.0746839Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0, line 801 <- wrt source file 2025-08-26T19:56:05.0748264Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRU:0 2025-08-26T19:56:05.0749684Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0, line 1206 <- wrt source file 2025-08-26T19:56:05.0751153Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::RNNCell:0 2025-08-26T19:56:05.0752600Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0, line 1273 <- wrt source file 2025-08-26T19:56:05.0754077Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::LSTMCell:0 2025-08-26T19:56:05.0755500Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0, line 1326 <- wrt source file 2025-08-26T19:56:05.0756960Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/dynamic/modules/rnn.py::GRUCell:0 2025-08-26T19:56:05.0758364Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0, line 36 <- wrt source file 2025-08-26T19:56:05.0759793Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/activation.py::ReLU6:0 2025-08-26T19:56:05.0761143Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0, line 505 <- wrt source file 2025-08-26T19:56:05.0762493Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv2d:0 2025-08-26T19:56:05.0763801Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0, line 635 <- wrt source file 2025-08-26T19:56:05.0765198Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::Conv3d:0 2025-08-26T19:56:05.0766582Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0, line 892 <- wrt source file 2025-08-26T19:56:05.0768055Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose1d:0 2025-08-26T19:56:05.0769566Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0, line 1014 <- wrt source file 2025-08-26T19:56:05.0771044Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose2d:0 2025-08-26T19:56:05.0772571Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0, line 1140 <- wrt source file 2025-08-26T19:56:05.0774054Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py::ConvTranspose3d:0 2025-08-26T19:56:05.0775635Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0, line 111 <- wrt source file 2025-08-26T19:56:05.0777173Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::Embedding:0 2025-08-26T19:56:05.0778755Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0, line 275 <- wrt source file 2025-08-26T19:56:05.0789690Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/embedding_ops.py::EmbeddingBag:0 2025-08-26T19:56:05.0791242Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0, line 23 <- wrt source file 2025-08-26T19:56:05.0795907Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::FloatFunctional:0 2025-08-26T19:56:05.0797501Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0, line 176 <- wrt source file 2025-08-26T19:56:05.0800928Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/functional_modules.py::QFunctional:0 2025-08-26T19:56:05.0802673Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0, line 138 <- wrt source file 2025-08-26T19:56:05.0804073Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/linear.py::Linear:0 2025-08-26T19:56:05.0805665Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0, line 55 <- wrt source file 2025-08-26T19:56:05.0807489Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_sparsifier/base_data_sparsifier.py::BaseDataSparsifier:0 2025-08-26T19:56:05.0809164Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0, line 24 <- wrt source file 2025-08-26T19:56:05.0836005Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/scheduler/lambda_scheduler.py::LambdaSL:0 2025-08-26T19:56:05.0837825Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0, line 47 <- wrt source file 2025-08-26T19:56:05.0839548Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py::BaseSparsifier:0 2025-08-26T19:56:05.0840999Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0, line 176 <- wrt source file 2025-08-26T19:56:05.0842408Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuse_modules.py::fuse_modules:0 2025-08-26T19:56:05.0843837Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0, line 31 <- wrt source file 2025-08-26T19:56:05.0851539Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn:0 2025-08-26T19:56:05.0854600Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0, line 76 <- wrt source file 2025-08-26T19:56:05.0859390Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_conv_bn_relu:0 2025-08-26T19:56:05.0862439Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0, line 130 <- wrt source file 2025-08-26T19:56:05.0866291Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_linear_bn:0 2025-08-26T19:56:05.0869415Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0, line 163 <- wrt source file 2025-08-26T19:56:05.0873630Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fuser_method_mappings.py::fuse_convtranspose_bn:0 2025-08-26T19:56:05.0876516Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_args:0, line 110 <- wrt source file 2025-08-26T19:56:05.0879222Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_args:0 2025-08-26T19:56:05.0881957Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0, line 132 <- wrt source file 2025-08-26T19:56:05.0884849Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/observer.py::_with_callable_args:0 2025-08-26T19:56:05.0887564Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0, line 218 <- wrt source file 2025-08-26T19:56:05.0890318Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::fuse_fx:0 2025-08-26T19:56:05.0893011Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0, line 288 <- wrt source file 2025-08-26T19:56:05.0895766Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_fx:0 2025-08-26T19:56:05.0898503Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0, line 427 <- wrt source file 2025-08-26T19:56:05.0901364Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::prepare_qat_fx:0 2025-08-26T19:56:05.0904115Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0, line 608 <- wrt source file 2025-08-26T19:56:05.0906954Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_fx:0 2025-08-26T19:56:05.0909797Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0, line 668 <- wrt source file 2025-08-26T19:56:05.0912832Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::convert_to_reference_fx:0 2025-08-26T19:56:05.0915968Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0, line 720 <- wrt source file 2025-08-26T19:56:05.0919268Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_fx.py::_convert_to_reference_decomposed_fx:0 2025-08-26T19:56:05.0922290Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0, line 51 <- wrt source file 2025-08-26T19:56:05.0925201Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_pt2e:0 2025-08-26T19:56:05.0928047Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0, line 130 <- wrt source file 2025-08-26T19:56:05.0931091Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::prepare_qat_pt2e:0 2025-08-26T19:56:05.0933984Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0, line 228 <- wrt source file 2025-08-26T19:56:05.0936859Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/quantize_pt2e.py::convert_pt2e:0 2025-08-26T19:56:05.0939773Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0, line 172 <- wrt source file 2025-08-26T19:56:05.0942542Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::get_combined_dict:0 2025-08-26T19:56:05.0945255Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0, line 544 <- wrt source file 2025-08-26T19:56:05.0948047Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_path_of_module:0 2025-08-26T19:56:05.0950827Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0, line 566 <- wrt source file 2025-08-26T19:56:05.0953667Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_signature_locals:0 2025-08-26T19:56:05.0956435Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0, line 580 <- wrt source file 2025-08-26T19:56:05.0959227Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_default_kwargs:0 2025-08-26T19:56:05.0961985Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0, line 602 <- wrt source file 2025-08-26T19:56:05.0964773Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_normalize_kwargs:0 2025-08-26T19:56:05.0967483Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0, line 729 <- wrt source file 2025-08-26T19:56:05.0970310Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/utils.py::_get_num_pos_args:0 2025-08-26T19:56:05.0973390Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0, line 85 <- wrt source file 2025-08-26T19:56:05.0976692Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/onednn.py::_fuse_linear_bn_leaky_relu:0 2025-08-26T19:56:05.0979952Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0, line 102 <- wrt source file 2025-08-26T19:56:05.0983260Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_get_reduction_params:0 2025-08-26T19:56:05.0986462Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0, line 148 <- wrt source file 2025-08-26T19:56:05.0989787Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/_affine_quantization.py::_register_custom_op:0 2025-08-26T19:56:05.0992930Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0, line 188 <- wrt source file 2025-08-26T19:56:05.0996123Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/prepare.py::_get_edge_or_node_to_group_id:0 2025-08-26T19:56:05.0999461Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0, line 436 <- wrt source file 2025-08-26T19:56:05.1002853Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/pt2e/utils.py::_replace_literals_with_new_placeholders:0 2025-08-26T19:56:05.1005818Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0, line 28 <- wrt source file 2025-08-26T19:56:05.1008498Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/anomaly_mode.py::detect_anomaly:0 2025-08-26T19:56:05.1011099Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::make_dual:0, line 82 <- wrt source file 2025-08-26T19:56:05.1013613Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::make_dual:0 2025-08-26T19:56:05.1016106Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::unpack_dual:0, line 151 <- wrt source file 2025-08-26T19:56:05.1018687Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::unpack_dual:0 2025-08-26T19:56:05.1021207Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::dual_level:0, line 187 <- wrt source file 2025-08-26T19:56:05.1023746Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/forward_ad.py::dual_level:0 2025-08-26T19:56:05.1026455Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0, line 71 <- wrt source file 2025-08-26T19:56:05.1029420Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_backward:0 2025-08-26T19:56:05.1032324Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0, line 115 <- wrt source file 2025-08-26T19:56:05.1035245Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.save_for_forward:0 2025-08-26T19:56:05.1038241Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0, line 167 <- wrt source file 2025-08-26T19:56:05.1041043Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_dirty:0 2025-08-26T19:56:05.1043958Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0, line 214 <- wrt source file 2025-08-26T19:56:05.1047054Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.mark_non_differentiable:0 2025-08-26T19:56:05.1050114Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0, line 243 <- wrt source file 2025-08-26T19:56:05.1053181Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::FunctionCtx.set_materialize_grads:0 2025-08-26T19:56:05.1055960Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::Function:0, line 485 <- wrt source file 2025-08-26T19:56:05.1058438Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/function.py::Function:0 2025-08-26T19:56:05.1060821Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vjp:0, line 293 <- wrt source file 2025-08-26T19:56:05.1063369Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vjp:0 2025-08-26T19:56:05.1065751Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jvp:0, line 395 <- wrt source file 2025-08-26T19:56:05.1068160Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jvp:0 2025-08-26T19:56:05.1070592Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jacobian:0, line 630 <- wrt source file 2025-08-26T19:56:05.1073112Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::jacobian:0 2025-08-26T19:56:05.1075567Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hessian:0, line 894 <- wrt source file 2025-08-26T19:56:05.1078070Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hessian:0 2025-08-26T19:56:05.1080490Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vhp:0, line 1010 <- wrt source file 2025-08-26T19:56:05.1082920Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::vhp:0 2025-08-26T19:56:05.1085295Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hvp:0, line 1109 <- wrt source file 2025-08-26T19:56:05.1087769Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/functional.py::hvp:0 2025-08-26T19:56:05.1090159Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::no_grad:0, line 50 <- wrt source file 2025-08-26T19:56:05.1092594Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::no_grad:0 2025-08-26T19:56:05.1095048Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::enable_grad:0, line 108 <- wrt source file 2025-08-26T19:56:05.1097576Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::enable_grad:0 2025-08-26T19:56:05.1100104Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0, line 166 <- wrt source file 2025-08-26T19:56:05.1102835Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::set_grad_enabled:0 2025-08-26T19:56:05.1105400Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::inference_mode:0, line 238 <- wrt source file 2025-08-26T19:56:05.1108016Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/grad_mode.py::inference_mode:0 2025-08-26T19:56:05.1121237Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.name:0, line 53 <- wrt source file 2025-08-26T19:56:05.1123701Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.name:0 2025-08-26T19:56:05.1126167Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_hook:0, line 110 <- wrt source file 2025-08-26T19:56:05.1128973Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_hook:0 2025-08-26T19:56:05.1131597Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_prehook:0, line 147 <- wrt source file 2025-08-26T19:56:05.1134292Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::Node.register_prehook:0 2025-08-26T19:56:05.1136996Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0, line 283 <- wrt source file 2025-08-26T19:56:05.1139831Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::saved_tensors_hooks:0 2025-08-26T19:56:05.1142295Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::save_on_cpu:0, line 353 <- wrt source file 2025-08-26T19:56:05.1144750Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::save_on_cpu:0 2025-08-26T19:56:05.1147347Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::disable_saved_tensors_hooks:0, line 410 <- wrt source file 2025-08-26T19:56:05.1150150Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::disable_saved_tensors_hooks:0 2025-08-26T19:56:05.1152879Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::register_multi_grad_hook:0, line 487 <- wrt source file 2025-08-26T19:56:05.1155606Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::register_multi_grad_hook:0 2025-08-26T19:56:05.1158368Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0, line 753 <- wrt source file 2025-08-26T19:56:05.1161249Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/graph.py::allow_mutation_on_saved_tensors:0 2025-08-26T19:56:05.1163874Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::profile:0, line 182 <- wrt source file 2025-08-26T19:56:05.1166328Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::profile:0 2025-08-26T19:56:05.1168747Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_itt:0, line 880 <- wrt source file 2025-08-26T19:56:05.1171261Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_itt:0 2025-08-26T19:56:05.1173691Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_nvtx:0, line 953 <- wrt source file 2025-08-26T19:56:05.1176289Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py::emit_nvtx:0 2025-08-26T19:56:05.1178700Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_register_buffer:0, line 42 <- wrt source file 2025-08-26T19:56:05.1181152Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_register_buffer:0 2025-08-26T19:56:05.1183587Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0, line 58 <- wrt source file 2025-08-26T19:56:05.1186068Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::gds_deregister_buffer:0 2025-08-26T19:56:05.1188383Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::GdsFile:0, line 85 <- wrt source file 2025-08-26T19:56:05.1190665Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/gds.py::GdsFile:0 2025-08-26T19:56:05.1193007Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0, line 114 <- wrt source file 2025-08-26T19:56:05.1195491Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:0 2025-08-26T19:56:05.1198037Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1, line 125 <- wrt source file 2025-08-26T19:56:05.1200525Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:1 2025-08-26T19:56:05.1202970Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2, line 140 <- wrt source file 2025-08-26T19:56:05.1205464Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_jit_fn:2 2025-08-26T19:56:05.1208062Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0, line 173 <- wrt source file 2025-08-26T19:56:05.1210917Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/jiterator.py::_create_multi_output_jit_fn:0 2025-08-26T19:56:05.1213433Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/profiler.py::profile:0, line 75 <- wrt source file 2025-08-26T19:56:05.1215798Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/profiler.py::profile:0 2025-08-26T19:56:05.1218284Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0, line 431 <- wrt source file 2025-08-26T19:56:05.1220953Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh:0 2025-08-26T19:56:05.1223730Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh.get_local_rank:0, line 975 <- wrt source file 2025-08-26T19:56:05.1226707Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::DeviceMesh.get_local_rank:0 2025-08-26T19:56:05.1229560Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0, line 1121 <- wrt source file 2025-08-26T19:56:05.1232350Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py::init_device_mesh:0 2025-08-26T19:56:05.1235196Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0, line 2578 <- wrt source file 2025-08-26T19:56:05.1238414Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_coalescing_manager:0 2025-08-26T19:56:05.1241318Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0, line 2680 <- wrt source file 2025-08-26T19:56:05.1244214Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::_time_estimator:0 2025-08-26T19:56:05.1247065Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0, line 3147 <- wrt source file 2025-08-26T19:56:05.1250061Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_object:0 2025-08-26T19:56:05.1252925Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0, line 3376 <- wrt source file 2025-08-26T19:56:05.1255908Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::send_object_list:0 2025-08-26T19:56:05.1258752Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0, line 3478 <- wrt source file 2025-08-26T19:56:05.1261742Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::recv_object_list:0 2025-08-26T19:56:05.1264665Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0, line 3592 <- wrt source file 2025-08-26T19:56:05.1267677Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::broadcast_object_list:0 2025-08-26T19:56:05.1270623Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0, line 3715 <- wrt source file 2025-08-26T19:56:05.1273613Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::scatter_object_list:0 2025-08-26T19:56:05.1276557Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0, line 3924 <- wrt source file 2025-08-26T19:56:05.1279590Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::all_gather_into_tensor:0 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DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::reduce_scatter_tensor:0, line 4391 <- wrt source file 2025-08-26T19:56:05.1302450Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::reduce_scatter_tensor:0 2025-08-26T19:56:05.1305393Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::monitored_barrier:0, line 4873 <- wrt source file 2025-08-26T19:56:05.1308344Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::monitored_barrier:0 2025-08-26T19:56:05.1311206Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::new_subgroups:0, line 5415 <- wrt source file 2025-08-26T19:56:05.1314069Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py::new_subgroups:0 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source file 2025-08-26T19:56:05.1640908Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py::StateDictType:0 2025-08-26T19:56:05.1643960Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0, line 125 <- wrt source file 2025-08-26T19:56:05.1647467Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel:0 2025-08-26T19:56:05.1651255Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.shard_full_optim_state_dict:0, line 1490 <- wrt source file 2025-08-26T19:56:05.1655317Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py::FullyShardedDataParallel.shard_full_optim_state_dict:0 2025-08-26T19:56:05.1659424Z * 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line 54 <- wrt source file 2025-08-26T19:56:05.1678221Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/sharded_grad_scaler.py::ShardedGradScaler:0 2025-08-26T19:56:05.1681089Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/wrap.py::CustomPolicy:0, line 224 <- wrt source file 2025-08-26T19:56:05.1683779Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/wrap.py::CustomPolicy:0 2025-08-26T19:56:05.1686498Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0, line 134 <- wrt source file 2025-08-26T19:56:05.1689397Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/functional.py::_all_gather_base:0 2025-08-26T19:56:05.1692541Z * DOCTEST : 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SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py::TensorChunkSpec.from_tuple:0 2025-08-26T19:56:05.1730614Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py::TensorChunkSpec.from_dict:0, line 102 <- wrt source file 2025-08-26T19:56:05.1733925Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py::TensorChunkSpec.from_dict:0 2025-08-26T19:56:05.1736738Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::_wait_all:0, line 174 <- wrt source file 2025-08-26T19:56:05.1739418Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::_wait_all:0 2025-08-26T19:56:05.1741826Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/api.py::shutdown:0, line 345 <- wrt source file 2025-08-26T19:56:05.1744303Z * SKIPPED: 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wrt source file 2025-08-26T19:56:05.1813309Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py::SequenceParallel:0 2025-08-26T19:56:05.1816090Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/bernoulli.py::Bernoulli:0, line 30 <- wrt source file 2025-08-26T19:56:05.1818756Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/bernoulli.py::Bernoulli:0 2025-08-26T19:56:05.1821214Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/beta.py::Beta:0, line 21 <- wrt source file 2025-08-26T19:56:05.1823615Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/beta.py::Beta:0 2025-08-26T19:56:05.1826072Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/binomial.py::Binomial:0, line 31 <- wrt source file 2025-08-26T19:56:05.1828665Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/binomial.py::Binomial:0 2025-08-26T19:56:05.1831274Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/categorical.py::Categorical:0, line 42 <- wrt source file 2025-08-26T19:56:05.1834028Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/categorical.py::Categorical:0 2025-08-26T19:56:05.1836639Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/cauchy.py::Cauchy:0, line 23 <- wrt source file 2025-08-26T19:56:05.1839332Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/cauchy.py::Cauchy:0 2025-08-26T19:56:05.1841727Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/chi2.py::Chi2:0, line 18 <- wrt source file 2025-08-26T19:56:05.1844123Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/chi2.py::Chi2:0 2025-08-26T19:56:05.1846664Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::is_dependent:0, line 166 <- wrt source file 2025-08-26T19:56:05.1849513Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::is_dependent:0 2025-08-26T19:56:05.1852433Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::_DependentProperty:0, line 187 <- wrt source file 2025-08-26T19:56:05.1855377Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/constraints.py::_DependentProperty:0 2025-08-26T19:56:05.1858386Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0, line 35 <- wrt source file 2025-08-26T19:56:05.1861655Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/continuous_bernoulli.py::ContinuousBernoulli:0 2025-08-26T19:56:05.1864479Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/dirichlet.py::Dirichlet:0, line 42 <- wrt source file 2025-08-26T19:56:05.1867120Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/dirichlet.py::Dirichlet:0 2025-08-26T19:56:05.1869777Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/exponential.py::Exponential:0, line 20 <- wrt source file 2025-08-26T19:56:05.1872548Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/exponential.py::Exponential:0 2025-08-26T19:56:05.1875346Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0, line 21 <- wrt source file 2025-08-26T19:56:05.1878275Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/fishersnedecor.py::FisherSnedecor:0 2025-08-26T19:56:05.1880862Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gamma.py::Gamma:0, line 24 <- wrt source file 2025-08-26T19:56:05.1883297Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gamma.py::Gamma:0 2025-08-26T19:56:05.1886023Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0, line 26 <- wrt source file 2025-08-26T19:56:05.1889152Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/generalized_pareto.py::GeneralizedPareto:0 2025-08-26T19:56:05.1891965Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/geometric.py::Geometric:0, line 36 <- wrt source file 2025-08-26T19:56:05.1894614Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/geometric.py::Geometric:0 2025-08-26T19:56:05.1897121Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gumbel.py::Gumbel:0, line 23 <- wrt source file 2025-08-26T19:56:05.1899691Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/gumbel.py::Gumbel:0 2025-08-26T19:56:05.1902235Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0, line 24 <- wrt source file 2025-08-26T19:56:05.1904940Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_cauchy.py::HalfCauchy:0 2025-08-26T19:56:05.1907597Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_normal.py::HalfNormal:0, line 24 <- wrt source file 2025-08-26T19:56:05.1910287Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/half_normal.py::HalfNormal:0 2025-08-26T19:56:05.1912985Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/independent.py::Independent:0, line 27 <- wrt source file 2025-08-26T19:56:05.1915744Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/independent.py::Independent:0 2025-08-26T19:56:05.1918514Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0, line 24 <- wrt source file 2025-08-26T19:56:05.1921328Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/inverse_gamma.py::InverseGamma:0 2025-08-26T19:56:05.1924137Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0, line 30 <- wrt source file 2025-08-26T19:56:05.1926880Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/kumaraswamy.py::Kumaraswamy:0 2025-08-26T19:56:05.1929530Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/laplace.py::Laplace:0, line 20 <- wrt source file 2025-08-26T19:56:05.1932092Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/laplace.py::Laplace:0 2025-08-26T19:56:05.1934684Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0, line 43 <- wrt source file 2025-08-26T19:56:05.1937563Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lkj_cholesky.py::LKJCholesky:0 2025-08-26T19:56:05.1940222Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/log_normal.py::LogNormal:0, line 23 <- wrt source file 2025-08-26T19:56:05.1942854Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/log_normal.py::LogNormal:0 2025-08-26T19:56:05.1945599Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0, line 28 <- wrt source file 2025-08-26T19:56:05.1948504Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/logistic_normal.py::LogisticNormal:0 2025-08-26T19:56:05.1951279Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multinomial.py::Multinomial:0, line 38 <- wrt source file 2025-08-26T19:56:05.1954115Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multinomial.py::Multinomial:0 2025-08-26T19:56:05.1957018Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0, line 103 <- wrt source file 2025-08-26T19:56:05.1960141Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/multivariate_normal.py::MultivariateNormal:0 2025-08-26T19:56:05.1962874Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/normal.py::Normal:0, line 22 <- wrt source file 2025-08-26T19:56:05.1965478Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/normal.py::Normal:0 2025-08-26T19:56:05.1968208Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0, line 34 <- wrt source file 2025-08-26T19:56:05.1971345Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/one_hot_categorical.py::OneHotCategorical:0 2025-08-26T19:56:05.1974073Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/pareto.py::Pareto:0, line 20 <- wrt source file 2025-08-26T19:56:05.1976570Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/pareto.py::Pareto:0 2025-08-26T19:56:05.1979057Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/poisson.py::Poisson:0, line 25 <- wrt source file 2025-08-26T19:56:05.1981670Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/poisson.py::Poisson:0 2025-08-26T19:56:05.1984178Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/studentT.py::StudentT:0, line 22 <- wrt source file 2025-08-26T19:56:05.1986765Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/studentT.py::StudentT:0 2025-08-26T19:56:05.1989512Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CatTransform:0, line 1065 <- wrt source file 2025-08-26T19:56:05.1992296Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/transforms.py::CatTransform:0 2025-08-26T19:56:05.1995058Z * DOCTEST : 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/wishart.py::Wishart:0, line 39 <- wrt source file 2025-08-26T19:56:05.2030042Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/wishart.py::Wishart:0 2025-08-26T19:56:05.2032457Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::Dim:0, line 103 <- wrt source file 2025-08-26T19:56:05.2034898Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::Dim:0 2025-08-26T19:56:05.2037594Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0, line 715 <- wrt source file 2025-08-26T19:56:05.2040370Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:0 2025-08-26T19:56:05.2043076Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1, line 731 <- wrt source file 2025-08-26T19:56:05.2045919Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::ShapesCollection:1 2025-08-26T19:56:05.2048615Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0, line 815 <- wrt source file 2025-08-26T19:56:05.2051430Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/export/dynamic_shapes.py::AdditionalInputs:0 2025-08-26T19:56:05.2054023Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::_snake_case:0, line 102 <- wrt source file 2025-08-26T19:56:05.2056319Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/graph.py::_snake_case:0 2025-08-26T19:56:05.2058752Z * DOCTEST : 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65 <- wrt source file 2025-08-26T19:56:05.2091419Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::is_consistent:0 2025-08-26T19:56:05.2093858Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::is_more_precise:0, line 93 <- wrt source file 2025-08-26T19:56:05.2096354Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/tensor_type.py::is_more_precise:0 2025-08-26T19:56:05.2099132Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/rewriter.py::AST_Rewriter.visit_AnnAssign:0, line 96 <- wrt source file 2025-08-26T19:56:05.2102216Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/rewriter.py::AST_Rewriter.visit_AnnAssign:0 2025-08-26T19:56:05.2105104Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/core.py::reify:0, line 58 <- wrt source file 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source file 2025-08-26T19:56:05.2194575Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::dissoc:0 2025-08-26T19:56:05.2197644Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::first:0, line 416 <- wrt source file 2025-08-26T19:56:05.2200764Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py::first:0 2025-08-26T19:56:05.2203740Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::transitive_get:0, line 15 <- wrt source file 2025-08-26T19:56:05.2206755Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::transitive_get:0 2025-08-26T19:56:05.2209708Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::_toposort:0, line 42 <- wrt source file 2025-08-26T19:56:05.2212622Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::_toposort:0 2025-08-26T19:56:05.2215499Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::reverse_dict:0, line 70 <- wrt source file 2025-08-26T19:56:05.2218485Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::reverse_dict:0 2025-08-26T19:56:05.2221326Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::freeze:0, line 95 <- wrt source file 2025-08-26T19:56:05.2224166Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/utils.py::freeze:0 2025-08-26T19:56:05.2227093Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/variable.py::variables:0, line 67 <- wrt source file 2025-08-26T19:56:05.2230090Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/variable.py::variables:0 2025-08-26T19:56:05.2233208Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/core.py::dispatch:0, line 20 <- wrt source file 2025-08-26T19:56:05.2236534Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/core.py::dispatch:0 2025-08-26T19:56:05.2240042Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher:0, line 113 <- wrt source file 2025-08-26T19:56:05.2243660Z * SKIPPED: 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.dispatch:0, line 304 <- wrt source file 2025-08-26T19:56:05.2265838Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::Dispatcher.dispatch:0 2025-08-26T19:56:05.2269443Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::str_signature:0, line 434 <- wrt source file 2025-08-26T19:56:05.2273040Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/dispatcher.py::str_signature:0 2025-08-26T19:56:05.2276483Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::expand_tuples:0, line 18 <- wrt source file 2025-08-26T19:56:05.2279937Z * SUCCESS: 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/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::groupby:0, line 87 <- wrt source file 2025-08-26T19:56:05.2300131Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::groupby:0 2025-08-26T19:56:05.2303404Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::typename:0, line 117 <- wrt source file 2025-08-26T19:56:05.2306770Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/utils.py::typename:0 2025-08-26T19:56:05.2310119Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/multipledispatch/variadic.py::isvariadic:0, line 47 <- wrt source file 2025-08-26T19:56:05.2313592Z * SKIPPED: 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file 2025-08-26T19:56:05.2331931Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/shape_prop.py::ShapeProp:0 2025-08-26T19:56:05.2334475Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/split_module.py::split_module:0, line 89 <- wrt source file 2025-08-26T19:56:05.2337117Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/split_module.py::split_module:0 2025-08-26T19:56:05.2339777Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0, line 51 <- wrt source file 2025-08-26T19:56:05.2341662Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/passes/utils/matcher_with_name_node_map_utils.py::SubgraphMatcherWithNameNodeMap:0 2025-08-26T19:56:05.2343258Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0, line 36 <- wrt source file 2025-08-26T19:56:05.2344704Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/_check.py::AttributeTypeIsSupportedChecker:0 2025-08-26T19:56:05.2346090Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_load_for_lite_interpreter:0, line 22 <- wrt source file 2025-08-26T19:56:05.2347517Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_load_for_lite_interpreter:0 2025-08-26T19:56:05.2348951Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_mobile_model_contained_types:0, line 122 <- wrt source file 2025-08-26T19:56:05.2350440Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_mobile_model_contained_types:0 2025-08-26T19:56:05.2352052Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0, line 214 <- wrt source file 2025-08-26T19:56:05.2353432Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/jit/mobile/__init__.py::_get_model_ops_and_info:0 2025-08-26T19:56:05.2354682Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/_ops.py::logaddexp:0, line 1530 <- wrt source file 2025-08-26T19:56:05.2355873Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/_ops.py::logaddexp:0 2025-08-26T19:56:05.2357154Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0, line 25 <- wrt source file 2025-08-26T19:56:05.2358562Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/masked/maskedtensor/core.py::is_masked_tensor:0 2025-08-26T19:56:05.2360038Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0, line 460 <- wrt source file 2025-08-26T19:56:05.2361509Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool2d_with_indices:0 2025-08-26T19:56:05.2363029Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0, line 579 <- wrt source file 2025-08-26T19:56:05.3168678Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::fractional_max_pool3d_with_indices:0 2025-08-26T19:56:05.3190456Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::gumbel_softmax:0, line 2174 <- wrt source file 2025-08-26T19:56:05.3199251Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::gumbel_softmax:0 2025-08-26T19:56:05.3201633Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding:0, line 2478 <- wrt source file 2025-08-26T19:56:05.3208198Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding:0 2025-08-26T19:56:05.3210654Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding_bag:0, line 2618 <- wrt source file 2025-08-26T19:56:05.3218244Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::embedding_bag:0 2025-08-26T19:56:05.3220635Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::ctc_loss:0, line 3051 <- wrt source file 2025-08-26T19:56:05.3232692Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::ctc_loss:0 2025-08-26T19:56:05.3235050Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::nll_loss:0, line 3121 <- wrt source file 2025-08-26T19:56:05.3239319Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::nll_loss:0 2025-08-26T19:56:05.3241717Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::cross_entropy:0, line 3430 <- wrt source file 2025-08-26T19:56:05.3248199Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::cross_entropy:0 2025-08-26T19:56:05.3250805Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy:0, line 3495 <- wrt source file 2025-08-26T19:56:05.3254904Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy:0 2025-08-26T19:56:05.3257896Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0, line 3565 <- wrt source file 2025-08-26T19:56:05.3261403Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::binary_cross_entropy_with_logits:0 2025-08-26T19:56:05.3263952Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::pad:0, line 5263 <- wrt source file 2025-08-26T19:56:05.3271567Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/functional.py::pad:0 2025-08-26T19:56:05.3273792Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_input:0, line 32 <- wrt source file 2025-08-26T19:56:05.3279742Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_input:0 2025-08-26T19:56:05.3282028Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_weight:0, line 79 <- wrt source file 2025-08-26T19:56:05.3284783Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv1d_weight:0 2025-08-26T19:56:05.3287063Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_input:0, line 130 <- wrt source file 2025-08-26T19:56:05.3292631Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_input:0 2025-08-26T19:56:05.3294892Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_weight:0, line 177 <- wrt source file 2025-08-26T19:56:05.3297242Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv2d_weight:0 2025-08-26T19:56:05.3299508Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_input:0, line 228 <- wrt source file 2025-08-26T19:56:05.3328163Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_input:0 2025-08-26T19:56:05.3331168Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_weight:0, line 275 <- wrt source file 2025-08-26T19:56:05.3355753Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/grad.py::conv3d_weight:0 2025-08-26T19:56:05.3358294Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::uniform_:0, line 230 <- wrt source file 2025-08-26T19:56:05.3360735Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::uniform_:0 2025-08-26T19:56:05.3362893Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::normal_:0, line 257 <- wrt source file 2025-08-26T19:56:05.3365097Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::normal_:0 2025-08-26T19:56:05.3367327Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::trunc_normal_:0, line 292 <- wrt source file 2025-08-26T19:56:05.3379020Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::trunc_normal_:0 2025-08-26T19:56:05.3381252Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::constant_:0, line 306 <- wrt source file 2025-08-26T19:56:05.3383501Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::constant_:0 2025-08-26T19:56:05.3385659Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::ones_:0, line 323 <- wrt source file 2025-08-26T19:56:05.3387825Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::ones_:0 2025-08-26T19:56:05.3390085Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::zeros_:0, line 336 <- wrt source file 2025-08-26T19:56:05.3392273Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::zeros_:0 2025-08-26T19:56:05.3394382Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::eye_:0, line 352 <- wrt source file 2025-08-26T19:56:05.3396514Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::eye_:0 2025-08-26T19:56:05.3398634Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::dirac_:0, line 374 <- wrt source file 2025-08-26T19:56:05.3400810Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::dirac_:0 2025-08-26T19:56:05.3403043Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_uniform_:0, line 460 <- wrt source file 2025-08-26T19:56:05.3405553Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_uniform_:0 2025-08-26T19:56:05.3407861Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_normal_:0, line 492 <- wrt source file 2025-08-26T19:56:05.3410247Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::xavier_normal_:0 2025-08-26T19:56:05.3412688Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_uniform_:0, line 543 <- wrt source file 2025-08-26T19:56:05.3415090Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_uniform_:0 2025-08-26T19:56:05.3417435Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_normal_:0, line 608 <- wrt source file 2025-08-26T19:56:05.3419795Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::kaiming_normal_:0 2025-08-26T19:56:05.3422074Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::orthogonal_:0, line 647 <- wrt source file 2025-08-26T19:56:05.3424370Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::orthogonal_:0 2025-08-26T19:56:05.3426580Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::sparse_:0, line 700 <- wrt source file 2025-08-26T19:56:05.3428792Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py::sparse_:0 2025-08-26T19:56:05.3431158Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0, line 120 <- wrt source file 2025-08-26T19:56:05.3433751Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/__init__.py::sdpa_kernel:0 2025-08-26T19:56:05.3436245Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/bias.py::CausalBias:0, line 95 <- wrt source file 2025-08-26T19:56:05.3438909Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/attention/bias.py::CausalBias:0 2025-08-26T19:56:05.3441417Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Threshold:0, line 72 <- wrt source file 2025-08-26T19:56:05.3444012Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Threshold:0 2025-08-26T19:56:05.3446483Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU:0, line 120 <- wrt source file 2025-08-26T19:56:05.3449016Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU:0 2025-08-26T19:56:05.3451529Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::RReLU:0, line 185 <- wrt source file 2025-08-26T19:56:05.3454025Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::RReLU:0 2025-08-26T19:56:05.3456507Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardtanh:0, line 247 <- wrt source file 2025-08-26T19:56:05.3459074Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardtanh:0 2025-08-26T19:56:05.3461549Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU6:0, line 318 <- wrt source file 2025-08-26T19:56:05.3464046Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ReLU6:0 2025-08-26T19:56:05.3466578Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Sigmoid:0, line 349 <- wrt source file 2025-08-26T19:56:05.3469117Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Sigmoid:0 2025-08-26T19:56:05.3471644Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0, line 384 <- wrt source file 2025-08-26T19:56:05.3474398Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardsigmoid:0 2025-08-26T19:56:05.3476908Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanh:0, line 420 <- wrt source file 2025-08-26T19:56:05.3479383Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanh:0 2025-08-26T19:56:05.3481804Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SiLU:0, line 456 <- wrt source file 2025-08-26T19:56:05.3484272Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SiLU:0 2025-08-26T19:56:05.3486696Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Mish:0, line 501 <- wrt source file 2025-08-26T19:56:05.3489198Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Mish:0 2025-08-26T19:56:05.3491684Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardswish:0, line 552 <- wrt source file 2025-08-26T19:56:05.3494265Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardswish:0 2025-08-26T19:56:05.3496725Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ELU:0, line 598 <- wrt source file 2025-08-26T19:56:05.3499198Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::ELU:0 2025-08-26T19:56:05.3501615Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::CELU:0, line 646 <- wrt source file 2025-08-26T19:56:05.3504083Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::CELU:0 2025-08-26T19:56:05.3506511Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SELU:0, line 705 <- wrt source file 2025-08-26T19:56:05.3508980Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::SELU:0 2025-08-26T19:56:05.3511387Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GLU:0, line 751 <- wrt source file 2025-08-26T19:56:05.3513916Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GLU:0 2025-08-26T19:56:05.3516332Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GELU:0, line 799 <- wrt source file 2025-08-26T19:56:05.3518802Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::GELU:0 2025-08-26T19:56:05.3521316Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardshrink:0, line 848 <- wrt source file 2025-08-26T19:56:05.3523955Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Hardshrink:0 2025-08-26T19:56:05.3526490Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LeakyReLU:0, line 903 <- wrt source file 2025-08-26T19:56:05.3529184Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LeakyReLU:0 2025-08-26T19:56:05.3531759Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSigmoid:0, line 945 <- wrt source file 2025-08-26T19:56:05.3534383Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSigmoid:0 2025-08-26T19:56:05.3537017Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softplus:0, line 981 <- wrt source file 2025-08-26T19:56:05.3539750Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softplus:0 2025-08-26T19:56:05.3542287Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softshrink:0, line 1030 <- wrt source file 2025-08-26T19:56:05.3544925Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softshrink:0 2025-08-26T19:56:05.3547703Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0, line 1144 <- wrt source file 2025-08-26T19:56:05.3550929Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::MultiheadAttention:0 2025-08-26T19:56:05.3553909Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::PReLU:0, line 1609 <- wrt source file 2025-08-26T19:56:05.3556537Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::PReLU:0 2025-08-26T19:56:05.3559034Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softsign:0, line 1660 <- wrt source file 2025-08-26T19:56:05.3561527Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softsign:0 2025-08-26T19:56:05.3564081Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanhshrink:0, line 1686 <- wrt source file 2025-08-26T19:56:05.3566708Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Tanhshrink:0 2025-08-26T19:56:05.3569321Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmin:0, line 1724 <- wrt source file 2025-08-26T19:56:05.3571885Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmin:0 2025-08-26T19:56:05.3574362Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax:0, line 1788 <- wrt source file 2025-08-26T19:56:05.3577010Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax:0 2025-08-26T19:56:05.3579537Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax2d:0, line 1835 <- wrt source file 2025-08-26T19:56:05.3582143Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::Softmax2d:0 2025-08-26T19:56:05.3584713Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSoftmax:0, line 1874 <- wrt source file 2025-08-26T19:56:05.3587350Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/activation.py::LogSoftmax:0 2025-08-26T19:56:05.3589902Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0, line 332 <- wrt source file 2025-08-26T19:56:05.3592598Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm1d:0 2025-08-26T19:56:05.3595165Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0, line 443 <- wrt source file 2025-08-26T19:56:05.3777841Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm2d:0 2025-08-26T19:56:05.3781013Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0, line 554 <- wrt source file 2025-08-26T19:56:05.6086971Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py::BatchNorm3d:0 2025-08-26T19:56:05.6250032Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0, line 21 <- wrt source file 2025-08-26T19:56:05.6272032Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/channelshuffle.py::ChannelShuffle:0 2025-08-26T19:56:05.6274701Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential:0, line 81 <- wrt source file 2025-08-26T19:56:05.6277281Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential:0 2025-08-26T19:56:05.6279915Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.append:0, line 260 <- wrt source file 2025-08-26T19:56:05.6282679Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.append:0 2025-08-26T19:56:05.6285394Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.insert:0, line 283 <- wrt source file 2025-08-26T19:56:05.6290166Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.insert:0 2025-08-26T19:56:05.6292872Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.extend:0, line 314 <- wrt source file 2025-08-26T19:56:05.6298691Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::Sequential.extend:0 2025-08-26T19:56:05.6301337Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleList:0, line 343 <- wrt source file 2025-08-26T19:56:05.6303928Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleList:0 2025-08-26T19:56:05.6306474Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleDict:0, line 523 <- wrt source file 2025-08-26T19:56:05.6309335Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ModuleDict:0 2025-08-26T19:56:05.6311931Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterList:0, line 653 <- wrt source file 2025-08-26T19:56:05.6314610Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterList:0 2025-08-26T19:56:05.6317248Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterDict:0, line 808 <- wrt source file 2025-08-26T19:56:05.6319931Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/container.py::ParameterDict:0 2025-08-26T19:56:05.6322582Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0, line 38 <- wrt source file 2025-08-26T19:56:05.6325367Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::PairwiseDistance:0 2025-08-26T19:56:05.6328009Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0, line 81 <- wrt source file 2025-08-26T19:56:05.6330786Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/distance.py::CosineSimilarity:0 2025-08-26T19:56:05.6333445Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout:0, line 60 <- wrt source file 2025-08-26T19:56:05.6335929Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout:0 2025-08-26T19:56:05.6338509Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout1d:0, line 108 <- wrt source file 2025-08-26T19:56:05.6341045Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout1d:0 2025-08-26T19:56:05.6343507Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout2d:0, line 163 <- wrt source file 2025-08-26T19:56:05.6350624Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout2d:0 2025-08-26T19:56:05.6353399Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout3d:0, line 211 <- wrt source file 2025-08-26T19:56:05.6421717Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::Dropout3d:0 2025-08-26T19:56:05.6424559Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0, line 257 <- wrt source file 2025-08-26T19:56:05.6427315Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::AlphaDropout:0 2025-08-26T19:56:05.6429957Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0, line 309 <- wrt source file 2025-08-26T19:56:05.6496772Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/dropout.py::FeatureAlphaDropout:0 2025-08-26T19:56:05.6499677Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py::Flatten:0, line 30 <- wrt source file 2025-08-26T19:56:05.6502449Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py::Flatten:0 2025-08-26T19:56:05.6504793Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Fold:0, line 224 <- wrt source file 2025-08-26T19:56:05.6508456Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Fold:0 2025-08-26T19:56:05.6510762Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Unfold:0, line 395 <- wrt source file 2025-08-26T19:56:05.6523142Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/fold.py::Unfold:0 2025-08-26T19:56:05.6525704Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0, line 187 <- wrt source file 2025-08-26T19:56:05.6535978Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm1d:0 2025-08-26T19:56:05.6707644Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0, line 303 <- wrt source file 2025-08-26T19:56:05.6710804Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm2d:0 2025-08-26T19:56:05.6713702Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0, line 419 <- wrt source file 2025-08-26T19:56:05.9007345Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/instancenorm.py::InstanceNorm3d:0 2025-08-26T19:56:05.9171565Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0, line 77 <- wrt source file 2025-08-26T19:56:05.9174187Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/lazy.py::LazyModuleMixin:0 2025-08-26T19:56:05.9176642Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Identity:0, line 34 <- wrt source file 2025-08-26T19:56:05.9179914Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Identity:0 2025-08-26T19:56:05.9182305Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Linear:0, line 83 <- wrt source file 2025-08-26T19:56:05.9189182Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Linear:0 2025-08-26T19:56:05.9191645Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Bilinear:0, line 191 <- wrt source file 2025-08-26T19:56:05.9208984Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/linear.py::Bilinear:0 2025-08-26T19:56:05.9211381Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::L1Loss:0, line 115 <- wrt source file 2025-08-26T19:56:05.9217562Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::L1Loss:0 2025-08-26T19:56:05.9219922Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::NLLLoss:0, line 215 <- wrt source file 2025-08-26T19:56:05.9251455Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::NLLLoss:0 2025-08-26T19:56:05.9254015Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0, line 329 <- wrt source file 2025-08-26T19:56:05.9258691Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::PoissonNLLLoss:0 2025-08-26T19:56:05.9261242Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0, line 418 <- wrt source file 2025-08-26T19:56:05.9274095Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::GaussianNLLLoss:0 2025-08-26T19:56:05.9276801Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::KLDivLoss:0, line 535 <- wrt source file 2025-08-26T19:56:05.9281983Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::KLDivLoss:0 2025-08-26T19:56:05.9284656Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MSELoss:0, line 617 <- wrt source file 2025-08-26T19:56:05.9289076Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MSELoss:0 2025-08-26T19:56:05.9291438Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCELoss:0, line 703 <- wrt source file 2025-08-26T19:56:05.9295615Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCELoss:0 2025-08-26T19:56:05.9298096Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0, line 778 <- wrt source file 2025-08-26T19:56:05.9307791Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:0 2025-08-26T19:56:05.9310524Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1, line 826 <- wrt source file 2025-08-26T19:56:05.9314025Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::BCEWithLogitsLoss:1 2025-08-26T19:56:05.9317304Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0, line 974 <- wrt source file 2025-08-26T19:56:05.9323087Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiLabelMarginLoss:0 2025-08-26T19:56:05.9325724Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0, line 1306 <- wrt source file 2025-08-26T19:56:05.9332120Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:0 2025-08-26T19:56:05.9335033Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1, line 1333 <- wrt source file 2025-08-26T19:56:05.9338234Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CrossEntropyLoss:1 2025-08-26T19:56:05.9340878Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0, line 1495 <- wrt source file 2025-08-26T19:56:05.9344375Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::CosineEmbeddingLoss:0 2025-08-26T19:56:05.9347002Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0, line 1562 <- wrt source file 2025-08-26T19:56:05.9351969Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MarginRankingLoss:0 2025-08-26T19:56:05.9354529Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0, line 1643 <- wrt source file 2025-08-26T19:56:05.9360556Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::MultiMarginLoss:0 2025-08-26T19:56:05.9363148Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0, line 1745 <- wrt source file 2025-08-26T19:56:05.9372610Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py::TripletMarginLoss:0 2025-08-26T19:56:05.9375284Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.register_buffer:0, line 551 <- wrt source file 2025-08-26T19:56:05.9378191Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.register_buffer:0 2025-08-26T19:56:05.9380811Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.apply:0, line 1039 <- wrt source file 2025-08-26T19:56:05.9388965Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.apply:0 2025-08-26T19:56:05.9391440Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.to:0, line 1290 <- wrt source file 2025-08-26T19:56:05.9396008Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.to:0 2025-08-26T19:56:05.9398549Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.state_dict:0, line 2229 <- wrt source file 2025-08-26T19:56:05.9401313Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.state_dict:0 2025-08-26T19:56:05.9403964Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.parameters:0, line 2670 <- wrt source file 2025-08-26T19:56:05.9406662Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.parameters:0 2025-08-26T19:56:05.9409554Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_parameters:0, line 2698 <- wrt source file 2025-08-26T19:56:05.9412387Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_parameters:0 2025-08-26T19:56:05.9415051Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.buffers:0, line 2725 <- wrt source file 2025-08-26T19:56:05.9417662Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.buffers:0 2025-08-26T19:56:05.9420293Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_buffers:0, line 2752 <- wrt source file 2025-08-26T19:56:05.9423022Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_buffers:0 2025-08-26T19:56:05.9425728Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_children:0, line 2783 <- wrt source file 2025-08-26T19:56:05.9428433Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_children:0 2025-08-26T19:56:05.9431070Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.modules:0, line 2807 <- wrt source file 2025-08-26T19:56:05.9434223Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.modules:0 2025-08-26T19:56:05.9437762Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_modules:0, line 2845 <- wrt source file 2025-08-26T19:56:05.9441413Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/module.py::Module.named_modules:0 2025-08-26T19:56:05.9444634Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0, line 38 <- wrt source file 2025-08-26T19:56:05.9448384Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LocalResponseNorm:0 2025-08-26T19:56:05.9452026Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LayerNorm:0, line 163 <- wrt source file 2025-08-26T19:56:05.9457867Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::LayerNorm:0 2025-08-26T19:56:05.9460844Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::GroupNorm:0, line 274 <- wrt source file 2025-08-26T19:56:05.9465582Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::GroupNorm:0 2025-08-26T19:56:05.9468508Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::RMSNorm:0, line 367 <- wrt source file 2025-08-26T19:56:05.9471402Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/normalization.py::RMSNorm:0 2025-08-26T19:56:05.9473974Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad1d:0, line 70 <- wrt source file 2025-08-26T19:56:05.9477867Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad1d:0 2025-08-26T19:56:05.9480438Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad2d:0, line 122 <- wrt source file 2025-08-26T19:56:05.9500566Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad2d:0 2025-08-26T19:56:05.9503138Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad3d:0, line 187 <- wrt source file 2025-08-26T19:56:06.5145749Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::CircularPad3d:0 2025-08-26T19:56:06.5441366Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0, line 241 <- wrt source file 2025-08-26T19:56:06.5451186Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad1d:0 2025-08-26T19:56:06.5453755Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0, line 294 <- wrt source file 2025-08-26T19:56:06.5457665Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad2d:0 2025-08-26T19:56:06.5460233Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0, line 350 <- wrt source file 2025-08-26T19:56:06.5479415Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ConstantPad3d:0 2025-08-26T19:56:06.5482150Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0, line 395 <- wrt source file 2025-08-26T19:56:06.5486528Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad1d:0 2025-08-26T19:56:06.5489195Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0, line 439 <- wrt source file 2025-08-26T19:56:06.5492974Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad2d:0 2025-08-26T19:56:06.5495606Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0, line 497 <- wrt source file 2025-08-26T19:56:06.5498287Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReflectionPad3d:0 2025-08-26T19:56:06.5501183Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0, line 556 <- wrt source file 2025-08-26T19:56:06.5503888Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad1d:0 2025-08-26T19:56:06.5506545Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0, line 600 <- wrt source file 2025-08-26T19:56:06.5509413Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad2d:0 2025-08-26T19:56:06.5512062Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0, line 658 <- wrt source file 2025-08-26T19:56:07.0230129Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ReplicationPad3d:0 2025-08-26T19:56:07.0527253Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0, line 692 <- wrt source file 2025-08-26T19:56:07.0535919Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad1d:0 2025-08-26T19:56:07.0538545Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0, line 750 <- wrt source file 2025-08-26T19:56:07.0542862Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad2d:0 2025-08-26T19:56:07.0545350Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0, line 812 <- wrt source file 2025-08-26T19:56:07.0564156Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/padding.py::ZeroPad3d:0 2025-08-26T19:56:07.0566633Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0, line 40 <- wrt source file 2025-08-26T19:56:07.0570453Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelShuffle:0 2025-08-26T19:56:07.0573157Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0, line 99 <- wrt source file 2025-08-26T19:56:07.0575973Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pixelshuffle.py::PixelUnshuffle:0 2025-08-26T19:56:07.0578556Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0, line 129 <- wrt source file 2025-08-26T19:56:07.0581608Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool1d:0 2025-08-26T19:56:07.0584085Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0, line 207 <- wrt source file 2025-08-26T19:56:07.0623974Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool2d:0 2025-08-26T19:56:07.0626453Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0, line 291 <- wrt source file 2025-08-26T19:56:07.2509152Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxPool3d:0 2025-08-26T19:56:07.2567451Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0, line 366 <- wrt source file 2025-08-26T19:56:07.2578888Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool1d:0 2025-08-26T19:56:07.2581428Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0, line 550 <- wrt source file 2025-08-26T19:56:07.3260109Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::MaxUnpool3d:0 2025-08-26T19:56:07.3262640Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0, line 642 <- wrt source file 2025-08-26T19:56:07.3278954Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool1d:0 2025-08-26T19:56:07.3281449Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0, line 738 <- wrt source file 2025-08-26T19:56:07.3314365Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool2d:0 2025-08-26T19:56:07.3316844Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0, line 855 <- wrt source file 2025-08-26T19:56:07.4898626Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AvgPool3d:0 2025-08-26T19:56:07.4957946Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0, line 946 <- wrt source file 2025-08-26T19:56:07.5000138Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool2d:0 2025-08-26T19:56:07.5003249Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0, line 1033 <- wrt source file 2025-08-26T19:56:07.5607488Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::FractionalMaxPool3d:0 2025-08-26T19:56:07.5610182Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool1d:0, line 1152 <- wrt source file 2025-08-26T19:56:07.5615691Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool1d:0 2025-08-26T19:56:07.5618159Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool2d:0, line 1204 <- wrt source file 2025-08-26T19:56:07.5660868Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool2d:0 2025-08-26T19:56:07.5664154Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool3d:0, line 1264 <- wrt source file 2025-08-26T19:56:07.7602297Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::LPPool3d:0 2025-08-26T19:56:07.7660602Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0, line 1320 <- wrt source file 2025-08-26T19:56:07.7676131Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool1d:0 2025-08-26T19:56:07.7678829Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0, line 1355 <- wrt source file 2025-08-26T19:56:07.7684810Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool2d:0 2025-08-26T19:56:07.7687539Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0, line 1399 <- wrt source file 2025-08-26T19:56:07.7759858Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveMaxPool3d:0 2025-08-26T19:56:07.7762566Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0, line 1447 <- wrt source file 2025-08-26T19:56:07.7765581Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool1d:0 2025-08-26T19:56:07.7768271Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0, line 1481 <- wrt source file 2025-08-26T19:56:07.7772916Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool2d:0 2025-08-26T19:56:07.7775636Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0, line 1521 <- wrt source file 2025-08-26T19:56:07.7789780Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py::AdaptiveAvgPool3d:0 2025-08-26T19:56:07.7792231Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNN:0, line 595 <- wrt source file 2025-08-26T19:56:07.7801874Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNN:0 2025-08-26T19:56:07.7804147Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTM:0, line 953 <- wrt source file 2025-08-26T19:56:07.8159323Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTM:0 2025-08-26T19:56:07.8177428Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRU:0, line 1288 <- wrt source file 2025-08-26T19:56:07.8179733Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRU:0 2025-08-26T19:56:07.8182025Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNNCell:0, line 1537 <- wrt source file 2025-08-26T19:56:07.8188406Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::RNNCell:0 2025-08-26T19:56:07.8190752Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTMCell:0, line 1659 <- wrt source file 2025-08-26T19:56:07.8199358Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::LSTMCell:0 2025-08-26T19:56:07.8201755Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRUCell:0, line 1773 <- wrt source file 2025-08-26T19:56:07.8212763Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/rnn.py::GRUCell:0 2025-08-26T19:56:07.8215148Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding:0, line 71 <- wrt source file 2025-08-26T19:56:07.8226559Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding:0 2025-08-26T19:56:07.8229210Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0, line 243 <- wrt source file 2025-08-26T19:56:07.8232163Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::Embedding.from_pretrained:0 2025-08-26T19:56:07.8235018Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0, line 521 <- wrt source file 2025-08-26T19:56:07.8238779Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py::EmbeddingBag.from_pretrained:0 2025-08-26T19:56:07.8241529Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::Transformer:0, line 90 <- wrt source file 2025-08-26T19:56:08.5628262Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::Transformer:0 2025-08-26T19:56:08.5684193Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0, line 336 <- wrt source file 2025-08-26T19:56:08.6709387Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoder:0 2025-08-26T19:56:08.6714430Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0, line 562 <- wrt source file 2025-08-26T19:56:08.8929183Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoder:0 2025-08-26T19:56:08.8937097Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0, line 686 <- wrt source file 2025-08-26T19:56:08.9210787Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerEncoderLayer:0 2025-08-26T19:56:08.9214314Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0, line 995 <- wrt source file 2025-08-26T19:56:08.9720955Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py::TransformerDecoderLayer:0 2025-08-26T19:56:08.9724314Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::Upsample:0, line 77 <- wrt source file 2025-08-26T19:56:08.9748861Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::Upsample:0 2025-08-26T19:56:08.9751560Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0, line 229 <- wrt source file 2025-08-26T19:56:08.9761398Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingNearest2d:0 2025-08-26T19:56:08.9764251Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0, line 279 <- wrt source file 2025-08-26T19:56:08.9769822Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/upsampling.py::UpsamplingBilinear2d:0 2025-08-26T19:56:08.9780915Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0, line 127 <- wrt source file 2025-08-26T19:56:08.9783934Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/data_parallel.py::DataParallel:0 2025-08-26T19:56:08.9786824Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0, line 642 <- wrt source file 2025-08-26T19:56:08.9789879Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel:0 2025-08-26T19:56:08.9792937Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0, line 1446 <- wrt source file 2025-08-26T19:56:08.9796142Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.no_sync:0 2025-08-26T19:56:08.9799426Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0, line 1999 <- wrt source file 2025-08-26T19:56:08.9802863Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:0 2025-08-26T19:56:08.9806400Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1, line 2009 <- wrt source file 2025-08-26T19:56:08.9809908Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel.register_comm_hook:1 2025-08-26T19:56:08.9813408Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0, line 2044 <- wrt source file 2025-08-26T19:56:08.9817018Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py::DistributedDataParallel._register_builtin_comm_hook:0 2025-08-26T19:56:08.9820158Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0, line 35 <- wrt source file 2025-08-26T19:56:08.9823169Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_per_sample_grad.py::call_for_per_sample_grads:0 2025-08-26T19:56:08.9825754Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/init.py::skip_init:0, line 33 <- wrt source file 2025-08-26T19:56:08.9828145Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/init.py::skip_init:0 2025-08-26T19:56:08.9830797Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0, line 265 <- wrt source file 2025-08-26T19:56:08.9833550Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::orthogonal:0 2025-08-26T19:56:08.9836238Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0, line 360 <- wrt source file 2025-08-26T19:56:08.9839193Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::weight_norm:0 2025-08-26T19:56:08.9841940Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0, line 591 <- wrt source file 2025-08-26T19:56:08.9844736Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrizations.py::spectral_norm:0 2025-08-26T19:56:08.9847275Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::identity:0, line 849 <- wrt source file 2025-08-26T19:56:08.9849722Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::identity:0 2025-08-26T19:56:08.9852195Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_unstructured:0, line 885 <- wrt source file 2025-08-26T19:56:08.9854788Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_unstructured:0 2025-08-26T19:56:08.9857311Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::l1_unstructured:0, line 928 <- wrt source file 2025-08-26T19:56:08.9859850Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::l1_unstructured:0 2025-08-26T19:56:08.9862366Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_structured:0, line 968 <- wrt source file 2025-08-26T19:56:08.9864941Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::random_structured:0 2025-08-26T19:56:08.9867370Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::remove:0, line 1197 <- wrt source file 2025-08-26T19:56:08.9869843Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::remove:0 2025-08-26T19:56:08.9872166Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::is_pruned:0, line 1225 <- wrt source file 2025-08-26T19:56:08.9874574Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py::is_pruned:0 2025-08-26T19:56:08.9876943Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pad_sequence:0, line 439 <- wrt source file 2025-08-26T19:56:08.9879357Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pad_sequence:0 2025-08-26T19:56:08.9881754Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0, line 500 <- wrt source file 2025-08-26T19:56:08.9884214Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpad_sequence:0 2025-08-26T19:56:08.9886683Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pack_sequence:0, line 556 <- wrt source file 2025-08-26T19:56:08.9889187Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::pack_sequence:0 2025-08-26T19:56:08.9891599Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0, line 584 <- wrt source file 2025-08-26T19:56:08.9894203Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py::unpack_sequence:0 2025-08-26T19:56:08.9896746Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0, line 314 <- wrt source file 2025-08-26T19:56:08.9899432Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::spectral_norm:0 2025-08-26T19:56:08.9902124Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0, line 346 <- wrt source file 2025-08-26T19:56:08.9904971Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/spectral_norm.py::remove_spectral_norm:0 2025-08-26T19:56:08.9907661Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/stateless.py::functional_call:0, line 196 <- wrt source file 2025-08-26T19:56:08.9910296Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/stateless.py::functional_call:0 2025-08-26T19:56:08.9912849Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0, line 134 <- wrt source file 2025-08-26T19:56:08.9915423Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::weight_norm:0 2025-08-26T19:56:08.9918019Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0, line 156 <- wrt source file 2025-08-26T19:56:08.9920737Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py::remove_weight_norm:0 2025-08-26T19:56:08.9923479Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0, line 315 <- wrt source file 2025-08-26T19:56:08.9926359Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/conv_utils.py::unfold3d:0 2025-08-26T19:56:08.9929613Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0, line 178 <- wrt source file 2025-08-26T19:56:08.9933326Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/_expanded_weights/expanded_weights_utils.py::sum_over_all_but_batch_and_last_n:0 2025-08-26T19:56:08.9936304Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0, line 280 <- wrt source file 2025-08-26T19:56:08.9938928Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LambdaLR:0 2025-08-26T19:56:08.9941471Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0, line 388 <- wrt source file 2025-08-26T19:56:08.9944157Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiplicativeLR:0 2025-08-26T19:56:08.9946657Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::StepLR:0, line 491 <- wrt source file 2025-08-26T19:56:08.9949176Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::StepLR:0 2025-08-26T19:56:08.9951623Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0, line 547 <- wrt source file 2025-08-26T19:56:08.9954182Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::MultiStepLR:0 2025-08-26T19:56:08.9956753Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0, line 608 <- wrt source file 2025-08-26T19:56:08.9959280Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ConstantLR:0 2025-08-26T19:56:08.9961737Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LinearLR:0, line 683 <- wrt source file 2025-08-26T19:56:08.9964211Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::LinearLR:0 2025-08-26T19:56:08.9966703Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0, line 773 <- wrt source file 2025-08-26T19:56:08.9969340Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ExponentialLR:0 2025-08-26T19:56:08.9971891Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0, line 971 <- wrt source file 2025-08-26T19:56:08.9974464Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::PolynomialLR:0 2025-08-26T19:56:08.9977065Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0, line 1062 <- wrt source file 2025-08-26T19:56:08.9979780Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingLR:0 2025-08-26T19:56:08.9982424Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0, line 1134 <- wrt source file 2025-08-26T19:56:08.9985082Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::ChainedScheduler:0 2025-08-26T19:56:08.9987938Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0, line 1803 <- wrt source file 2025-08-26T19:56:08.9991018Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:0 2025-08-26T19:56:08.9994040Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1, line 1819 <- wrt source file 2025-08-26T19:56:08.9997221Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py::CosineAnnealingWarmRestarts.step:1 2025-08-26T19:56:08.9999872Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py::update_bn:0, line 337 <- wrt source file 2025-08-26T19:56:09.0002282Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py::update_bn:0 2025-08-26T19:56:09.0004687Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/package/glob_group.py::GlobGroup:0, line 22 <- wrt source file 2025-08-26T19:56:09.0007187Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/package/glob_group.py::GlobGroup:0 2025-08-26T19:56:09.0010116Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0, line 295 <- wrt source file 2025-08-26T19:56:09.0013371Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::_KinetoProfile.toggle_collection_dynamic:0 2025-08-26T19:56:09.0016125Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::profile:0, line 617 <- wrt source file 2025-08-26T19:56:09.0018575Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/profiler/profiler.py::profile:0 2025-08-26T19:56:09.0021295Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0, line 339 <- wrt source file 2025-08-26T19:56:09.0024224Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/semi_structured.py::to_sparse_semi_structured:0 2025-08-26T19:56:09.0026885Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_creation.py::make_tensor:0, line 114 <- wrt source file 2025-08-26T19:56:09.0029391Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_creation.py::make_tensor:0 2025-08-26T19:56:09.0032018Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::parametrize:0, line 615 <- wrt source file 2025-08-26T19:56:09.0034844Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::parametrize:0 2025-08-26T19:56:09.0037758Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0, line 736 <- wrt source file 2025-08-26T19:56:09.0040633Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::reparametrize:0 2025-08-26T19:56:09.0043397Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0, line 825 <- wrt source file 2025-08-26T19:56:09.0046200Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::decorateIf:0 2025-08-26T19:56:09.0049197Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_symmetric_psd_matrix:0, line 4734 <- wrt source file 2025-08-26T19:56:09.0052350Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_symmetric_psd_matrix:0 2025-08-26T19:56:09.0055423Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_psd_matrix:0, line 4748 <- wrt source file 2025-08-26T19:56:09.0058565Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_psd_matrix:0 2025-08-26T19:56:09.0061711Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/common_utils.py::random_hermitian_pd_matrix:0, line 4778 <- wrt source file 2025-08-26T19:56:09.0064824Z * SKIPPED: 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<- wrt source file 2025-08-26T19:56:09.0083382Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/distributed/_tensor/common_dtensor.py::skip_unless_torch_gpu:0 2025-08-26T19:56:09.0086940Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0, line 29 <- wrt source file 2025-08-26T19:56:09.0090547Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_internal/optests/autograd_registration.py::autograd_registration_check:0 2025-08-26T19:56:09.0093464Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0, line 277 <- wrt source file 2025-08-26T19:56:09.0095943Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_is_leaf:0 2025-08-26T19:56:09.0098402Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0, line 320 <- wrt source file 2025-08-26T19:56:09.0100913Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_flatten:0 2025-08-26T19:56:09.0103394Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0, line 357 <- wrt source file 2025-08-26T19:56:09.0105941Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_unflatten:0 2025-08-26T19:56:09.0108384Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0, line 387 <- wrt source file 2025-08-26T19:56:09.0110850Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_iter:0 2025-08-26T19:56:09.0113239Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0, line 422 <- wrt source file 2025-08-26T19:56:09.0115713Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_leaves:0 2025-08-26T19:56:09.0118180Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0, line 457 <- wrt source file 2025-08-26T19:56:09.0120731Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_structure:0 2025-08-26T19:56:09.0123204Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_map:0, line 494 <- wrt source file 2025-08-26T19:56:09.0125606Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::tree_map:0 2025-08-26T19:56:09.0128070Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0, line 893 <- wrt source file 2025-08-26T19:56:09.0130729Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py::broadcast_prefix:0 2025-08-26T19:56:09.0133284Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_dataclass:0, line 303 <- wrt source file 2025-08-26T19:56:09.0135855Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_dataclass:0 2025-08-26T19:56:09.0138493Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_constant:0, line 419 <- wrt source file 2025-08-26T19:56:09.0141119Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::register_constant:0 2025-08-26T19:56:09.0143542Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_is_leaf:0, line 1026 <- wrt source file 2025-08-26T19:56:09.0145956Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_is_leaf:0 2025-08-26T19:56:09.0148391Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_map:0, line 1345 <- wrt source file 2025-08-26T19:56:09.0150742Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_pytree.py::tree_map:0 2025-08-26T19:56:09.0153411Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0, line 69 <- wrt source file 2025-08-26T19:56:09.0156471Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::rename_privateuse1_backend:0 2025-08-26T19:56:09.0159637Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/backend_registration.py::generate_methods_for_privateuse1_backend:0, line 375 <- wrt source file 2025-08-26T19:56:09.0162997Z * SKIPPED: 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SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py::set_checkpoint_early_stop:0 2025-08-26T19:56:09.0182696Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/dlpack.py::from_dlpack:0, line 93 <- wrt source file 2025-08-26T19:56:09.0185098Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/dlpack.py::from_dlpack:0 2025-08-26T19:56:09.0187872Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0, line 724 <- wrt source file 2025-08-26T19:56:09.0660785Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_sympy/functions.py::MinMaxBase._collapse_arguments:0 2025-08-26T19:56:09.0663605Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/dataset.py::IterableDataset:0, line 94 <- wrt source file 2025-08-26T19:56:09.0666298Z * SKIPPED: 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2025-08-26T19:56:09.0684290Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_convert:0, line 39 <- wrt source file 2025-08-26T19:56:09.0687071Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_convert:0 2025-08-26T19:56:09.0689774Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::collate:0, line 137 <- wrt source file 2025-08-26T19:56:09.0692390Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::collate:0 2025-08-26T19:56:09.0695016Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_collate:0, line 364 <- wrt source file 2025-08-26T19:56:09.0697798Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/_utils/collate.py::default_collate:0 2025-08-26T19:56:09.0700585Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0, line 268 <- wrt source file 2025-08-26T19:56:09.0703453Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py::MapDataPipe:0 2025-08-26T19:56:09.0706437Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0, line 53 <- wrt source file 2025-08-26T19:56:09.0709604Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::MapperIterDataPipe:0 2025-08-26T19:56:09.0712742Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0, line 201 <- wrt source file 2025-08-26T19:56:09.0715964Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/callable.py::CollatorIterDataPipe:0 2025-08-26T19:56:09.0719200Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0, line 90 <- wrt source file 2025-08-26T19:56:09.0722663Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combinatorics.py::ShufflerIterDataPipe:0 2025-08-26T19:56:09.0725884Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0, line 38 <- wrt source file 2025-08-26T19:56:09.0729198Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ConcaterIterDataPipe:0 2025-08-26T19:56:09.0732369Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py::ForkerIterDataPipe:0, line 88 <- wrt source file 2025-08-26T19:56:09.0735543Z * SKIPPED: 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source file 2025-08-26T19:56:09.0754992Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::BatcherIterDataPipe:0 2025-08-26T19:56:09.0758166Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0, line 113 <- wrt source file 2025-08-26T19:56:09.0761419Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py::UnBatcherIterDataPipe:0 2025-08-26T19:56:09.0764588Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0, line 37 <- wrt source file 2025-08-26T19:56:09.0767804Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/selecting.py::FilterIterDataPipe:0 2025-08-26T19:56:09.0771137Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0, line 25 <- wrt source file 2025-08-26T19:56:09.0774588Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/streamreader.py::StreamReaderIterDataPipe:0 2025-08-26T19:56:09.0777881Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0, line 29 <- wrt source file 2025-08-26T19:56:09.0781200Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/utils.py::IterableWrapperIterDataPipe:0 2025-08-26T19:56:09.0784365Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0, line 35 <- wrt source file 2025-08-26T19:56:09.0787493Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/callable.py::MapperMapDataPipe:0 2025-08-26T19:56:09.0790751Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0, line 34 <- wrt source file 2025-08-26T19:56:09.0794086Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combinatorics.py::ShufflerIterDataPipe:0 2025-08-26T19:56:09.0797291Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0, line 29 <- wrt source file 2025-08-26T19:56:09.0800488Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ConcaterMapDataPipe:0 2025-08-26T19:56:09.0803600Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0, line 73 <- wrt source file 2025-08-26T19:56:09.0806780Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/combining.py::ZipperMapDataPipe:0 2025-08-26T19:56:09.0809978Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0, line 29 <- wrt source file 2025-08-26T19:56:09.0813137Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/grouping.py::BatcherMapDataPipe:0 2025-08-26T19:56:09.0816390Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0, line 29 <- wrt source file 2025-08-26T19:56:09.0819650Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/map/utils.py::SequenceWrapperMapDataPipe:0 2025-08-26T19:56:09.0822770Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0, line 37 <- wrt source file 2025-08-26T19:56:09.0825878Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/common.py::validate_input_col:0 2025-08-26T19:56:09.0828900Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0, line 47 <- wrt source file 2025-08-26T19:56:09.0831933Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/utils/decoder.py::basichandlers:0 2025-08-26T19:56:09.0834821Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0, line 439 <- wrt source file 2025-08-26T19:56:09.0837836Z * SUCCESS: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::find_closure_group:0 2025-08-26T19:56:09.0840706Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0, line 535 <- wrt source file 2025-08-26T19:56:09.0843678Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/hipify/hipify_python.py::replace_extern_shared:0 2025-08-26T19:56:09.0846590Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0, line 216 <- wrt source file 2025-08-26T19:56:09.0849585Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.__init__:0 2025-08-26T19:56:09.0852548Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0, line 314 <- wrt source file 2025-08-26T19:56:09.0855600Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_hparams:0 2025-08-26T19:56:09.0858663Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0, line 362 <- wrt source file 2025-08-26T19:56:09.0861675Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalar:0 2025-08-26T19:56:09.0866516Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0, line 394 <- wrt source file 2025-08-26T19:56:09.0869563Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_scalars:0 2025-08-26T19:56:09.0872546Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0, line 441 <- wrt source file 2025-08-26T19:56:09.0875548Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_tensor:0 2025-08-26T19:56:09.0878627Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0, line 480 <- wrt source file 2025-08-26T19:56:09.0881721Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram:0 2025-08-26T19:56:09.0884912Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0, line 533 <- wrt source file 2025-08-26T19:56:09.0888086Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_histogram_raw:0 2025-08-26T19:56:09.0891182Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0, line 599 <- wrt source file 2025-08-26T19:56:09.0894186Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_image:0 2025-08-26T19:56:09.0897144Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0, line 648 <- wrt source file 2025-08-26T19:56:09.0900158Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_images:0 2025-08-26T19:56:09.0903100Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0, line 811 <- wrt source file 2025-08-26T19:56:09.0906081Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_text:0 2025-08-26T19:56:09.0909061Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0, line 878 <- wrt source file 2025-08-26T19:56:09.0912158Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_embedding:0 2025-08-26T19:56:09.0915153Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0, line 989 <- wrt source file 2025-08-26T19:56:09.0918197Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_pr_curve:0 2025-08-26T19:56:09.0921456Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0, line 1063 <- wrt source file 2025-08-26T19:56:09.0924977Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_multilinechart:0 2025-08-26T19:56:09.0928464Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0, line 1084 <- wrt source file 2025-08-26T19:56:09.0931990Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars_marginchart:0 2025-08-26T19:56:09.0935264Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0, line 1108 <- wrt source file 2025-08-26T19:56:09.0938583Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_custom_scalars:0 2025-08-26T19:56:09.0941630Z * DOCTEST : /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0, line 1154 <- wrt source file 2025-08-26T19:56:09.0944679Z * SKIPPED: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/tensorboard/writer.py::SummaryWriter.add_mesh:0 2025-08-26T19:56:09.0946222Z ============ 2025-08-26T19:56:09.0946741Z Finished doctests 2025-08-26T19:56:09.0947174Z 338 / 731 passed 2025-08-26T19:56:09.0947639Z  2025-08-26T19:56:09.0948217Z === Found 146 parse-time warnings === 2025-08-26T19:56:09.0949030Z --- Parse Warning: 1 / 146 --- 2025-08-26T19:56:09.0951344Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Tensor.dim_order in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py line=1493. 2025-08-26T19:56:09.0953883Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.0954822Z 2025-08-26T19:56:09.0955279Z dim_order(ambiguity_check=False) -> tuple 2025-08-26T19:56:09.0955914Z 2025-08-26T19:56:09.0956587Z Returns the uniquely determined tuple of int describing the dim order or 2025-08-26T19:56:09.0957526Z physical layout of :attr:`self`. 2025-08-26T19:56:09.0958099Z 2025-08-26T19:56:09.0958832Z The dim order represents how dimensions are laid out in memory of dense tensors, 2025-08-26T19:56:09.0959927Z starting from the outermost to the innermost dimension. 2025-08-26T19:56:09.0960679Z 2025-08-26T19:56:09.0961263Z Note that the dim order may not always be uniquely determined. 2025-08-26T19:56:09.0962673Z If `ambiguity_check` is True, this function raises a RuntimeError when the dim order cannot be uniquely determined; 2025-08-26T19:56:09.0964516Z If `ambiguity_check` is a list of memory formats, this function raises a RuntimeError when tensor can not be interpreted 2025-08-26T19:56:09.0966090Z into exactly one of the given memory formats, or it cannot be uniquely determined. 2025-08-26T19:56:09.0967518Z If `ambiguity_check` is False, it will return one of legal dim order(s) without checking its uniqueness. 2025-08-26T19:56:09.0968653Z Otherwise, it will raise TypeError. 2025-08-26T19:56:09.0969315Z 2025-08-26T19:56:09.0969679Z Args: 2025-08-26T19:56:09.0970555Z ambiguity_check (bool or List[torch.memory_format]): The check method for ambiguity of dim order. 2025-08-26T19:56:09.0971624Z 2025-08-26T19:56:09.0972017Z Examples:: 2025-08-26T19:56:09.0972420Z 2025-08-26T19:56:09.0972844Z >>> torch.empty((2, 3, 5, 7)).dim_order() 2025-08-26T19:56:09.0973471Z (0, 1, 2, 3) 2025-08-26T19:56:09.0974056Z >>> torch.empty((2, 3, 5, 7)).transpose(1, 2).dim_order() 2025-08-26T19:56:09.0974750Z (0, 2, 1, 3) 2025-08-26T19:56:09.0975437Z >>> torch.empty((2, 3, 5, 7), memory_format=torch.channels_last).dim_order() 2025-08-26T19:56:09.0976258Z (0, 2, 3, 1) 2025-08-26T19:56:09.0976758Z >>> torch.empty((1, 2, 3, 4)).dim_order() 2025-08-26T19:56:09.0977458Z (0, 1, 2, 3) 2025-08-26T19:56:09.0977906Z >>> try: 2025-08-26T19:56:09.0978497Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check=True) 2025-08-26T19:56:09.0979285Z ... except RuntimeError as e: 2025-08-26T19:56:09.0979854Z ... print(e) 2025-08-26T19:56:09.0980785Z The tensor does not have unique dim order, or cannot map to exact one of the given memory formats. 2025-08-26T19:56:09.0981878Z >>> torch.empty((1, 2, 3, 4)).dim_order( 2025-08-26T19:56:09.0982736Z ... ambiguity_check=[torch.contiguous_format, torch.channels_last] 2025-08-26T19:56:09.0983631Z ... ) # It can be mapped to contiguous format 2025-08-26T19:56:09.0984269Z (0, 1, 2, 3) 2025-08-26T19:56:09.0984713Z >>> try: 2025-08-26T19:56:09.0985324Z ... torch.empty((1, 2, 3, 4)).dim_order(ambiguity_check="ILLEGAL") 2025-08-26T19:56:09.0986115Z ... except TypeError as e: 2025-08-26T19:56:09.0986685Z ... print(e) 2025-08-26T19:56:09.0987491Z The ambiguity_check argument must be a bool or a list of memory formats. 2025-08-26T19:56:09.0988360Z 2025-08-26T19:56:09.0988729Z .. warning:: 2025-08-26T19:56:09.0989379Z The dim_order tensor API is experimental and subject to change. 2025-08-26T19:56:09.0990171Z 2025-08-26T19:56:09.0990885Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.0991800Z 2025-08-26T19:56:09.0992186Z warnings.warn(msg) 2025-08-26T19:56:09.0992669Z 2025-08-26T19:56:09.0993351Z --- Parse Warning: 2 / 146 --- 2025-08-26T19:56:09.0995564Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=meshgrid in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=397. 2025-08-26T19:56:09.0998057Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.0999324Z Creates grids of coordinates specified by the 1D inputs in `attr`:tensors. 2025-08-26T19:56:09.1000217Z 2025-08-26T19:56:09.1000776Z This is helpful when you want to visualize data over some 2025-08-26T19:56:09.1001642Z range of inputs. See below for a plotting example. 2025-08-26T19:56:09.1002345Z 2025-08-26T19:56:09.1002870Z Given :math:`N` 1D tensors :math:`T_0 \ldots T_{N-1}` as 2025-08-26T19:56:09.1003797Z inputs with corresponding sizes :math:`S_0 \ldots S_{N-1}`, 2025-08-26T19:56:09.1004775Z this creates :math:`N` N-dimensional tensors :math:`G_0 \ldots 2025-08-26T19:56:09.1005694Z G_{N-1}`, each with shape :math:`(S_0, ..., S_{N-1})` where 2025-08-26T19:56:09.1006599Z the output :math:`G_i` is constructed by expanding :math:`T_i` 2025-08-26T19:56:09.1007408Z to the result shape. 2025-08-26T19:56:09.1007937Z 2025-08-26T19:56:09.1008309Z .. note:: 2025-08-26T19:56:09.1008961Z 0D inputs are treated equivalently to 1D inputs of a 2025-08-26T19:56:09.1009713Z single element. 2025-08-26T19:56:09.1010230Z 2025-08-26T19:56:09.1010605Z .. warning:: 2025-08-26T19:56:09.1011267Z `torch.meshgrid(*tensors)` currently has the same behavior 2025-08-26T19:56:09.1012180Z as calling `numpy.meshgrid(*arrays, indexing='ij')`. 2025-08-26T19:56:09.1012899Z 2025-08-26T19:56:09.1013381Z In the future `torch.meshgrid` will transition to 2025-08-26T19:56:09.1014135Z `indexing='xy'` as the default. 2025-08-26T19:56:09.1014739Z 2025-08-26T19:56:09.1015312Z https://github.com/pytorch/pytorch/issues/50276 tracks 2025-08-26T19:56:09.1016234Z this issue with the goal of migrating to NumPy's behavior. 2025-08-26T19:56:09.1016988Z 2025-08-26T19:56:09.1017372Z .. seealso:: 2025-08-26T19:56:09.1017842Z 2025-08-26T19:56:09.1018416Z :func:`torch.cartesian_prod` has the same effect but it 2025-08-26T19:56:09.1019242Z collects the data in a tensor of vectors. 2025-08-26T19:56:09.1019883Z 2025-08-26T19:56:09.1020257Z Args: 2025-08-26T19:56:09.1021017Z tensors (list of Tensor): list of scalars or 1 dimensional tensors. Scalars will be 2025-08-26T19:56:09.1022111Z treated as tensors of size :math:`(1,)` automatically 2025-08-26T19:56:09.1022835Z 2025-08-26T19:56:09.1023387Z indexing: (str, optional): the indexing mode, either "xy" 2025-08-26T19:56:09.1024295Z or "ij", defaults to "ij". See warning for future changes. 2025-08-26T19:56:09.1025034Z 2025-08-26T19:56:09.1025534Z If "xy" is selected, the first dimension corresponds 2025-08-26T19:56:09.1026393Z to the cardinality of the second input and the second 2025-08-26T19:56:09.1027286Z dimension corresponds to the cardinality of the first 2025-08-26T19:56:09.1028068Z input. 2025-08-26T19:56:09.1028550Z 2025-08-26T19:56:09.1029047Z If "ij" is selected, the dimensions are in the same 2025-08-26T19:56:09.1029834Z order as the cardinality of the inputs. 2025-08-26T19:56:09.1030475Z 2025-08-26T19:56:09.1030863Z Returns: 2025-08-26T19:56:09.1031455Z seq (sequence of Tensors): If the input has :math:`N` 2025-08-26T19:56:09.1032315Z tensors of size :math:`S_0 \ldots S_{N-1}``, then the 2025-08-26T19:56:09.1033269Z output will also have :math:`N` tensors, where each tensor 2025-08-26T19:56:09.1034105Z is of shape :math:`(S_0, ..., S_{N-1})`. 2025-08-26T19:56:09.1034735Z 2025-08-26T19:56:09.1035126Z Example:: 2025-08-26T19:56:09.1035565Z 2025-08-26T19:56:09.1035989Z >>> x = torch.tensor([1, 2, 3]) 2025-08-26T19:56:09.1036642Z >>> y = torch.tensor([4, 5, 6]) 2025-08-26T19:56:09.1037249Z 2025-08-26T19:56:09.1037955Z Observe the element-wise pairings across the grid, (1, 4), 2025-08-26T19:56:09.1038814Z (1, 5), ..., (3, 6). This is the same thing as the 2025-08-26T19:56:09.1039503Z cartesian product. 2025-08-26T19:56:09.1040200Z >>> grid_x, grid_y = torch.meshgrid(x, y, indexing='ij') 2025-08-26T19:56:09.1040913Z >>> grid_x 2025-08-26T19:56:09.1041426Z tensor([[1, 1, 1], 2025-08-26T19:56:09.1041971Z [2, 2, 2], 2025-08-26T19:56:09.1042521Z [3, 3, 3]]) 2025-08-26T19:56:09.1043051Z >>> grid_y 2025-08-26T19:56:09.1043546Z tensor([[4, 5, 6], 2025-08-26T19:56:09.1044103Z [4, 5, 6], 2025-08-26T19:56:09.1044642Z [4, 5, 6]]) 2025-08-26T19:56:09.1045162Z 2025-08-26T19:56:09.1045691Z This correspondence can be seen when these grids are 2025-08-26T19:56:09.1046449Z stacked properly. 2025-08-26T19:56:09.1047206Z >>> torch.equal(torch.cat(tuple(torch.dstack([grid_x, grid_y]))), 2025-08-26T19:56:09.1048065Z ... torch.cartesian_prod(x, y)) 2025-08-26T19:56:09.1048705Z True 2025-08-26T19:56:09.1049202Z 2025-08-26T19:56:09.1049749Z `torch.meshgrid` is commonly used to produce a grid for 2025-08-26T19:56:09.1050496Z plotting. 2025-08-26T19:56:09.1051063Z >>> # xdoctest: +REQUIRES(module:matplotlib) 2025-08-26T19:56:09.1051793Z >>> # xdoctest: +REQUIRES(env:DOCTEST_SHOW) 2025-08-26T19:56:09.1052511Z >>> import matplotlib.pyplot as plt 2025-08-26T19:56:09.1053215Z >>> xs = torch.linspace(-5, 5, steps=100) 2025-08-26T19:56:09.1053900Z >>> ys = torch.linspace(-5, 5, steps=100) 2025-08-26T19:56:09.1054728Z >>> x, y = torch.meshgrid(xs, ys, indexing='xy') 2025-08-26T19:56:09.1055467Z >>> z = torch.sin(torch.sqrt(x * x + y * y)) 2025-08-26T19:56:09.1056173Z >>> ax = plt.axes(projection='3d') 2025-08-26T19:56:09.1056901Z >>> ax.plot_surface(x.numpy(), y.numpy(), z.numpy()) 2025-08-26T19:56:09.1057624Z >>> plt.show() 2025-08-26T19:56:09.1058134Z 2025-08-26T19:56:09.1058578Z .. image:: ../_static/img/meshgrid.png 2025-08-26T19:56:09.1059203Z :width: 512 2025-08-26T19:56:09.1059690Z 2025-08-26T19:56:09.1060069Z 2025-08-26T19:56:09.1060812Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1061712Z 2025-08-26T19:56:09.1062110Z warnings.warn(msg) 2025-08-26T19:56:09.1062599Z 2025-08-26T19:56:09.1063230Z --- Parse Warning: 3 / 146 --- 2025-08-26T19:56:09.1065445Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_unique_impl in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/functional.py line=793. 2025-08-26T19:56:09.1068038Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1069590Z unique(input, sorted=True, return_inverse=False, return_counts=False, dim=None) -> tuple[Tensor, Tensor, Tensor] 2025-08-26T19:56:09.1070787Z 2025-08-26T19:56:09.1071291Z Returns the unique elements of the input tensor. 2025-08-26T19:56:09.1071966Z 2025-08-26T19:56:09.1072861Z .. note:: This function is different from :func:`torch.unique_consecutive` in the sense that 2025-08-26T19:56:09.1074108Z this function also eliminates non-consecutive duplicate values. 2025-08-26T19:56:09.1074935Z 2025-08-26T19:56:09.1075587Z .. note:: Currently in the CUDA implementation and the CPU implementation, 2025-08-26T19:56:09.1076860Z `torch.unique` always sort the tensor at the beginning regardless of the `sort` argument. 2025-08-26T19:56:09.1078262Z Sorting could be slow, so if your input tensor is already sorted, it is recommended to use 2025-08-26T19:56:09.1079428Z :func:`torch.unique_consecutive` which avoids the sorting. 2025-08-26T19:56:09.1080177Z 2025-08-26T19:56:09.1080540Z Args: 2025-08-26T19:56:09.1081005Z input (Tensor): the input tensor 2025-08-26T19:56:09.1081875Z sorted (bool): Whether to sort the unique elements in ascending order 2025-08-26T19:56:09.1082764Z before returning as output. 2025-08-26T19:56:09.1083601Z return_inverse (bool): Whether to also return the indices for where 2025-08-26T19:56:09.1084698Z elements in the original input ended up in the returned unique list. 2025-08-26T19:56:09.1085820Z return_counts (bool): Whether to also return the counts for each unique 2025-08-26T19:56:09.1086686Z element. 2025-08-26T19:56:09.1087383Z dim (int, optional): the dimension to operate upon. If ``None``, the 2025-08-26T19:56:09.1088434Z unique of the flattened input is returned. Otherwise, each of the 2025-08-26T19:56:09.1089552Z tensors indexed by the given dimension is treated as one of the 2025-08-26T19:56:09.1090614Z elements to apply the unique operation upon. See examples for more 2025-08-26T19:56:09.1091495Z details. Default: ``None`` 2025-08-26T19:56:09.1092068Z 2025-08-26T19:56:09.1092446Z Returns: 2025-08-26T19:56:09.1093282Z (Tensor, Tensor (optional), Tensor (optional)): A tensor or a tuple of tensors containing 2025-08-26T19:56:09.1094264Z 2025-08-26T19:56:09.1094834Z - **output** (*Tensor*): the output list of unique scalar elements. 2025-08-26T19:56:09.1095726Z - **inverse_indices** (*Tensor*): (optional) if 2025-08-26T19:56:09.1096581Z :attr:`return_inverse` is True, there will be an additional 2025-08-26T19:56:09.1097637Z returned tensor (same shape as input) representing the indices 2025-08-26T19:56:09.1098657Z for where elements in the original input map to in the output; 2025-08-26T19:56:09.1099660Z otherwise, this function will only return a single tensor. 2025-08-26T19:56:09.1100516Z - **counts** (*Tensor*): (optional) if 2025-08-26T19:56:09.1101317Z :attr:`return_counts` is True, there will be an additional 2025-08-26T19:56:09.1102289Z returned tensor (same shape as output or output.size(dim), 2025-08-26T19:56:09.1103275Z if dim was specified) representing the number of occurrences 2025-08-26T19:56:09.1104108Z for each unique value or tensor. 2025-08-26T19:56:09.1104731Z 2025-08-26T19:56:09.1105120Z Example:: 2025-08-26T19:56:09.1105538Z 2025-08-26T19:56:09.1106161Z >>> output = torch.unique(torch.tensor([1, 3, 2, 3], dtype=torch.long)) 2025-08-26T19:56:09.1107044Z >>> output 2025-08-26T19:56:09.1107521Z tensor([1, 2, 3]) 2025-08-26T19:56:09.1108022Z 2025-08-26T19:56:09.1108484Z >>> output, inverse_indices = torch.unique( 2025-08-26T19:56:09.1109424Z ... torch.tensor([1, 3, 2, 3], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T19:56:09.1110306Z >>> output 2025-08-26T19:56:09.1110762Z tensor([1, 2, 3]) 2025-08-26T19:56:09.1111297Z >>> inverse_indices 2025-08-26T19:56:09.1111926Z tensor([0, 2, 1, 2]) 2025-08-26T19:56:09.1112446Z 2025-08-26T19:56:09.1112889Z >>> output, inverse_indices = torch.unique( 2025-08-26T19:56:09.1113827Z ... torch.tensor([[1, 3], [2, 3]], dtype=torch.long), sorted=True, return_inverse=True) 2025-08-26T19:56:09.1114713Z >>> output 2025-08-26T19:56:09.1115191Z tensor([1, 2, 3]) 2025-08-26T19:56:09.1115711Z >>> inverse_indices 2025-08-26T19:56:09.1116243Z tensor([[0, 2], 2025-08-26T19:56:09.1116744Z [1, 2]]) 2025-08-26T19:56:09.1117240Z 2025-08-26T19:56:09.1117618Z >>> a = torch.tensor([ 2025-08-26T19:56:09.1118157Z ... [ 2025-08-26T19:56:09.1118616Z ... [1, 1, 0, 0], 2025-08-26T19:56:09.1119170Z ... [1, 1, 0, 0], 2025-08-26T19:56:09.1119709Z ... [0, 0, 1, 1], 2025-08-26T19:56:09.1120249Z ... ], 2025-08-26T19:56:09.1120701Z ... [ 2025-08-26T19:56:09.1121158Z ... [0, 0, 1, 1], 2025-08-26T19:56:09.1121701Z ... [0, 0, 1, 1], 2025-08-26T19:56:09.1122248Z ... [1, 1, 1, 1], 2025-08-26T19:56:09.1122792Z ... ], 2025-08-26T19:56:09.1123242Z ... [ 2025-08-26T19:56:09.1123684Z ... [1, 1, 0, 0], 2025-08-26T19:56:09.1124245Z ... [1, 1, 0, 0], 2025-08-26T19:56:09.1124801Z ... [0, 0, 1, 1], 2025-08-26T19:56:09.1125345Z ... ], 2025-08-26T19:56:09.1125779Z ... ]) 2025-08-26T19:56:09.1126202Z 2025-08-26T19:56:09.1126827Z >>> # If we call `torch.unique(a, dim=0)`, each of the tensors `a[idx, :, :]` 2025-08-26T19:56:09.1127895Z >>> # will be compared. We can see that `a[0, :, :]` and `a[2, :, :]` match 2025-08-26T19:56:09.1128866Z >>> # each other, so one of them will be removed. 2025-08-26T19:56:09.1129568Z >>> (a[0, :, :] == a[2, :, :]).all() 2025-08-26T19:56:09.1130173Z tensor(True) 2025-08-26T19:56:09.1130727Z >>> a_unique_dim0 = torch.unique(a, dim=0) 2025-08-26T19:56:09.1131362Z >>> a_unique_dim0 2025-08-26T19:56:09.1131890Z tensor([[[0, 0, 1, 1], 2025-08-26T19:56:09.1132439Z [0, 0, 1, 1], 2025-08-26T19:56:09.1132981Z [1, 1, 1, 1]], 2025-08-26T19:56:09.1133562Z [[1, 1, 0, 0], 2025-08-26T19:56:09.1134108Z [1, 1, 0, 0], 2025-08-26T19:56:09.1134644Z [0, 0, 1, 1]]]) 2025-08-26T19:56:09.1135187Z 2025-08-26T19:56:09.1135812Z >>> # Notice which sub-tensors from `a` match with the sub-tensors from 2025-08-26T19:56:09.1136673Z >>> # `a_unique_dim0`: 2025-08-26T19:56:09.1137282Z >>> (a_unique_dim0[0, :, :] == a[1, :, :]).all() 2025-08-26T19:56:09.1138068Z tensor(True) 2025-08-26T19:56:09.1138603Z >>> (a_unique_dim0[1, :, :] == a[0, :, :]).all() 2025-08-26T19:56:09.1139254Z tensor(True) 2025-08-26T19:56:09.1139726Z 2025-08-26T19:56:09.1140340Z >>> # For `torch.unique(a, dim=1)`, each of the tensors `a[:, idx, :]` are 2025-08-26T19:56:09.1141324Z >>> # compared. `a[:, 0, :]` and `a[:, 1, :]` match each other, so one of 2025-08-26T19:56:09.1142124Z >>> # them will be removed. 2025-08-26T19:56:09.1142815Z >>> (a[:, 0, :] == a[:, 1, :]).all() 2025-08-26T19:56:09.1143422Z tensor(True) 2025-08-26T19:56:09.1143932Z >>> torch.unique(a, dim=1) 2025-08-26T19:56:09.1144507Z tensor([[[0, 0, 1, 1], 2025-08-26T19:56:09.1145053Z [1, 1, 0, 0]], 2025-08-26T19:56:09.1145591Z [[1, 1, 1, 1], 2025-08-26T19:56:09.1146119Z [0, 0, 1, 1]], 2025-08-26T19:56:09.1146638Z [[0, 0, 1, 1], 2025-08-26T19:56:09.1147169Z [1, 1, 0, 0]]]) 2025-08-26T19:56:09.1147794Z 2025-08-26T19:56:09.1148410Z >>> # For `torch.unique(a, dim=2)`, the tensors `a[:, :, idx]` are compared. 2025-08-26T19:56:09.1149348Z >>> # `a[:, :, 0]` and `a[:, :, 1]` match each other. Also, `a[:, :, 2]` and 2025-08-26T19:56:09.1150228Z >>> # `a[:, :, 3]` match each other as well. So in this case, two of the 2025-08-26T19:56:09.1151038Z >>> # sub-tensors will be removed. 2025-08-26T19:56:09.1151681Z >>> (a[:, :, 0] == a[:, :, 1]).all() 2025-08-26T19:56:09.1152271Z tensor(True) 2025-08-26T19:56:09.1152776Z >>> (a[:, :, 2] == a[:, :, 3]).all() 2025-08-26T19:56:09.1153373Z tensor(True) 2025-08-26T19:56:09.1153882Z >>> torch.unique(a, dim=2) 2025-08-26T19:56:09.1154458Z tensor([[[0, 1], 2025-08-26T19:56:09.1154965Z [0, 1], 2025-08-26T19:56:09.1155461Z [1, 0]], 2025-08-26T19:56:09.1155964Z [[1, 0], 2025-08-26T19:56:09.1156449Z [1, 0], 2025-08-26T19:56:09.1156947Z [1, 1]], 2025-08-26T19:56:09.1157450Z [[0, 1], 2025-08-26T19:56:09.1157948Z [0, 1], 2025-08-26T19:56:09.1158434Z [1, 0]]]) 2025-08-26T19:56:09.1158930Z 2025-08-26T19:56:09.1159657Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1160582Z 2025-08-26T19:56:09.1160971Z warnings.warn(msg) 2025-08-26T19:56:09.1161457Z 2025-08-26T19:56:09.1162061Z --- Parse Warning: 4 / 146 --- 2025-08-26T19:56:09.1164156Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=565. 2025-08-26T19:56:09.1166532Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1167476Z 2025-08-26T19:56:09.1168003Z Load a model from a github repo or a local directory. 2025-08-26T19:56:09.1168710Z 2025-08-26T19:56:09.1169423Z Note: Loading a model is the typical use case, but this can also be used to 2025-08-26T19:56:09.1170550Z for loading other objects such as tokenizers, loss functions, etc. 2025-08-26T19:56:09.1171376Z 2025-08-26T19:56:09.1171915Z If ``source`` is 'github', ``repo_or_dir`` is expected to be 2025-08-26T19:56:09.1172879Z of the form ``repo_owner/repo_name[:ref]`` with an optional 2025-08-26T19:56:09.1173622Z ref (a tag or a branch). 2025-08-26T19:56:09.1174135Z 2025-08-26T19:56:09.1174672Z If ``source`` is 'local', ``repo_or_dir`` is expected to be a 2025-08-26T19:56:09.1175441Z path to a local directory. 2025-08-26T19:56:09.1175952Z 2025-08-26T19:56:09.1176333Z Args: 2025-08-26T19:56:09.1176812Z repo_or_dir (str): If ``source`` is 'github', 2025-08-26T19:56:09.1177877Z this should correspond to a github repo with format ``repo_owner/repo_name[:ref]`` with 2025-08-26T19:56:09.1179296Z an optional ref (tag or branch), for example 'pytorch/vision:0.10'. If ``ref`` is not specified, 2025-08-26T19:56:09.1180661Z the default branch is assumed to be ``main`` if it exists, and otherwise ``master``. 2025-08-26T19:56:09.1181826Z If ``source`` is 'local' then it should be a path to a local directory. 2025-08-26T19:56:09.1182884Z model (str): the name of a callable (entrypoint) defined in the 2025-08-26T19:56:09.1183691Z repo/dir's ``hubconf.py``. 2025-08-26T19:56:09.1184487Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T19:56:09.1185455Z source (str, optional): 'github' or 'local'. Specifies how 2025-08-26T19:56:09.1186356Z ``repo_or_dir`` is to be interpreted. Default is 'github'. 2025-08-26T19:56:09.1187336Z trust_repo (bool, str or None): ``"check"``, ``True``, ``False`` or ``None``. 2025-08-26T19:56:09.1188513Z This parameter was introduced in v1.12 and helps ensuring that users 2025-08-26T19:56:09.1189456Z only run code from repos that they trust. 2025-08-26T19:56:09.1190097Z 2025-08-26T19:56:09.1190673Z - If ``False``, a prompt will ask the user whether the repo should 2025-08-26T19:56:09.1191457Z be trusted. 2025-08-26T19:56:09.1192143Z - If ``True``, the repo will be added to the trusted list and loaded 2025-08-26T19:56:09.1193014Z without requiring explicit confirmation. 2025-08-26T19:56:09.1193823Z - If ``"check"``, the repo will be checked against the list of 2025-08-26T19:56:09.1194810Z trusted repos in the cache. If it is not present in that list, the 2025-08-26T19:56:09.1195845Z behaviour will fall back onto the ``trust_repo=False`` option. 2025-08-26T19:56:09.1196839Z - If ``None``: this will raise a warning, inviting the user to set 2025-08-26T19:56:09.1197814Z ``trust_repo`` to either ``False``, ``True`` or ``"check"``. This 2025-08-26T19:56:09.1198838Z is only present for backward compatibility and will be removed in 2025-08-26T19:56:09.1199645Z v2.0. 2025-08-26T19:56:09.1200069Z 2025-08-26T19:56:09.1200680Z Default is ``None`` and will eventually change to ``"check"`` in v2.0. 2025-08-26T19:56:09.1201752Z force_reload (bool, optional): whether to force a fresh download of 2025-08-26T19:56:09.1202782Z the github repo unconditionally. Does not have any effect if 2025-08-26T19:56:09.1203637Z ``source = 'local'``. Default is ``False``. 2025-08-26T19:56:09.1204508Z verbose (bool, optional): If ``False``, mute messages about hitting 2025-08-26T19:56:09.1205572Z local caches. Note that the message about first download cannot be 2025-08-26T19:56:09.1206558Z muted. Does not have any effect if ``source = 'local'``. 2025-08-26T19:56:09.1207312Z Default is ``True``. 2025-08-26T19:56:09.1208265Z skip_validation (bool, optional): if ``False``, torchhub will check that the branch or commit 2025-08-26T19:56:09.1209785Z specified by the ``github`` argument properly belongs to the repo owner. This will make 2025-08-26T19:56:09.1211148Z requests to the GitHub API; you can specify a non-default GitHub token by setting the 2025-08-26T19:56:09.1212321Z ``GITHUB_TOKEN`` environment variable. Default is ``False``. 2025-08-26T19:56:09.1213331Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T19:56:09.1214164Z 2025-08-26T19:56:09.1214549Z Returns: 2025-08-26T19:56:09.1215156Z The output of the ``model`` callable when called with the given 2025-08-26T19:56:09.1215939Z ``*args`` and ``**kwargs``. 2025-08-26T19:56:09.1216494Z 2025-08-26T19:56:09.1216874Z Example: 2025-08-26T19:56:09.1217355Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T19:56:09.1218043Z >>> # from a github repo 2025-08-26T19:56:09.1218599Z >>> repo = "pytorch/vision" 2025-08-26T19:56:09.1219182Z >>> model = torch.hub.load( 2025-08-26T19:56:09.1219922Z ... repo, "resnet50", weights="ResNet50_Weights.IMAGENET1K_V1" 2025-08-26T19:56:09.1220670Z ... ) 2025-08-26T19:56:09.1221105Z >>> # from a local directory 2025-08-26T19:56:09.1221754Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T19:56:09.1222459Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.1223268Z >>> model = torch.hub.load(path, "resnet50", weights="ResNet50_Weights.DEFAULT") 2025-08-26T19:56:09.1224159Z 2025-08-26T19:56:09.1224875Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1225789Z 2025-08-26T19:56:09.1226175Z warnings.warn(msg) 2025-08-26T19:56:09.1226660Z 2025-08-26T19:56:09.1227246Z --- Parse Warning: 5 / 146 --- 2025-08-26T19:56:09.1229467Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_load_local in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=657. 2025-08-26T19:56:09.1231907Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1232849Z 2025-08-26T19:56:09.1233397Z Load a model from a local directory with a ``hubconf.py``. 2025-08-26T19:56:09.1234133Z 2025-08-26T19:56:09.1234489Z Args: 2025-08-26T19:56:09.1235077Z hubconf_dir (str): path to a local directory that contains a 2025-08-26T19:56:09.1235863Z ``hubconf.py``. 2025-08-26T19:56:09.1236565Z model (str): name of an entrypoint defined in the directory's 2025-08-26T19:56:09.1237331Z ``hubconf.py``. 2025-08-26T19:56:09.1238233Z *args (optional): the corresponding args for callable ``model``. 2025-08-26T19:56:09.1239294Z **kwargs (optional): the corresponding kwargs for callable ``model``. 2025-08-26T19:56:09.1240129Z 2025-08-26T19:56:09.1240491Z Returns: 2025-08-26T19:56:09.1241054Z a single model with corresponding pretrained weights. 2025-08-26T19:56:09.1241780Z 2025-08-26T19:56:09.1242156Z Example: 2025-08-26T19:56:09.1242607Z >>> # xdoctest: +SKIP("stub local path") 2025-08-26T19:56:09.1243312Z >>> path = "/some/local/path/pytorch/vision" 2025-08-26T19:56:09.1243987Z >>> model = _load_local( 2025-08-26T19:56:09.1244528Z ... path, 2025-08-26T19:56:09.1244976Z ... "resnet50", 2025-08-26T19:56:09.1245561Z ... weights="ResNet50_Weights.IMAGENET1K_V1", 2025-08-26T19:56:09.1246236Z ... ) 2025-08-26T19:56:09.1246638Z 2025-08-26T19:56:09.1247348Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1248274Z 2025-08-26T19:56:09.1248677Z warnings.warn(msg) 2025-08-26T19:56:09.1249216Z 2025-08-26T19:56:09.1249788Z --- Parse Warning: 6 / 146 --- 2025-08-26T19:56:09.1252021Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=download_url_to_file in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=696. 2025-08-26T19:56:09.1254543Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1255703Z Download object at the given URL to a local path. 2025-08-26T19:56:09.1256387Z 2025-08-26T19:56:09.1256743Z Args: 2025-08-26T19:56:09.1257218Z url (str): URL of the object to download 2025-08-26T19:56:09.1258150Z dst (str): Full path where object will be saved, e.g. ``/tmp/temporary_file`` 2025-08-26T19:56:09.1259530Z hash_prefix (str, optional): If not None, the SHA256 downloaded file should start with ``hash_prefix``. 2025-08-26T19:56:09.1260616Z Default: None 2025-08-26T19:56:09.1261465Z progress (bool, optional): whether or not to display a progress bar to stderr 2025-08-26T19:56:09.1262396Z Default: True 2025-08-26T19:56:09.1262905Z 2025-08-26T19:56:09.1263274Z Example: 2025-08-26T19:56:09.1263798Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T19:56:09.1264514Z >>> # xdoctest: +REQUIRES(POSIX) 2025-08-26T19:56:09.1265178Z >>> torch.hub.download_url_to_file( 2025-08-26T19:56:09.1266123Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth", 2025-08-26T19:56:09.1266987Z ... "/tmp/temporary_file", 2025-08-26T19:56:09.1267577Z ... ) 2025-08-26T19:56:09.1267996Z 2025-08-26T19:56:09.1268372Z 2025-08-26T19:56:09.1269079Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1269989Z 2025-08-26T19:56:09.1270390Z warnings.warn(msg) 2025-08-26T19:56:09.1270858Z 2025-08-26T19:56:09.1271535Z --- Parse Warning: 7 / 146 --- 2025-08-26T19:56:09.1273791Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_state_dict_from_url in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/hub.py line=821. 2025-08-26T19:56:09.1276376Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1277451Z Loads the Torch serialized object at the given URL. 2025-08-26T19:56:09.1278145Z 2025-08-26T19:56:09.1278693Z If downloaded file is a zip file, it will be automatically 2025-08-26T19:56:09.1279469Z decompressed. 2025-08-26T19:56:09.1279919Z 2025-08-26T19:56:09.1280552Z If the object is already present in `model_dir`, it's deserialized and 2025-08-26T19:56:09.1281376Z returned. 2025-08-26T19:56:09.1282059Z The default value of ``model_dir`` is ``/checkpoints`` where 2025-08-26T19:56:09.1283117Z ``hub_dir`` is the directory returned by :func:`~torch.hub.get_dir`. 2025-08-26T19:56:09.1283902Z 2025-08-26T19:56:09.1284267Z Args: 2025-08-26T19:56:09.1284756Z url (str): URL of the object to download 2025-08-26T19:56:09.1285612Z model_dir (str, optional): directory in which to save the object 2025-08-26T19:56:09.1286949Z map_location (optional): a function or a dict specifying how to remap storage locations (see torch.load) 2025-08-26T19:56:09.1288408Z progress (bool, optional): whether or not to display a progress bar to stderr. 2025-08-26T19:56:09.1289405Z Default: True 2025-08-26T19:56:09.1290416Z check_hash(bool, optional): If True, the filename part of the URL should follow the naming convention 2025-08-26T19:56:09.1291741Z ``filename-.ext`` where ```` is the first eight or more 2025-08-26T19:56:09.1292871Z digits of the SHA256 hash of the contents of the file. The hash is used to 2025-08-26T19:56:09.1293937Z ensure unique names and to verify the contents of the file. 2025-08-26T19:56:09.1294737Z Default: False 2025-08-26T19:56:09.1295755Z file_name (str, optional): name for the downloaded file. Filename from ``url`` will be used if not set. 2025-08-26T19:56:09.1297331Z weights_only(bool, optional): If True, only weights will be loaded and no complex pickled objects. 2025-08-26T19:56:09.1298788Z Recommended for untrusted sources. See :func:`~torch.load` for more details. 2025-08-26T19:56:09.1299705Z 2025-08-26T19:56:09.1300084Z Example: 2025-08-26T19:56:09.1300603Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_HUB) 2025-08-26T19:56:09.1301388Z >>> state_dict = torch.hub.load_state_dict_from_url( 2025-08-26T19:56:09.1302319Z ... "https://s3.amazonaws.com/pytorch/models/resnet18-5c106cde.pth" 2025-08-26T19:56:09.1303147Z ... ) 2025-08-26T19:56:09.1303574Z 2025-08-26T19:56:09.1303951Z 2025-08-26T19:56:09.1304669Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1305582Z 2025-08-26T19:56:09.1305982Z warnings.warn(msg) 2025-08-26T19:56:09.1306462Z 2025-08-26T19:56:09.1307017Z --- Parse Warning: 8 / 146 --- 2025-08-26T19:56:09.1309267Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Library.fallback in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=375. 2025-08-26T19:56:09.1350411Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.1351667Z Registers the function implementation as the fallback for the given key. 2025-08-26T19:56:09.1352550Z 2025-08-26T19:56:09.1353204Z This function only works for a library with global namespace ("_"). 2025-08-26T19:56:09.1354055Z 2025-08-26T19:56:09.1354624Z Args: 2025-08-26T19:56:09.1355440Z fn: function used as fallback for the given dispatch key or :func:`~fallthrough_kernel` 2025-08-26T19:56:09.1356482Z to register a fallthrough. 2025-08-26T19:56:09.1357590Z dispatch_key: dispatch key that the input function should be registered for. By default, it uses 2025-08-26T19:56:09.1358831Z the dispatch key that the library was created with. 2025-08-26T19:56:09.1360163Z with_keyset: flag controlling if the current dispatcher call keyset should be passed as the first argument 2025-08-26T19:56:09.1361809Z to :attr:`fn` when calling. This should be used to create the appropriate keyset for redispatch calls. 2025-08-26T19:56:09.1362877Z 2025-08-26T19:56:09.1363283Z Example:: 2025-08-26T19:56:09.1363739Z 2025-08-26T19:56:09.1364152Z >>> my_lib = Library("_", "IMPL") 2025-08-26T19:56:09.1364858Z >>> def fallback_kernel(op, *args, **kwargs): 2025-08-26T19:56:09.1365599Z >>> # Handle all autocast ops generically 2025-08-26T19:56:09.1366244Z >>> # ... 2025-08-26T19:56:09.1366846Z >>> my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T19:56:09.1367528Z 2025-08-26T19:56:09.1369167Z Original Error: IndentationError('expected an indented block after function definition on line 2', ('', 5, 1, 'my_lib.fallback(fallback_kernel, "Autocast")\n', 5, 7)) 2025-08-26T19:56:09.1370881Z 2025-08-26T19:56:09.1371348Z my_lib.fallback(fallback_kernel, "Autocast") 2025-08-26T19:56:09.1371980Z ^ 2025-08-26T19:56:09.1372385Z warnings.warn(msg) 2025-08-26T19:56:09.1372867Z 2025-08-26T19:56:09.1373478Z --- Parse Warning: 9 / 146 --- 2025-08-26T19:56:09.1375692Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=948. 2025-08-26T19:56:09.1378164Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.1379357Z Register a FakeTensor implementation ("fake impl") for this operator. 2025-08-26T19:56:09.1380221Z 2025-08-26T19:56:09.1380768Z Also sometimes known as a "meta kernel", "abstract impl". 2025-08-26T19:56:09.1381602Z 2025-08-26T19:56:09.1382300Z An "FakeTensor implementation" specifies the behavior of this operator on 2025-08-26T19:56:09.1383489Z Tensors that carry no data ("FakeTensor"). Given some input Tensors with 2025-08-26T19:56:09.1384642Z certain properties (sizes/strides/storage_offset/device), it specifies 2025-08-26T19:56:09.1385628Z what the properties of the output Tensors are. 2025-08-26T19:56:09.1386306Z 2025-08-26T19:56:09.1386981Z The FakeTensor implementation has the same signature as the operator. 2025-08-26T19:56:09.1388109Z It is run for both FakeTensors and meta tensors. To write a FakeTensor 2025-08-26T19:56:09.1389191Z implementation, assume that all Tensor inputs to the operator are 2025-08-26T19:56:09.1390277Z regular CPU/CUDA/Meta tensors, but they do not have storage, and 2025-08-26T19:56:09.1391336Z you are trying to return regular CPU/CUDA/Meta tensor(s) as output. 2025-08-26T19:56:09.1392456Z The FakeTensor implementation must consist of only PyTorch operations 2025-08-26T19:56:09.1393584Z (and may not directly access the storage or data of any input or 2025-08-26T19:56:09.1394405Z intermediate Tensors). 2025-08-26T19:56:09.1394942Z 2025-08-26T19:56:09.1395453Z This API may be used as a decorator (see examples). 2025-08-26T19:56:09.1396139Z 2025-08-26T19:56:09.1396612Z For a detailed guide on custom ops, please see 2025-08-26T19:56:09.1397565Z https://pytorch.org/tutorials/advanced/custom_ops_landing_page.html 2025-08-26T19:56:09.1398495Z 2025-08-26T19:56:09.1398855Z Args: 2025-08-26T19:56:09.1399528Z op_name: Operator name (along with the overload) or OpOverload object. 2025-08-26T19:56:09.1400447Z func: Fake tensor implementation. 2025-08-26T19:56:09.1401283Z lib (Optional[Library]): Library to register the fake tensor to. 2025-08-26T19:56:09.1402272Z allow_override: Flag controlling if we want to override an 2025-08-26T19:56:09.1403209Z existing registered fake impl. This is by default off, 2025-08-26T19:56:09.1404136Z and will error you're trying to register a fake impl to 2025-08-26T19:56:09.1405072Z an operator that already has a fake impl. This also only 2025-08-26T19:56:09.1405976Z applies if the custom operator was not created via 2025-08-26T19:56:09.1406892Z torch.library.custom_op, as overriding and existing fake 2025-08-26T19:56:09.1407740Z impl is already allowed. 2025-08-26T19:56:09.1408350Z 2025-08-26T19:56:09.1408729Z Examples: 2025-08-26T19:56:09.1409236Z >>> import torch 2025-08-26T19:56:09.1409775Z >>> import numpy as np 2025-08-26T19:56:09.1410363Z >>> from torch import Tensor 2025-08-26T19:56:09.1410944Z >>> 2025-08-26T19:56:09.1411543Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T19:56:09.1412581Z >>> @torch.library.custom_op("mylib::custom_linear", mutates_args=()) 2025-08-26T19:56:09.1413674Z >>> def custom_linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T19:56:09.1414698Z >>> raise NotImplementedError("Implementation goes here") 2025-08-26T19:56:09.1415446Z >>> 2025-08-26T19:56:09.1416009Z >>> @torch.library.register_fake("mylib::custom_linear") 2025-08-26T19:56:09.1416771Z >>> def _(x, weight, bias): 2025-08-26T19:56:09.1417376Z >>> assert x.dim() == 2 2025-08-26T19:56:09.1417994Z >>> assert weight.dim() == 2 2025-08-26T19:56:09.1418611Z >>> assert bias.dim() == 1 2025-08-26T19:56:09.1419274Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T19:56:09.1419989Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T19:56:09.1420762Z >>> assert x.device == weight.device 2025-08-26T19:56:09.1421372Z >>> 2025-08-26T19:56:09.1421844Z >>> return (x @ weight.t()) + bias 2025-08-26T19:56:09.1422457Z >>> 2025-08-26T19:56:09.1423040Z >>> with torch._subclasses.fake_tensor.FakeTensorMode(): 2025-08-26T19:56:09.1423796Z >>> x = torch.randn(2, 3) 2025-08-26T19:56:09.1424415Z >>> w = torch.randn(3, 3) 2025-08-26T19:56:09.1425027Z >>> b = torch.randn(3) 2025-08-26T19:56:09.1425700Z >>> y = torch.ops.mylib.custom_linear(x, w, b) 2025-08-26T19:56:09.1426369Z >>> 2025-08-26T19:56:09.1426808Z >>> assert y.shape == (2, 3) 2025-08-26T19:56:09.1427392Z >>> 2025-08-26T19:56:09.1427987Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T19:56:09.1429003Z >>> @torch.library.custom_op("mylib::custom_nonzero", mutates_args=()) 2025-08-26T19:56:09.1429957Z >>> def custom_nonzero(x: Tensor) -> Tensor: 2025-08-26T19:56:09.1430651Z >>> x_np = x.numpy(force=True) 2025-08-26T19:56:09.1431334Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T19:56:09.1432070Z >>> return torch.tensor(res, device=x.device) 2025-08-26T19:56:09.1432720Z >>> 2025-08-26T19:56:09.1433297Z >>> @torch.library.register_fake("mylib::custom_nonzero") 2025-08-26T19:56:09.1434041Z >>> def _(x): 2025-08-26T19:56:09.1434705Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T19:56:09.1435507Z >>> # Since we cannot peek at the data in an fake impl, 2025-08-26T19:56:09.1436344Z >>> # we use the ctx object to construct a new symint that 2025-08-26T19:56:09.1437136Z >>> # represents the data-dependent size. 2025-08-26T19:56:09.1437984Z >>> ctx = torch.library.get_ctx() 2025-08-26T19:56:09.1438657Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T19:56:09.1439297Z >>> shape = [nnz, x.dim()] 2025-08-26T19:56:09.1440002Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T19:56:09.1440708Z >>> return result 2025-08-26T19:56:09.1441240Z >>> 2025-08-26T19:56:09.1441828Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T19:56:09.1442574Z >>> 2025-08-26T19:56:09.1443034Z >>> x = torch.tensor([0, 1, 2, 3, 4, 0]) 2025-08-26T19:56:09.1443970Z >>> trace = make_fx(torch.ops.mylib.custom_nonzero, tracing_mode="symbolic")(x) 2025-08-26T19:56:09.1444903Z >>> trace.print_readable() 2025-08-26T19:56:09.1445471Z >>> 2025-08-26T19:56:09.1446155Z >>> assert torch.allclose(trace(x), torch.ops.mylib.custom_nonzero(x)) 2025-08-26T19:56:09.1447007Z 2025-08-26T19:56:09.1447367Z 2025-08-26T19:56:09.1448681Z Original Error: IndentationError('expected an indented block after function definition on line 37', ('', 38, 1, '_._ = None\n', 38, 2)) 2025-08-26T19:56:09.1450250Z 2025-08-26T19:56:09.1450630Z _._ = None 2025-08-26T19:56:09.1451024Z ^ 2025-08-26T19:56:09.1451426Z warnings.warn(msg) 2025-08-26T19:56:09.1451915Z 2025-08-26T19:56:09.1452524Z --- Parse Warning: 10 / 146 --- 2025-08-26T19:56:09.1454794Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_autograd in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1083. 2025-08-26T19:56:09.1457373Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1458430Z Register a backward formula for this custom op. 2025-08-26T19:56:09.1459103Z 2025-08-26T19:56:09.1459716Z In order for an operator to work with autograd, you need to register 2025-08-26T19:56:09.1460630Z a backward formula: 2025-08-26T19:56:09.1461378Z 1. You must tell us how to compute gradients during the backward pass 2025-08-26T19:56:09.1462262Z by providing us a "backward" function. 2025-08-26T19:56:09.1463148Z 2. If you need any values from the forward to compute gradients, you can 2025-08-26T19:56:09.1464080Z use `setup_context` to save values for backward. 2025-08-26T19:56:09.1464751Z 2025-08-26T19:56:09.1465404Z ``backward`` runs during the backward pass. It accepts ``(ctx, *grads)``: 2025-08-26T19:56:09.1466482Z - ``grads`` is one or more gradients. The number of gradients matches 2025-08-26T19:56:09.1467331Z the number of outputs of the operator. 2025-08-26T19:56:09.1468215Z The ``ctx`` object is `the same ctx object `_ used by 2025-08-26T19:56:09.1469376Z :class:`torch.autograd.Function`. The semantics of ``backward_fn`` are the 2025-08-26T19:56:09.1470406Z same as :meth:`torch.autograd.Function.backward`. 2025-08-26T19:56:09.1471159Z 2025-08-26T19:56:09.1471779Z ``setup_context(ctx, inputs, output)`` runs during the forward pass. 2025-08-26T19:56:09.1472908Z Please save quantities needed for backward onto the ``ctx`` object via 2025-08-26T19:56:09.1474074Z either :meth:`torch.autograd.function.FunctionCtx.save_for_backward` 2025-08-26T19:56:09.1475179Z or assigning them as attributes of ``ctx``. If your custom op has 2025-08-26T19:56:09.1476222Z kwarg-only arguments, we expect the signature of ``setup_context`` 2025-08-26T19:56:09.1477361Z to be ``setup_context(ctx, inputs, keyword_only_inputs, output)``. 2025-08-26T19:56:09.1478145Z 2025-08-26T19:56:09.1478789Z Both ``setup_context_fn`` and ``backward_fn`` must be traceable. That is, 2025-08-26T19:56:09.1479900Z they may not directly access :meth:`torch.Tensor.data_ptr` and they must 2025-08-26T19:56:09.1481050Z not depend on or mutate global state. If you need a non-traceable backward, 2025-08-26T19:56:09.1482214Z you can make it a separate custom_op that you call inside ``backward_fn``. 2025-08-26T19:56:09.1483069Z 2025-08-26T19:56:09.1483715Z If you need different autograd behavior on different devices, then we 2025-08-26T19:56:09.1484843Z recommend creating two different custom operators, one for each device 2025-08-26T19:56:09.1485994Z that needs different behavior, and switching between them at runtime. 2025-08-26T19:56:09.1486848Z 2025-08-26T19:56:09.1487224Z Examples: 2025-08-26T19:56:09.1487661Z >>> import torch 2025-08-26T19:56:09.1488192Z >>> import numpy as np 2025-08-26T19:56:09.1488851Z >>> from torch import Tensor 2025-08-26T19:56:09.1489439Z >>> 2025-08-26T19:56:09.1490076Z >>> @torch.library.custom_op("mylib::numpy_sin", mutates_args=()) 2025-08-26T19:56:09.1490945Z >>> def numpy_sin(x: Tensor) -> Tensor: 2025-08-26T19:56:09.1491608Z >>> x_np = x.cpu().numpy() 2025-08-26T19:56:09.1492220Z >>> y_np = np.sin(x_np) 2025-08-26T19:56:09.1492909Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T19:56:09.1493608Z >>> 2025-08-26T19:56:09.1494157Z >>> def setup_context(ctx, inputs, output) -> Tensor: 2025-08-26T19:56:09.1494861Z >>> x, = inputs 2025-08-26T19:56:09.1495392Z >>> ctx.save_for_backward(x) 2025-08-26T19:56:09.1495983Z >>> 2025-08-26T19:56:09.1496446Z >>> def backward(ctx, grad): 2025-08-26T19:56:09.1497069Z >>> x, = ctx.saved_tensors 2025-08-26T19:56:09.1497664Z >>> return grad * x.cos() 2025-08-26T19:56:09.1498237Z >>> 2025-08-26T19:56:09.1498716Z >>> torch.library.register_autograd( 2025-08-26T19:56:09.1499522Z ... "mylib::numpy_sin", backward, setup_context=setup_context 2025-08-26T19:56:09.1500420Z ... ) 2025-08-26T19:56:09.1500831Z >>> 2025-08-26T19:56:09.1501326Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T19:56:09.1501984Z >>> y = numpy_sin(x) 2025-08-26T19:56:09.1502672Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T19:56:09.1503472Z >>> assert torch.allclose(grad_x, x.cos()) 2025-08-26T19:56:09.1504113Z >>> 2025-08-26T19:56:09.1504590Z >>> # Example with a keyword-only arg 2025-08-26T19:56:09.1505438Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T19:56:09.1506343Z >>> def numpy_mul(x: Tensor, *, val: float) -> Tensor: 2025-08-26T19:56:09.1507069Z >>> x_np = x.cpu().numpy() 2025-08-26T19:56:09.1507660Z >>> y_np = x_np * val 2025-08-26T19:56:09.1508329Z >>> return torch.from_numpy(y_np).to(device=x.device) 2025-08-26T19:56:09.1509017Z >>> 2025-08-26T19:56:09.1509705Z >>> def setup_context(ctx, inputs, keyword_only_inputs, output) -> Tensor: 2025-08-26T19:56:09.1510667Z >>> ctx.val = keyword_only_inputs["val"] 2025-08-26T19:56:09.1511294Z >>> 2025-08-26T19:56:09.1511720Z >>> def backward(ctx, grad): 2025-08-26T19:56:09.1512327Z >>> return grad * ctx.val 2025-08-26T19:56:09.1512890Z >>> 2025-08-26T19:56:09.1513361Z >>> torch.library.register_autograd( 2025-08-26T19:56:09.1514144Z ... "mylib::numpy_mul", backward, setup_context=setup_context 2025-08-26T19:56:09.1514959Z ... ) 2025-08-26T19:56:09.1515373Z >>> 2025-08-26T19:56:09.1515837Z >>> x = torch.randn(3, requires_grad=True) 2025-08-26T19:56:09.1516485Z >>> y = numpy_mul(x, val=3.14) 2025-08-26T19:56:09.1517217Z >>> (grad_x,) = torch.autograd.grad(y, x, torch.ones_like(y)) 2025-08-26T19:56:09.1518115Z >>> assert torch.allclose(grad_x, torch.full_like(x, 3.14)) 2025-08-26T19:56:09.1518856Z 2025-08-26T19:56:09.1519210Z 2025-08-26T19:56:09.1519917Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1520809Z 2025-08-26T19:56:09.1521194Z warnings.warn(msg) 2025-08-26T19:56:09.1521655Z 2025-08-26T19:56:09.1522227Z --- Parse Warning: 11 / 146 --- 2025-08-26T19:56:09.1524405Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_kernel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1482. 2025-08-26T19:56:09.1526850Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.1527998Z Returns the computed kernel for a given operator and dispatch key. 2025-08-26T19:56:09.1528870Z 2025-08-26T19:56:09.1529508Z This function retrieves the kernel that would be executed for a given 2025-08-26T19:56:09.1530662Z operator and dispatch key combination. The returned SafeKernelFunction 2025-08-26T19:56:09.1531742Z can be used to call the kernel in a boxed fashion. The intended use 2025-08-26T19:56:09.1532778Z case for this function is to retrieve the original kernel for a given 2025-08-26T19:56:09.1533865Z dispatch key and then register another kernel to the same dispatch key 2025-08-26T19:56:09.1534866Z that calls into the original kernel for certain cases. 2025-08-26T19:56:09.1535571Z 2025-08-26T19:56:09.1535936Z Args: 2025-08-26T19:56:09.1536555Z op: Operator name (along with the overload) or OpOverload object 2025-08-26T19:56:09.1537772Z Can be a string (e.g., "aten::add.Tensor"), an OpOverload, or a CustomOpDef. 2025-08-26T19:56:09.1538969Z dispatch_key (str | torch.DispatchKey): The dispatch key to get the kernel for. 2025-08-26T19:56:09.1540090Z Can be a string (e.g., "CPU", "CUDA") or a DispatchKey enum value. 2025-08-26T19:56:09.1540969Z 2025-08-26T19:56:09.1541336Z Returns: 2025-08-26T19:56:09.1542050Z torch._C._SafeKernelFunction: A safe kernel function that can be used to 2025-08-26T19:56:09.1542957Z call the kernel. 2025-08-26T19:56:09.1543474Z 2025-08-26T19:56:09.1543842Z Raises: 2025-08-26T19:56:09.1544364Z RuntimeError: If the operator does not exist. 2025-08-26T19:56:09.1545053Z 2025-08-26T19:56:09.1545462Z Example: 2025-08-26T19:56:09.1545936Z >>> # Get the CPU kernel for torch.add 2025-08-26T19:56:09.1546757Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", "CPU") 2025-08-26T19:56:09.1547519Z >>> 2025-08-26T19:56:09.1547974Z >>> # You can also use DispatchKey enum 2025-08-26T19:56:09.1548926Z >>> kernel = torch.library.get_kernel("aten::add.Tensor", torch.DispatchKey.CPU) 2025-08-26T19:56:09.1549826Z >>> 2025-08-26T19:56:09.1550285Z >>> # Or use an OpOverload directly 2025-08-26T19:56:09.1551213Z >>> kernel = torch.library.get_kernel(torch.ops.aten.add.Tensor, "CPU") 2025-08-26T19:56:09.1552050Z >>> 2025-08-26T19:56:09.1552700Z >>> # Example: Using get_kernel in a custom op with conditional dispatch 2025-08-26T19:56:09.1553604Z >>> # Get the original kernel for torch.sin 2025-08-26T19:56:09.1554472Z >>> original_sin_kernel = torch.library.get_kernel("aten::sin", "CPU") 2025-08-26T19:56:09.1555293Z >>> 2025-08-26T19:56:09.1556069Z >>> # If input has negative values, use original sin, otherwise return zeros 2025-08-26T19:56:09.1557018Z >>> def conditional_sin_impl(dispatch_keys, x): 2025-08-26T19:56:09.1557697Z >>> if (x < 0).any(): 2025-08-26T19:56:09.1558432Z >>> return original_sin_kernel.call_boxed(dispatch_keys, x) 2025-08-26T19:56:09.1559203Z >>> else: 2025-08-26T19:56:09.1559708Z >>> return torch.zeros_like(x) 2025-08-26T19:56:09.1560306Z >>> 2025-08-26T19:56:09.1560801Z >>> lib = torch.library.Library("aten", "IMPL") 2025-08-26T19:56:09.1561801Z >>> # with_keyset=True so the first argument to the impl is the current DispatchKeySet 2025-08-26T19:56:09.1562924Z >>> which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T19:56:09.1563892Z >>> lib.impl("sin", conditional_sin_impl, "CPU", with_keyset=True) 2025-08-26T19:56:09.1564671Z >>> 2025-08-26T19:56:09.1565126Z >>> # Test the conditional behavior 2025-08-26T19:56:09.1565799Z >>> x_positive = torch.tensor([1.0, 2.0]) 2025-08-26T19:56:09.1566459Z >>> x_mixed = torch.tensor([-1.0, 2.0]) 2025-08-26T19:56:09.1567095Z >>> torch.sin(x_positive) 2025-08-26T19:56:09.1567673Z tensor([0., 0.]) 2025-08-26T19:56:09.1568197Z >>> torch.sin(x_mixed) 2025-08-26T19:56:09.1568747Z tensor([-0.8415, 0.9093]) 2025-08-26T19:56:09.1569352Z 2025-08-26T19:56:09.1570549Z Original Error: SyntaxError('invalid syntax', ('', 23, 7, 'which needs to be the first argument to ``kernel.call_boxed``\n', 23, 12)) 2025-08-26T19:56:09.1571924Z 2025-08-26T19:56:09.1572477Z which needs to be the first argument to ``kernel.call_boxed`` 2025-08-26T19:56:09.1573232Z ^ 2025-08-26T19:56:09.1573641Z warnings.warn(msg) 2025-08-26T19:56:09.1574112Z 2025-08-26T19:56:09.1574687Z --- Parse Warning: 12 / 146 --- 2025-08-26T19:56:09.1576859Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=opcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py line=1571. 2025-08-26T19:56:09.1579325Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1580523Z Given an operator and some sample arguments, tests if the operator is 2025-08-26T19:56:09.1581440Z registered correctly. 2025-08-26T19:56:09.1581943Z 2025-08-26T19:56:09.1582566Z That is, when you use the torch.library/TORCH_LIBRARY APIs to create a 2025-08-26T19:56:09.1583697Z custom op, you specified metadata (e.g. mutability info) about the custom op 2025-08-26T19:56:09.1584865Z and these APIs require that the functions you pass them satisfy certain 2025-08-26T19:56:09.1585984Z properties (e.g. no data pointer access in the fake/meta/abstract kernel) 2025-08-26T19:56:09.1586958Z ``opcheck`` tests these metadata and properties. 2025-08-26T19:56:09.1587614Z 2025-08-26T19:56:09.1588031Z Concretely, we test the following: 2025-08-26T19:56:09.1588605Z 2025-08-26T19:56:09.1589145Z - test_schema: If the schema matches the implementation of 2025-08-26T19:56:09.1590156Z the operator. For example: if the schema specifies a Tensor is mutated, 2025-08-26T19:56:09.1591247Z then we check the implementation mutates the Tensor. If the schema 2025-08-26T19:56:09.1592303Z specifies that we return a new Tensor, then we check that the 2025-08-26T19:56:09.1593344Z implementation returns a new Tensor (instead of an existing one or 2025-08-26T19:56:09.1594219Z a view of an existing one). 2025-08-26T19:56:09.1595011Z - test_autograd_registration: If the operator supports training 2025-08-26T19:56:09.1596025Z (autograd): we check that its autograd formula is registered via 2025-08-26T19:56:09.1597121Z torch.library.register_autograd or a manual registration to one 2025-08-26T19:56:09.1598179Z or more DispatchKey::Autograd keys. Any other DispatchKey-based 2025-08-26T19:56:09.1599081Z registrations may lead to undefined behavior. 2025-08-26T19:56:09.1599931Z - test_faketensor: If the operator has a FakeTensor kernel 2025-08-26T19:56:09.1600843Z (and if it is correct). The FakeTensor kernel is necessary ( 2025-08-26T19:56:09.1601850Z but not sufficient) for the operator to work with PyTorch compilation 2025-08-26T19:56:09.1602935Z APIs (torch.compile/export/FX). We check that a FakeTensor kernel 2025-08-26T19:56:09.1603966Z (also sometimes known as a meta kernel) was registered for the 2025-08-26T19:56:09.1604962Z operator and that it is correct. This test takes the result of 2025-08-26T19:56:09.1605950Z running the operator on real tensors and the result of running 2025-08-26T19:56:09.1606964Z the operator on FakeTensors and checks that they have the same 2025-08-26T19:56:09.1607883Z Tensor metadata (sizes/strides/dtype/device/etc). 2025-08-26T19:56:09.1608867Z - test_aot_dispatch_dynamic: If the operator has correct behavior 2025-08-26T19:56:09.1609851Z with PyTorch compilation APIs (torch.compile/export/FX). 2025-08-26T19:56:09.1610855Z This checks that the outputs (and gradients, if applicable) are the 2025-08-26T19:56:09.1611808Z same under eager-mode PyTorch and torch.compile. 2025-08-26T19:56:09.1612703Z This test is a superset of ``test_faketensor`` and is an e2e test; 2025-08-26T19:56:09.1613640Z other things it tests are that the operator supports 2025-08-26T19:56:09.1614607Z functionalization and that the backward pass (if it exists) also 2025-08-26T19:56:09.1615539Z supports FakeTensor and functionalization. 2025-08-26T19:56:09.1616179Z 2025-08-26T19:56:09.1616774Z For best results, please call ``opcheck`` multiple times with a 2025-08-26T19:56:09.1617736Z representative set of inputs. If your operator supports 2025-08-26T19:56:09.1618787Z autograd, please use ``opcheck`` with inputs with ``requires_grad = True``; 2025-08-26T19:56:09.1619938Z if your operator supports multiple devices (e.g. CPU and CUDA), please 2025-08-26T19:56:09.1620922Z use ``opcheck`` with inputs on all supported devices. 2025-08-26T19:56:09.1621654Z 2025-08-26T19:56:09.1622012Z Args: 2025-08-26T19:56:09.1622588Z op: The operator. Must either be a function decorated with 2025-08-26T19:56:09.1623575Z :func:`torch.library.custom_op` or an OpOverload/OpOverloadPacket 2025-08-26T19:56:09.1624640Z found in torch.ops.* (e.g. torch.ops.aten.sin, torch.ops.mylib.foo) 2025-08-26T19:56:09.1625505Z args: The args to the operator 2025-08-26T19:56:09.1626146Z kwargs: The kwargs to the operator 2025-08-26T19:56:09.1626950Z test_utils: Tests that we should run. Default: all of them. 2025-08-26T19:56:09.1627799Z Example: ("test_schema", "test_faketensor") 2025-08-26T19:56:09.1628668Z raise_exception: If we should raise an exception on the first 2025-08-26T19:56:09.1629614Z error. If False, we will return a dict with information 2025-08-26T19:56:09.1630400Z on if each test passed or not. 2025-08-26T19:56:09.1631357Z rtol (Optional[float]): Relative tolerance for floating point comparisons. 2025-08-26T19:56:09.1632332Z If specified ``atol`` must also be specified. 2025-08-26T19:56:09.1633208Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T19:56:09.1634144Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T19:56:09.1635176Z atol (Optional[float]): Absolute tolerance for floating point comparisons. 2025-08-26T19:56:09.1636296Z If specified ``rtol`` must also be specified. 2025-08-26T19:56:09.1637154Z If omitted, default values based on the ``dtype`` are selected 2025-08-26T19:56:09.1638240Z (see the table in :func:`torch.testing.assert_close`). 2025-08-26T19:56:09.1638961Z 2025-08-26T19:56:09.1639355Z .. warning:: 2025-08-26T19:56:09.1639783Z 2025-08-26T19:56:09.1640423Z opcheck and :func:`torch.autograd.gradcheck` test different things; 2025-08-26T19:56:09.1641523Z opcheck tests if your usage of torch.library APIs is correct while 2025-08-26T19:56:09.1642596Z :func:`torch.autograd.gradcheck` tests if your autograd formula is 2025-08-26T19:56:09.1643718Z mathematically correct. Use both to test custom ops that support 2025-08-26T19:56:09.1644602Z gradient computation. 2025-08-26T19:56:09.1645153Z 2025-08-26T19:56:09.1645532Z Example: 2025-08-26T19:56:09.1645941Z 2025-08-26T19:56:09.1646417Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:09.1647320Z >>> @torch.library.custom_op("mylib::numpy_mul", mutates_args=()) 2025-08-26T19:56:09.1648239Z >>> def numpy_mul(x: Tensor, y: float) -> Tensor: 2025-08-26T19:56:09.1649043Z >>> x_np = x.numpy(force=True) 2025-08-26T19:56:09.1649663Z >>> z_np = x_np * y 2025-08-26T19:56:09.1650312Z >>> return torch.from_numpy(z_np).to(x.device) 2025-08-26T19:56:09.1650978Z >>> 2025-08-26T19:56:09.1651441Z >>> @numpy_mul.register_fake 2025-08-26T19:56:09.1652036Z >>> def _(x, y): 2025-08-26T19:56:09.1652588Z >>> return torch.empty_like(x) 2025-08-26T19:56:09.1653194Z >>> 2025-08-26T19:56:09.1653689Z >>> def setup_context(ctx, inputs, output): 2025-08-26T19:56:09.1654326Z >>> y, = inputs 2025-08-26T19:56:09.1654840Z >>> ctx.y = y 2025-08-26T19:56:09.1655351Z >>> 2025-08-26T19:56:09.1655809Z >>> def backward(ctx, grad): 2025-08-26T19:56:09.1656426Z >>> return grad * ctx.y, None 2025-08-26T19:56:09.1657021Z >>> 2025-08-26T19:56:09.1657706Z >>> numpy_mul.register_autograd(backward, setup_context=setup_context) 2025-08-26T19:56:09.1658560Z >>> 2025-08-26T19:56:09.1658983Z >>> sample_inputs = [ 2025-08-26T19:56:09.1659662Z >>> (torch.randn(3), 3.14), 2025-08-26T19:56:09.1660328Z >>> (torch.randn(2, 3, device='cuda'), 2.718), 2025-08-26T19:56:09.1661091Z >>> (torch.randn(1, 10, requires_grad=True), 1.234), 2025-08-26T19:56:09.1661966Z >>> (torch.randn(64, 64, device='cuda', requires_grad=True), 90.18), 2025-08-26T19:56:09.1662747Z >>> ] 2025-08-26T19:56:09.1663175Z >>> 2025-08-26T19:56:09.1663625Z >>> for args in sample_inputs: 2025-08-26T19:56:09.1664293Z >>> torch.library.opcheck(numpy_mul, args) 2025-08-26T19:56:09.1664947Z 2025-08-26T19:56:09.1665310Z 2025-08-26T19:56:09.1666031Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1666930Z 2025-08-26T19:56:09.1667320Z warnings.warn(msg) 2025-08-26T19:56:09.1667805Z 2025-08-26T19:56:09.1668395Z --- Parse Warning: 13 / 146 --- 2025-08-26T19:56:09.1670591Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/serialization.py line=1285. 2025-08-26T19:56:09.1673153Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1674588Z load(f, map_location=None, pickle_module=pickle, *, weights_only=True, mmap=None, **pickle_load_args) 2025-08-26T19:56:09.1675657Z 2025-08-26T19:56:09.1676214Z Loads an object saved with :func:`torch.save` from a file. 2025-08-26T19:56:09.1676942Z 2025-08-26T19:56:09.1677704Z :func:`torch.load` uses Python's unpickling facilities but treats storages, 2025-08-26T19:56:09.1678877Z which underlie tensors, specially. They are first deserialized on the 2025-08-26T19:56:09.1680001Z CPU and are then moved to the device they were saved from. If this fails 2025-08-26T19:56:09.1681117Z (e.g. because the run time system doesn't have certain devices), an exception 2025-08-26T19:56:09.1682302Z is raised. However, storages can be dynamically remapped to an alternative 2025-08-26T19:56:09.1683345Z set of devices using the :attr:`map_location` argument. 2025-08-26T19:56:09.1684060Z 2025-08-26T19:56:09.1684744Z If :attr:`map_location` is a callable, it will be called once for each serialized 2025-08-26T19:56:09.1685902Z storage with two arguments: storage and location. The storage argument 2025-08-26T19:56:09.1687051Z will be the initial deserialization of the storage, residing on the CPU. 2025-08-26T19:56:09.1688185Z Each serialized storage has a location tag associated with it which 2025-08-26T19:56:09.1689357Z identifies the device it was saved from, and this tag is the second 2025-08-26T19:56:09.1690522Z argument passed to :attr:`map_location`. The builtin location tags are ``'cpu'`` 2025-08-26T19:56:09.1691726Z for CPU tensors and ``'cuda:device_id'`` (e.g. ``'cuda:2'``) for CUDA tensors. 2025-08-26T19:56:09.1692822Z :attr:`map_location` should return either ``None`` or a storage. If 2025-08-26T19:56:09.1693971Z :attr:`map_location` returns a storage, it will be used as the final deserialized 2025-08-26T19:56:09.1695224Z object, already moved to the right device. Otherwise, :func:`torch.load` will 2025-08-26T19:56:09.1696438Z fall back to the default behavior, as if :attr:`map_location` wasn't specified. 2025-08-26T19:56:09.1697335Z 2025-08-26T19:56:09.1698009Z If :attr:`map_location` is a :class:`torch.device` object or a string containing 2025-08-26T19:56:09.1699179Z a device tag, it indicates the location where all tensors should be loaded. 2025-08-26T19:56:09.1700037Z 2025-08-26T19:56:09.1700763Z Otherwise, if :attr:`map_location` is a dict, it will be used to remap location tags 2025-08-26T19:56:09.1701933Z appearing in the file (keys), to ones that specify where to put the 2025-08-26T19:56:09.1702812Z storages (values). 2025-08-26T19:56:09.1703303Z 2025-08-26T19:56:09.1703937Z User extensions can register their own location tags and tagging and 2025-08-26T19:56:09.1705149Z deserialization methods using :func:`torch.serialization.register_package`. 2025-08-26T19:56:09.1706092Z 2025-08-26T19:56:09.1706784Z See :ref:`layout-control` for more advanced tools to manipulate a checkpoint. 2025-08-26T19:56:09.1707669Z 2025-08-26T19:56:09.1708031Z Args: 2025-08-26T19:56:09.1708902Z f: a file-like object (has to implement :meth:`read`, :meth:`readline`, :meth:`tell`, and :meth:`seek`), 2025-08-26T19:56:09.1710113Z or a string or os.PathLike object containing a file name 2025-08-26T19:56:09.1711315Z map_location: a function, :class:`torch.device`, string or a dict specifying how to remap storage 2025-08-26T19:56:09.1712384Z locations 2025-08-26T19:56:09.1713151Z pickle_module: module used for unpickling metadata and objects (has to 2025-08-26T19:56:09.1714220Z match the :attr:`pickle_module` used to serialize file) 2025-08-26T19:56:09.1715203Z weights_only: Indicates whether unpickler should be restricted to 2025-08-26T19:56:09.1716172Z loading only tensors, primitive types, dictionaries 2025-08-26T19:56:09.1717148Z and any types added via :func:`torch.serialization.add_safe_globals`. 2025-08-26T19:56:09.1718068Z See :ref:`weights-only` for more details. 2025-08-26T19:56:09.1719300Z mmap: Indicates whether the file should be mapped rather than loading all the storages into memory. 2025-08-26T19:56:09.1720900Z Typically, tensor storages in the file will first be moved from disk to CPU memory, after which they 2025-08-26T19:56:09.1727445Z are moved to the location that they were tagged with when saving, or specified by ``map_location``. This 2025-08-26T19:56:09.1729160Z second step is a no-op if the final location is CPU. When the ``mmap`` flag is set, instead of copying the 2025-08-26T19:56:09.1730755Z tensor storages from disk to CPU memory in the first step, ``f`` is mapped, which means tensor storages 2025-08-26T19:56:09.1731969Z will be lazily loaded when their data is accessed. 2025-08-26T19:56:09.1732969Z pickle_load_args: (Python 3 only) optional keyword arguments passed over to 2025-08-26T19:56:09.1734140Z :func:`pickle_module.load` and :func:`pickle_module.Unpickler`, e.g., 2025-08-26T19:56:09.1735034Z :attr:`errors=...`. 2025-08-26T19:56:09.1735582Z 2025-08-26T19:56:09.1735959Z .. warning:: 2025-08-26T19:56:09.1736657Z :func:`torch.load()` unless `weights_only` parameter is set to `True`, 2025-08-26T19:56:09.1737858Z uses ``pickle`` module implicitly, which is known to be insecure. 2025-08-26T19:56:09.1739095Z It is possible to construct malicious pickle data which will execute arbitrary code 2025-08-26T19:56:09.1740367Z during unpickling. Never load data that could have come from an untrusted 2025-08-26T19:56:09.1741692Z source in an unsafe mode, or that could have been tampered with. **Only load data you trust**. 2025-08-26T19:56:09.1742698Z 2025-08-26T19:56:09.1743079Z .. note:: 2025-08-26T19:56:09.1743845Z When you call :func:`torch.load()` on a file which contains GPU tensors, those tensors 2025-08-26T19:56:09.1745128Z will be loaded to GPU by default. You can call ``torch.load(.., map_location='cpu')`` 2025-08-26T19:56:09.1746433Z and then :meth:`load_state_dict` to avoid GPU RAM surge when loading a model checkpoint. 2025-08-26T19:56:09.1747399Z 2025-08-26T19:56:09.1747786Z .. note:: 2025-08-26T19:56:09.1748529Z By default, we decode byte strings as ``utf-8``. This is to avoid a common error 2025-08-26T19:56:09.1749803Z case ``UnicodeDecodeError: 'ascii' codec can't decode byte 0x...`` 2025-08-26T19:56:09.1750895Z when loading files saved by Python 2 in Python 3. If this default 2025-08-26T19:56:09.1752072Z is incorrect, you may use an extra :attr:`encoding` keyword argument to specify how 2025-08-26T19:56:09.1753298Z these objects should be loaded, e.g., :attr:`encoding='latin1'` decodes them 2025-08-26T19:56:09.1754509Z to strings using ``latin1`` encoding, and :attr:`encoding='bytes'` keeps them 2025-08-26T19:56:09.1755695Z as byte arrays which can be decoded later with ``byte_array.decode(...)``. 2025-08-26T19:56:09.1756566Z 2025-08-26T19:56:09.1756957Z Example: 2025-08-26T19:56:09.1757457Z >>> # xdoctest: +SKIP("undefined filepaths") 2025-08-26T19:56:09.1758210Z >>> torch.load("tensors.pt", weights_only=True) 2025-08-26T19:56:09.1758925Z # Load all tensors onto the CPU 2025-08-26T19:56:09.1759539Z >>> torch.load( 2025-08-26T19:56:09.1760102Z ... "tensors.pt", 2025-08-26T19:56:09.1760715Z ... map_location=torch.device("cpu"), 2025-08-26T19:56:09.1761383Z ... weights_only=True, 2025-08-26T19:56:09.1761951Z ... ) 2025-08-26T19:56:09.1762467Z # Load all tensors onto the CPU, using a function 2025-08-26T19:56:09.1763159Z >>> torch.load( 2025-08-26T19:56:09.1763676Z ... "tensors.pt", 2025-08-26T19:56:09.1764318Z ... map_location=lambda storage, loc: storage, 2025-08-26T19:56:09.1765053Z ... weights_only=True, 2025-08-26T19:56:09.1765622Z ... ) 2025-08-26T19:56:09.1766094Z # Load all tensors onto GPU 1 2025-08-26T19:56:09.1766707Z >>> torch.load( 2025-08-26T19:56:09.1767205Z ... "tensors.pt", 2025-08-26T19:56:09.1767883Z ... map_location=lambda storage, loc: storage.cuda(1), 2025-08-26T19:56:09.1768730Z ... weights_only=True, 2025-08-26T19:56:09.1769436Z ... ) # type: ignore[attr-defined] 2025-08-26T19:56:09.1770088Z # Map tensors from GPU 1 to GPU 0 2025-08-26T19:56:09.1770713Z >>> torch.load( 2025-08-26T19:56:09.1771228Z ... "tensors.pt", 2025-08-26T19:56:09.1771833Z ... map_location={"cuda:1": "cuda:0"}, 2025-08-26T19:56:09.1772481Z ... weights_only=True, 2025-08-26T19:56:09.1773044Z ... ) 2025-08-26T19:56:09.1773534Z # Load tensor from io.BytesIO object 2025-08-26T19:56:09.1774499Z # Loading from a buffer setting weights_only=False, warning this can be unsafe 2025-08-26T19:56:09.1775462Z >>> with open("tensor.pt", "rb") as f: 2025-08-26T19:56:09.1776146Z ... buffer = io.BytesIO(f.read()) 2025-08-26T19:56:09.1776838Z >>> torch.load(buffer, weights_only=False) 2025-08-26T19:56:09.1777606Z # Load a module with 'ascii' encoding for unpickling 2025-08-26T19:56:09.1778642Z # Loading from a module setting weights_only=False, warning this can be unsafe 2025-08-26T19:56:09.1779760Z >>> torch.load("module.pt", encoding="ascii", weights_only=False) 2025-08-26T19:56:09.1780547Z 2025-08-26T19:56:09.1781270Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1782196Z 2025-08-26T19:56:09.1782587Z warnings.warn(msg) 2025-08-26T19:56:09.1783068Z 2025-08-26T19:56:09.1783682Z --- Parse Warning: 14 / 146 --- 2025-08-26T19:56:09.1786231Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compute_required_storage_length in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_prims_common/__init__.py line=1877. 2025-08-26T19:56:09.1789070Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1790334Z Computes the minimum storage size to hold the given tensor geometry. 2025-08-26T19:56:09.1791177Z 2025-08-26T19:56:09.1791555Z Example 2025-08-26T19:56:09.1791959Z ======= 2025-08-26T19:56:09.1792373Z 2025-08-26T19:56:09.1793041Z This is the size of a newly allocated tensor's storage, in units of elements 2025-08-26T19:56:09.1793908Z 2025-08-26T19:56:09.1794299Z >>> t = torch.empty((10, 20)) 2025-08-26T19:56:09.1795183Z >>> compute_required_storage_length(t.shape, t.stride(), t.storage_offset()) 2025-08-26T19:56:09.1796079Z 200 2025-08-26T19:56:09.1796468Z 2025-08-26T19:56:09.1796863Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:56:09.1797520Z >>> t2 = torch.empty_strided((1, 2, 3), (5, 7, 11)) 2025-08-26T19:56:09.1798245Z >>> size = compute_required_storage_length( 2025-08-26T19:56:09.1798971Z ... t2.shape, t2.stride(), t2.storage_offset() 2025-08-26T19:56:09.1799626Z ... ) 2025-08-26T19:56:09.1800058Z >>> size == t.storage().size() 2025-08-26T19:56:09.1800696Z True 2025-08-26T19:56:09.1801101Z 2025-08-26T19:56:09.1801681Z A valid tensor may have a larger storage size, but never smaller 2025-08-26T19:56:09.1802477Z 2025-08-26T19:56:09.1802901Z >>> slice = torch.empty(100)[20:40] 2025-08-26T19:56:09.1803525Z >>> slice.storage().size() 2025-08-26T19:56:09.1804065Z 100 2025-08-26T19:56:09.1804450Z 2025-08-26T19:56:09.1804874Z >>> compute_required_storage_length( 2025-08-26T19:56:09.1805671Z ... slice.shape, slice.stride(), slice.storage_offset() 2025-08-26T19:56:09.1806376Z ... ) 2025-08-26T19:56:09.1806784Z 40 2025-08-26T19:56:09.1807184Z 2025-08-26T19:56:09.1807558Z 2025-08-26T19:56:09.1808275Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1809284Z 2025-08-26T19:56:09.1809685Z warnings.warn(msg) 2025-08-26T19:56:09.1810244Z 2025-08-26T19:56:09.1810824Z --- Parse Warning: 15 / 146 --- 2025-08-26T19:56:09.1813153Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=is_available in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=66. 2025-08-26T19:56:09.1815740Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.1816997Z Check if the current accelerator is available at runtime: it was build, all the 2025-08-26T19:56:09.1818194Z required drivers are available and at least one device is visible. 2025-08-26T19:56:09.1819132Z See :ref:`accelerator` for details. 2025-08-26T19:56:09.1819809Z 2025-08-26T19:56:09.1820193Z Returns: 2025-08-26T19:56:09.1821011Z bool: A boolean indicating if there is an available :ref:`accelerator`. 2025-08-26T19:56:09.1821964Z 2025-08-26T19:56:09.1822661Z .. note:: This API delegates to the device-specific version of `is_available`. 2025-08-26T19:56:09.1823913Z On CUDA, when the environment variable ``PYTORCH_NVML_BASED_CUDA_CHECK=1`` is set, 2025-08-26T19:56:09.1825184Z this function will NOT poison fork. Otherwise, it will. For more details, see 2025-08-26T19:56:09.1826207Z :ref:`multiprocessing-poison-fork-note`. 2025-08-26T19:56:09.1826861Z 2025-08-26T19:56:09.1827254Z Example:: 2025-08-26T19:56:09.1827687Z 2025-08-26T19:56:09.1828426Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:56:09.1829356Z 2025-08-26T19:56:09.1830720Z Original Error: SyntaxError('invalid syntax', ('', 1, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 1, 78)) 2025-08-26T19:56:09.1832262Z 2025-08-26T19:56:09.1832994Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:56:09.1833984Z ^ 2025-08-26T19:56:09.1834578Z warnings.warn(msg) 2025-08-26T19:56:09.1835057Z 2025-08-26T19:56:09.1835623Z --- Parse Warning: 16 / 146 --- 2025-08-26T19:56:09.1838107Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=synchronize in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/accelerator/__init__.py line=212. 2025-08-26T19:56:09.1840712Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.1841870Z Wait for all kernels in all streams on the given device to complete. 2025-08-26T19:56:09.1842685Z 2025-08-26T19:56:09.1843061Z Args: 2025-08-26T19:56:09.1843928Z device (:class:`torch.device`, str, int, optional): device for which to synchronize. It must match 2025-08-26T19:56:09.1845274Z the current :ref:`accelerator` device type. If not given, 2025-08-26T19:56:09.1846438Z use :func:`torch.accelerator.current_device_index` by default. 2025-08-26T19:56:09.1847231Z 2025-08-26T19:56:09.1848051Z .. note:: This function is a no-op if the current :ref:`accelerator` is not initialized. 2025-08-26T19:56:09.1849139Z 2025-08-26T19:56:09.1849531Z Example:: 2025-08-26T19:56:09.1849955Z 2025-08-26T19:56:09.1850419Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:09.1851512Z >>> assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:56:09.1852582Z >>> start_event = torch.Event(enable_timing=True) 2025-08-26T19:56:09.1853352Z >>> end_event = torch.Event(enable_timing=True) 2025-08-26T19:56:09.1854049Z >>> start_event.record() 2025-08-26T19:56:09.1854908Z >>> tensor = torch.randn(100, device=torch.accelerator.current_accelerator()) 2025-08-26T19:56:09.1855904Z >>> sum = torch.sum(tensor) 2025-08-26T19:56:09.1856519Z >>> end_event.record() 2025-08-26T19:56:09.1857149Z >>> torch.accelerator.synchronize() 2025-08-26T19:56:09.1857930Z >>> elapsed_time_ms = start_event.elapsed_time(end_event) 2025-08-26T19:56:09.1858667Z 2025-08-26T19:56:09.1860034Z Original Error: SyntaxError('invalid syntax', ('', 2, 41, 'assert torch.accelerator.is_available() "No available accelerators detected."\n', 2, 78)) 2025-08-26T19:56:09.1861590Z 2025-08-26T19:56:09.1862311Z assert torch.accelerator.is_available() "No available accelerators detected." 2025-08-26T19:56:09.1863281Z ^ 2025-08-26T19:56:09.1863884Z warnings.warn(msg) 2025-08-26T19:56:09.1864368Z 2025-08-26T19:56:09.1864943Z --- Parse Warning: 17 / 146 --- 2025-08-26T19:56:09.1867146Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=cudart in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/cuda/__init__.py line=434. 2025-08-26T19:56:09.1869613Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.1870583Z Retrieves the CUDA runtime API module. 2025-08-26T19:56:09.1871183Z 2025-08-26T19:56:09.1871546Z 2025-08-26T19:56:09.1872252Z This function initializes the CUDA runtime environment if it is not already 2025-08-26T19:56:09.1873463Z initialized and returns the CUDA runtime API module (_cudart). The CUDA 2025-08-26T19:56:09.1874621Z runtime API module provides access to various CUDA runtime functions. 2025-08-26T19:56:09.1875462Z 2025-08-26T19:56:09.1875835Z Args: 2025-08-26T19:56:09.1876242Z ``None`` 2025-08-26T19:56:09.1876682Z 2025-08-26T19:56:09.1877047Z Returns: 2025-08-26T19:56:09.1877583Z module: The CUDA runtime API module (_cudart). 2025-08-26T19:56:09.1878314Z 2025-08-26T19:56:09.1878685Z Raises: 2025-08-26T19:56:09.1879376Z RuntimeError: If CUDA cannot be re-initialized in a forked subprocess. 2025-08-26T19:56:09.1880812Z AssertionError: If PyTorch is not compiled with CUDA support or if libcudart functions are unavailable. 2025-08-26T19:56:09.1881949Z 2025-08-26T19:56:09.1882413Z Example of CUDA operations with profiling: 2025-08-26T19:56:09.1883077Z >>> import torch 2025-08-26T19:56:09.1883681Z >>> from torch.cuda import cudart, check_error 2025-08-26T19:56:09.1884353Z >>> import os 2025-08-26T19:56:09.1884832Z >>> 2025-08-26T19:56:09.1885292Z >>> os.environ["CUDA_PROFILE"] = "1" 2025-08-26T19:56:09.1885908Z >>> 2025-08-26T19:56:09.1886421Z >>> def perform_cuda_operations_with_streams(): 2025-08-26T19:56:09.1887143Z >>> stream = torch.cuda.Stream() 2025-08-26T19:56:09.1887813Z >>> with torch.cuda.stream(stream): 2025-08-26T19:56:09.1888561Z >>> x = torch.randn(100, 100, device='cuda') 2025-08-26T19:56:09.1889345Z >>> y = torch.randn(100, 100, device='cuda') 2025-08-26T19:56:09.1890023Z >>> z = torch.mul(x, y) 2025-08-26T19:56:09.1890626Z >>> return z 2025-08-26T19:56:09.1891115Z >>> 2025-08-26T19:56:09.1891581Z >>> torch.cuda.synchronize() 2025-08-26T19:56:09.1892265Z >>> print("====== Start nsys profiling ======") 2025-08-26T19:56:09.1893061Z >>> check_error(cudart().cudaProfilerStart()) 2025-08-26T19:56:09.1893817Z >>> with torch.autograd.profiler.emit_nvtx(): 2025-08-26T19:56:09.1894608Z >>> result = perform_cuda_operations_with_streams() 2025-08-26T19:56:09.1895389Z >>> print("CUDA operations completed.") 2025-08-26T19:56:09.1896179Z >>> check_error(torch.cuda.cudart().cudaProfilerStop()) 2025-08-26T19:56:09.1897013Z >>> print("====== End nsys profiling ======") 2025-08-26T19:56:09.1897660Z 2025-08-26T19:56:09.1898265Z To run this example and save the profiling information, execute: 2025-08-26T19:56:09.1899617Z >>> $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T19:56:09.1900727Z 2025-08-26T19:56:09.1901432Z This command profiles the CUDA operations in the provided script and saves 2025-08-26T19:56:09.1902555Z the profiling information to a file named `trace_name.prof`. 2025-08-26T19:56:09.1903640Z The `--profile-from-start off` option ensures that profiling starts only 2025-08-26T19:56:09.1904635Z after the `cudaProfilerStart` call in the script. 2025-08-26T19:56:09.1905578Z The `--csv` and `--print-summary` options format the profiling output as a 2025-08-26T19:56:09.1906523Z CSV file and print a summary, respectively. 2025-08-26T19:56:09.1907505Z The `-o` option specifies the output file name, and the `-f` option forces the 2025-08-26T19:56:09.1908540Z overwrite of the output file if it already exists. 2025-08-26T19:56:09.1909220Z 2025-08-26T19:56:09.1910766Z Original Error: SyntaxError('invalid syntax', ('', 1, 1, '$ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py\n', 1, 2)) 2025-08-26T19:56:09.1912484Z 2025-08-26T19:56:09.1913391Z $ nvprof --profile-from-start off --csv --print-summary -o trace_name.prof -f -- python cudart_test.py 2025-08-26T19:56:09.1914493Z ^ 2025-08-26T19:56:09.1914883Z warnings.warn(msg) 2025-08-26T19:56:09.1915363Z 2025-08-26T19:56:09.1915948Z --- Parse Warning: 18 / 146 --- 2025-08-26T19:56:09.1918219Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.then in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=101. 2025-08-26T19:56:09.1919730Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1920210Z 2025-08-26T19:56:09.1920569Z Append the given callback function to this ``Future``, which will be run 2025-08-26T19:56:09.1921144Z when the ``Future`` is completed. Multiple callbacks can be added to 2025-08-26T19:56:09.1921680Z the same ``Future``, but the order in which they will be executed cannot 2025-08-26T19:56:09.1922207Z be guaranteed (to enforce a certain order consider chaining: 2025-08-26T19:56:09.1922727Z ``fut.then(cb1).then(cb2)``). The callback must take one argument, which 2025-08-26T19:56:09.1923270Z is the reference to this ``Future``. The callback function can use the 2025-08-26T19:56:09.1923825Z :meth:`value` method to get the value. Note that if this ``Future`` is 2025-08-26T19:56:09.1924382Z already completed, the given callback will be run immediately inline. 2025-08-26T19:56:09.1924823Z 2025-08-26T19:56:09.1925143Z If the ``Future``'s value contains tensors that reside on GPUs, the 2025-08-26T19:56:09.1925726Z callback might be invoked while the async kernels that are populating 2025-08-26T19:56:09.1926297Z those tensors haven't yet finished executing on the device. However, the 2025-08-26T19:56:09.1926874Z callback will be invoked with some dedicated streams set as current 2025-08-26T19:56:09.1927424Z (fetched from a global pool) which will be synchronized with those 2025-08-26T19:56:09.1927995Z kernels. Hence any operation performed by the callback on these tensors 2025-08-26T19:56:09.1928598Z will be scheduled on the device after the kernels complete. In other 2025-08-26T19:56:09.1929203Z words, as long as the callback doesn't switch streams, it can safely 2025-08-26T19:56:09.1929775Z manipulate the result without any additional synchronization. This is 2025-08-26T19:56:09.1930346Z similar to the non-blocking behavior of :meth:`wait`. 2025-08-26T19:56:09.1930717Z 2025-08-26T19:56:09.1931042Z Similarly, if the callback returns a value that contains tensors that 2025-08-26T19:56:09.1931587Z reside on a GPU, it can do so even if the kernels that are producing 2025-08-26T19:56:09.1932133Z these tensors are still running on the device, as long as the callback 2025-08-26T19:56:09.1932693Z didn't change streams during its execution. If one wants to change 2025-08-26T19:56:09.1933231Z streams, one must be careful to re-synchronize them with the original 2025-08-26T19:56:09.1933797Z streams, that is, those that were current when the callback was invoked. 2025-08-26T19:56:09.1934223Z 2025-08-26T19:56:09.1934427Z Args: 2025-08-26T19:56:09.1934766Z callback(``Callable``): a ``Callable`` that takes this ``Future`` as 2025-08-26T19:56:09.1935201Z the only argument. 2025-08-26T19:56:09.1935518Z 2025-08-26T19:56:09.1935723Z Returns: 2025-08-26T19:56:09.1936028Z A new ``Future`` object that holds the return value of the 2025-08-26T19:56:09.1936492Z ``callback`` and will be marked as completed when the given 2025-08-26T19:56:09.1936901Z ``callback`` finishes. 2025-08-26T19:56:09.1937176Z 2025-08-26T19:56:09.1937641Z .. note:: Note that if the callback function throws, either 2025-08-26T19:56:09.1938144Z through the original future being completed with an exception and 2025-08-26T19:56:09.1938686Z calling ``fut.wait()``, or through other code in the callback, the 2025-08-26T19:56:09.1939223Z future returned by ``then`` will be marked appropriately with the 2025-08-26T19:56:09.1939763Z encountered error. However, if this callback later completes 2025-08-26T19:56:09.1940296Z additional futures, those futures are not marked as completed with 2025-08-26T19:56:09.1940852Z an error and the user is responsible for handling completion/waiting 2025-08-26T19:56:09.1941306Z on those futures independently. 2025-08-26T19:56:09.1941704Z 2025-08-26T19:56:09.1941909Z Example:: 2025-08-26T19:56:09.1942136Z 2025-08-26T19:56:09.1942407Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T19:56:09.1942786Z >>> def callback(fut): 2025-08-26T19:56:09.1943111Z ... print(f"RPC return value is {fut.wait()}.") 2025-08-26T19:56:09.1943495Z >>> fut = torch.futures.Future() 2025-08-26T19:56:09.1943898Z >>> # The inserted callback will print the return value when 2025-08-26T19:56:09.1944320Z >>> # receiving the response from "worker1" 2025-08-26T19:56:09.1944679Z >>> cb_fut = fut.then(callback) 2025-08-26T19:56:09.1944997Z >>> chain_cb_fut = cb_fut.then( 2025-08-26T19:56:09.1945373Z ... lambda x : print(f"Chained cb done. {x.wait()}") 2025-08-26T19:56:09.1945744Z ... ) 2025-08-26T19:56:09.1945985Z >>> fut.set_result(5) 2025-08-26T19:56:09.1946270Z RPC return value is 5. 2025-08-26T19:56:09.1946571Z Chained cb done. None 2025-08-26T19:56:09.1946891Z 2025-08-26T19:56:09.1947273Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1947731Z 2025-08-26T19:56:09.1947954Z warnings.warn(msg) 2025-08-26T19:56:09.1948219Z 2025-08-26T19:56:09.1948570Z --- Parse Warning: 19 / 146 --- 2025-08-26T19:56:09.1949736Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Future.set_result in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/futures/__init__.py line=211. 2025-08-26T19:56:09.1951093Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1951583Z 2025-08-26T19:56:09.1951919Z Set the result for this ``Future``, which will mark this ``Future`` as 2025-08-26T19:56:09.1952467Z completed and trigger all attached callbacks. Note that a ``Future`` 2025-08-26T19:56:09.1952973Z cannot be marked completed twice. 2025-08-26T19:56:09.1953284Z 2025-08-26T19:56:09.1953627Z If the result contains tensors that reside on GPUs, this method can be 2025-08-26T19:56:09.1954192Z called even if the asynchronous kernels that are populating those 2025-08-26T19:56:09.1954740Z tensors haven't yet completed running on the device, provided that the 2025-08-26T19:56:09.1955326Z streams on which those kernels were enqueued are set as the current ones 2025-08-26T19:56:09.1955901Z when this method is called. Put simply, it's safe to call this method 2025-08-26T19:56:09.1956471Z immediately after launching those kernels, without any additional 2025-08-26T19:56:09.1957032Z synchronization, as long as one doesn't change streams in between. This 2025-08-26T19:56:09.1957615Z method will record events on all the relevant current streams and will 2025-08-26T19:56:09.1958170Z use them to ensure proper scheduling for all the consumers of this 2025-08-26T19:56:09.1958592Z ``Future``. 2025-08-26T19:56:09.1958808Z 2025-08-26T19:56:09.1959013Z Args: 2025-08-26T19:56:09.1959309Z result (object): the result object of this ``Future``. 2025-08-26T19:56:09.1959680Z 2025-08-26T19:56:09.1959878Z Example:: 2025-08-26T19:56:09.1960100Z 2025-08-26T19:56:09.1960371Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_FUTURES) 2025-08-26T19:56:09.1960750Z >>> import threading 2025-08-26T19:56:09.1961019Z >>> import time 2025-08-26T19:56:09.1961304Z >>> def slow_set_future(fut, value): 2025-08-26T19:56:09.1961635Z ... time.sleep(0.5) 2025-08-26T19:56:09.1961938Z ... fut.set_result(value) 2025-08-26T19:56:09.1962255Z >>> fut = torch.futures.Future() 2025-08-26T19:56:09.1962584Z >>> t = threading.Thread( 2025-08-26T19:56:09.1962892Z ... target=slow_set_future, 2025-08-26T19:56:09.1963224Z ... args=(fut, torch.ones(2) * 3) 2025-08-26T19:56:09.1963528Z ... ) 2025-08-26T19:56:09.1963788Z >>> t.start() 2025-08-26T19:56:09.1964048Z >>> print(fut.wait()) 2025-08-26T19:56:09.1964337Z tensor([3., 3.]) 2025-08-26T19:56:09.1964586Z >>> t.join() 2025-08-26T19:56:09.1964828Z 2025-08-26T19:56:09.1965209Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1965676Z 2025-08-26T19:56:09.1965881Z warnings.warn(msg) 2025-08-26T19:56:09.1966141Z 2025-08-26T19:56:09.1966472Z --- Parse Warning: 20 / 146 --- 2025-08-26T19:56:09.1967626Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=compile_shader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/mps/__init__.py line=145. 2025-08-26T19:56:09.1968985Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1969617Z Compiles compute shader from source and allows one to invoke kernels 2025-08-26T19:56:09.1970131Z defined there from the comfort of Python runtime 2025-08-26T19:56:09.1970538Z Example:: 2025-08-26T19:56:09.1970770Z 2025-08-26T19:56:09.1971019Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_MPS) 2025-08-26T19:56:09.1971409Z >>> lib = torch.mps.compile_shader( 2025-08-26T19:56:09.1972043Z ... "kernel void full(device float* out, constant float& val, uint idx [[thread_position_in_grid]]) { out[idx] = val; }" 2025-08-26T19:56:09.1972647Z ... ) 2025-08-26T19:56:09.1972903Z >>> x = torch.zeros(16, device="mps") 2025-08-26T19:56:09.1973048Z >>> lib.full(x, 3.14) 2025-08-26T19:56:09.1973133Z 2025-08-26T19:56:09.1973405Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1973486Z 2025-08-26T19:56:09.1973585Z warnings.warn(msg) 2025-08-26T19:56:09.1973678Z 2025-08-26T19:56:09.1973915Z --- Parse Warning: 21 / 146 --- 2025-08-26T19:56:09.1974774Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=sum in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=202. 2025-08-26T19:56:09.1975045Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1975211Z Return the sum of each row of the given sparse tensor. 2025-08-26T19:56:09.1975304Z 2025-08-26T19:56:09.1975535Z Returns the sum of each row of the sparse tensor :attr:`input` in the given 2025-08-26T19:56:09.1975753Z dimensions :attr:`dim`. If :attr:`dim` is a list of dimensions, 2025-08-26T19:56:09.1975967Z reduce over all of them. When sum over all ``sparse_dim``, this method 2025-08-26T19:56:09.1976121Z returns a dense tensor instead of a sparse tensor. 2025-08-26T19:56:09.1976214Z 2025-08-26T19:56:09.1976481Z All summed :attr:`dim` are squeezed (see :func:`torch.squeeze`), resulting an output 2025-08-26T19:56:09.1976692Z tensor having :attr:`dim` fewer dimensions than :attr:`input`. 2025-08-26T19:56:09.1976775Z 2025-08-26T19:56:09.1977000Z During backward, only gradients at ``nnz`` locations of :attr:`input` 2025-08-26T19:56:09.1977257Z will propagate back. Note that the gradients of :attr:`input` is coalesced. 2025-08-26T19:56:09.1977339Z 2025-08-26T19:56:09.1977435Z Args: 2025-08-26T19:56:09.1977565Z input (Tensor): the input sparse tensor 2025-08-26T19:56:09.1977847Z dim (int or tuple of ints): a dimension or a list of dimensions to reduce. Default: reduce 2025-08-26T19:56:09.1977957Z over all dims. 2025-08-26T19:56:09.1978220Z dtype (:class:`torch.dtype`, optional): the desired data type of returned Tensor. 2025-08-26T19:56:09.1978354Z Default: dtype of :attr:`input`. 2025-08-26T19:56:09.1978435Z 2025-08-26T19:56:09.1978527Z Example:: 2025-08-26T19:56:09.1978657Z 2025-08-26T19:56:09.1978748Z >>> nnz = 3 2025-08-26T19:56:09.1978852Z >>> dims = [5, 5, 2, 3] 2025-08-26T19:56:09.1979029Z >>> I = torch.cat([torch.randint(0, dims[0], size=(nnz,)), 2025-08-26T19:56:09.1979217Z torch.randint(0, dims[1], size=(nnz,))], 0).reshape(2, nnz) 2025-08-26T19:56:09.1979358Z >>> V = torch.randn(nnz, dims[2], dims[3]) 2025-08-26T19:56:09.1979467Z >>> size = torch.Size(dims) 2025-08-26T19:56:09.1979624Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:09.1979757Z >>> S = torch.sparse_coo_tensor(I, V, size) 2025-08-26T19:56:09.1979844Z >>> S 2025-08-26T19:56:09.1979974Z tensor(indices=tensor([[2, 0, 3], 2025-08-26T19:56:09.1980075Z [2, 4, 1]]), 2025-08-26T19:56:09.1980209Z values=tensor([[[-0.6438, -1.6467, 1.4004], 2025-08-26T19:56:09.1980339Z [ 0.3411, 0.0918, -0.2312]], 2025-08-26T19:56:09.1992560Z 2025-08-26T19:56:09.1992775Z [[ 0.5348, 0.0634, -2.0494], 2025-08-26T19:56:09.1992898Z [-0.7125, -1.0646, 2.1844]], 2025-08-26T19:56:09.1992985Z 2025-08-26T19:56:09.1993115Z [[ 0.1276, 0.1874, -0.6334], 2025-08-26T19:56:09.1993232Z [-1.9682, -0.5340, 0.7483]]]), 2025-08-26T19:56:09.1993402Z size=(5, 5, 2, 3), nnz=3, layout=torch.sparse_coo) 2025-08-26T19:56:09.1993485Z 2025-08-26T19:56:09.1993791Z # when sum over only part of sparse_dims, return a sparse tensor 2025-08-26T19:56:09.1993927Z >>> torch.sparse.sum(S, [1, 3]) 2025-08-26T19:56:09.1994050Z tensor(indices=tensor([[0, 2, 3]]), 2025-08-26T19:56:09.1994183Z values=tensor([[-1.4512, 0.4073], 2025-08-26T19:56:09.1994330Z [-0.8901, 0.2017], 2025-08-26T19:56:09.1994451Z [-0.3183, -1.7539]]), 2025-08-26T19:56:09.1994610Z size=(5, 2), nnz=3, layout=torch.sparse_coo) 2025-08-26T19:56:09.1994694Z 2025-08-26T19:56:09.1994864Z # when sum over all sparse dim, return a dense tensor 2025-08-26T19:56:09.1994972Z # with summed dims squeezed 2025-08-26T19:56:09.1995090Z >>> torch.sparse.sum(S, [0, 1, 3]) 2025-08-26T19:56:09.1995206Z tensor([-2.6596, -1.1450]) 2025-08-26T19:56:09.1995292Z 2025-08-26T19:56:09.1995557Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.1995652Z 2025-08-26T19:56:09.1995752Z warnings.warn(msg) 2025-08-26T19:56:09.1995843Z 2025-08-26T19:56:09.1996086Z --- Parse Warning: 22 / 146 --- 2025-08-26T19:56:09.1997015Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=as_sparse_gradcheck in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/sparse/__init__.py line=550. 2025-08-26T19:56:09.1997300Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.1997494Z Decorate function, to extend gradcheck for sparse tensors. 2025-08-26T19:56:09.1997591Z 2025-08-26T19:56:09.1997810Z Decorator for torch.autograd.gradcheck or its functools.partial 2025-08-26T19:56:09.1998045Z variants that extends the gradcheck function with support to input 2025-08-26T19:56:09.1998225Z functions that operate on or/and return sparse tensors. 2025-08-26T19:56:09.1998309Z 2025-08-26T19:56:09.1998535Z The specified gradcheck function itself is guaranteed to operate 2025-08-26T19:56:09.1998641Z on strided tensors only. 2025-08-26T19:56:09.1998724Z 2025-08-26T19:56:09.1998828Z For example: 2025-08-26T19:56:09.1998911Z 2025-08-26T19:56:09.1999172Z >>> gradcheck = torch.sparse.as_sparse_gradcheck(torch.autograd.gradcheck) 2025-08-26T19:56:09.1999291Z >>> x = ( 2025-08-26T19:56:09.1999453Z ... torch.tensor([[0, 1], [2, 3]], dtype=torch.float64) 2025-08-26T19:56:09.1999567Z ... .to_sparse_coo() 2025-08-26T19:56:09.1999672Z ... .requires_grad_(True) 2025-08-26T19:56:09.1999770Z ... ) 2025-08-26T19:56:09.1999906Z >>> gradcheck(lambda x: x.to_sparse_csr(), x) 2025-08-26T19:56:09.1999990Z True 2025-08-26T19:56:09.2000086Z 2025-08-26T19:56:09.2000346Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2000439Z 2025-08-26T19:56:09.2000537Z warnings.warn(msg) 2025-08-26T19:56:09.2000618Z 2025-08-26T19:56:09.2000821Z --- Parse Warning: 23 / 146 --- 2025-08-26T19:56:09.2001678Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=vmap in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=39. 2025-08-26T19:56:09.2001990Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2002069Z 2025-08-26T19:56:09.2002291Z vmap is the vectorizing map; ``vmap(func)`` returns a new function that 2025-08-26T19:56:09.2002506Z maps ``func`` over some dimension of the inputs. Semantically, vmap 2025-08-26T19:56:09.2002725Z pushes the map into PyTorch operations called by ``func``, effectively 2025-08-26T19:56:09.2002851Z vectorizing those operations. 2025-08-26T19:56:09.2002932Z 2025-08-26T19:56:09.2003175Z vmap is useful for handling batch dimensions: one can write a function 2025-08-26T19:56:09.2003393Z ``func`` that runs on examples and then lift it to a function that can 2025-08-26T19:56:09.2003611Z take batches of examples with ``vmap(func)``. vmap can also be used to 2025-08-26T19:56:09.2003842Z compute batched gradients when composed with autograd. 2025-08-26T19:56:09.2003927Z 2025-08-26T19:56:09.2004024Z .. note:: 2025-08-26T19:56:09.2004229Z :func:`torch.vmap` is aliased to :func:`torch.func.vmap` for 2025-08-26T19:56:09.2004364Z convenience. Use whichever one you'd like. 2025-08-26T19:56:09.2004462Z 2025-08-26T19:56:09.2004548Z Args: 2025-08-26T19:56:09.2004764Z func (function): A Python function that takes one or more arguments. 2025-08-26T19:56:09.2004896Z Must return one or more Tensors. 2025-08-26T19:56:09.2005104Z in_dims (int or nested structure): Specifies which dimension of the 2025-08-26T19:56:09.2005296Z inputs should be mapped over. ``in_dims`` should have a 2025-08-26T19:56:09.2005491Z structure like the inputs. If the ``in_dim`` for a particular 2025-08-26T19:56:09.2005678Z input is None, then that indicates there is no map dimension. 2025-08-26T19:56:09.2005784Z Default: 0. 2025-08-26T19:56:09.2005984Z out_dims (int or Tuple[int]): Specifies where the mapped dimension 2025-08-26T19:56:09.2006197Z should appear in the outputs. If ``out_dims`` is a Tuple, then 2025-08-26T19:56:09.2006355Z it should have one element per output. Default: 0. 2025-08-26T19:56:09.2006543Z randomness (str): Specifies whether the randomness in this 2025-08-26T19:56:09.2006770Z vmap should be the same or different across batches. If 'different', 2025-08-26T19:56:09.2006976Z the randomness for each batch will be different. If 'same', the 2025-08-26T19:56:09.2007211Z randomness will be the same across batches. If 'error', any calls to 2025-08-26T19:56:09.2007425Z random functions will error. Default: 'error'. WARNING: this flag 2025-08-26T19:56:09.2007635Z only applies to random PyTorch operations and does not apply to 2025-08-26T19:56:09.2007787Z Python's random module or numpy randomness. 2025-08-26T19:56:09.2008019Z chunk_size (None or int): If None (default), apply a single vmap over inputs. 2025-08-26T19:56:09.2008281Z If not None, then compute the vmap :attr:`chunk_size` samples at a time. 2025-08-26T19:56:09.2008544Z Note that :attr:`chunk_size=1` is equivalent to computing the vmap with a for-loop. 2025-08-26T19:56:09.2008926Z If you run into memory issues computing the vmap, please try a non-None chunk_size. 2025-08-26T19:56:09.2009026Z 2025-08-26T19:56:09.2009114Z Returns: 2025-08-26T19:56:09.2009322Z Returns a new "batched" function. It takes the same inputs as 2025-08-26T19:56:09.2009514Z ``func``, except each input has an extra dimension at the index 2025-08-26T19:56:09.2009708Z specified by ``in_dims``. It takes returns the same outputs as 2025-08-26T19:56:09.2009911Z ``func``, except each output has an extra dimension at the index 2025-08-26T19:56:09.2010018Z specified by ``out_dims``. 2025-08-26T19:56:09.2010110Z 2025-08-26T19:56:09.2010204Z .. warning: 2025-08-26T19:56:09.2010442Z :func:`vmap` works best with functional-style code. Please do not 2025-08-26T19:56:09.2010646Z perform any side-effects in ``func``, with the exception of 2025-08-26T19:56:09.2010888Z in-place PyTorch operations. Examples of side-effects include mutating 2025-08-26T19:56:09.2011133Z Python data structures and assigning values to variables not captured 2025-08-26T19:56:09.2011222Z in ``func``. 2025-08-26T19:56:09.2011303Z 2025-08-26T19:56:09.2011554Z One example of using :func:`vmap` is to compute batched dot products. PyTorch 2025-08-26T19:56:09.2011834Z doesn't provide a batched ``torch.dot`` API; instead of unsuccessfully 2025-08-26T19:56:09.2012074Z rummaging through docs, use :func:`vmap` to construct a new function. 2025-08-26T19:56:09.2012156Z 2025-08-26T19:56:09.2012265Z >>> torch.dot # [D], [D] -> [] 2025-08-26T19:56:09.2012512Z >>> batched_dot = torch.func.vmap(torch.dot) # [N, D], [N, D] -> [N] 2025-08-26T19:56:09.2012648Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T19:56:09.2012762Z >>> batched_dot(x, y) 2025-08-26T19:56:09.2012844Z 2025-08-26T19:56:09.2013076Z :func:`vmap` can be helpful in hiding batch dimensions, leading to a simpler 2025-08-26T19:56:09.2013200Z model authoring experience. 2025-08-26T19:56:09.2013284Z 2025-08-26T19:56:09.2013414Z >>> batch_size, feature_size = 3, 5 2025-08-26T19:56:09.2013591Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T19:56:09.2013677Z >>> 2025-08-26T19:56:09.2013797Z >>> def model(feature_vec): 2025-08-26T19:56:09.2013934Z >>> # Very simple linear model with activation 2025-08-26T19:56:09.2014064Z >>> return feature_vec.dot(weights).relu() 2025-08-26T19:56:09.2014167Z >>> 2025-08-26T19:56:09.2014320Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T19:56:09.2014460Z >>> result = torch.vmap(model)(examples) 2025-08-26T19:56:09.2014545Z 2025-08-26T19:56:09.2014800Z :func:`vmap` can also help vectorize computations that were previously difficult 2025-08-26T19:56:09.2015051Z or impossible to batch. One example is higher-order gradient computation. 2025-08-26T19:56:09.2015285Z The PyTorch autograd engine computes vjps (vector-Jacobian products). 2025-08-26T19:56:09.2015528Z Computing a full Jacobian matrix for some function f: R^N -> R^N usually 2025-08-26T19:56:09.2015779Z requires N calls to ``autograd.grad``, one per Jacobian row. Using :func:`vmap`, 2025-08-26T19:56:09.2016033Z we can vectorize the whole computation, computing the Jacobian in a single 2025-08-26T19:56:09.2016138Z call to ``autograd.grad``. 2025-08-26T19:56:09.2016224Z 2025-08-26T19:56:09.2016323Z >>> # Setup 2025-08-26T19:56:09.2016408Z >>> N = 5 2025-08-26T19:56:09.2016505Z >>> f = lambda x: x**2 2025-08-26T19:56:09.2016645Z >>> x = torch.randn(N, requires_grad=True) 2025-08-26T19:56:09.2016760Z >>> y = f(x) 2025-08-26T19:56:09.2016871Z >>> I_N = torch.eye(N) 2025-08-26T19:56:09.2016952Z >>> 2025-08-26T19:56:09.2017058Z >>> # Sequential approach 2025-08-26T19:56:09.2017292Z >>> jacobian_rows = [torch.autograd.grad(y, x, v, retain_graph=True)[0] 2025-08-26T19:56:09.2017409Z >>> for v in I_N.unbind()] 2025-08-26T19:56:09.2017546Z >>> jacobian = torch.stack(jacobian_rows) 2025-08-26T19:56:09.2017628Z >>> 2025-08-26T19:56:09.2017747Z >>> # vectorized gradient computation 2025-08-26T19:56:09.2017855Z >>> def get_vjp(v): 2025-08-26T19:56:09.2017978Z >>> return torch.autograd.grad(y, x, v) 2025-08-26T19:56:09.2018108Z >>> jacobian = torch.vmap(get_vjp)(I_N) 2025-08-26T19:56:09.2018192Z 2025-08-26T19:56:09.2018461Z :func:`vmap` can also be nested, producing an output with multiple batched dimensions 2025-08-26T19:56:09.2018559Z 2025-08-26T19:56:09.2018666Z >>> torch.dot # [D], [D] -> [] 2025-08-26T19:56:09.2018801Z >>> batched_dot = torch.vmap( 2025-08-26T19:56:09.2018919Z ... torch.vmap(torch.dot) 2025-08-26T19:56:09.2019038Z ... ) # [N1, N0, D], [N1, N0, D] -> [N1, N0] 2025-08-26T19:56:09.2019190Z >>> x, y = torch.randn(2, 3, 5), torch.randn(2, 3, 5) 2025-08-26T19:56:09.2019319Z >>> batched_dot(x, y) # tensor of size [2, 3] 2025-08-26T19:56:09.2019399Z 2025-08-26T19:56:09.2019658Z If the inputs are not batched along the first dimension, ``in_dims`` specifies 2025-08-26T19:56:09.2019842Z the dimension that each inputs are batched along as 2025-08-26T19:56:09.2019937Z 2025-08-26T19:56:09.2020042Z >>> torch.dot # [N], [N] -> [] 2025-08-26T19:56:09.2020265Z >>> batched_dot = torch.vmap(torch.dot, in_dims=1) # [N, D], [N, D] -> [D] 2025-08-26T19:56:09.2020404Z >>> x, y = torch.randn(2, 5), torch.randn(2, 5) 2025-08-26T19:56:09.2020526Z >>> batched_dot( 2025-08-26T19:56:09.2020626Z ... x, y 2025-08-26T19:56:09.2020822Z ... ) # output is [5] instead of [2] if batched along the 0th dimension 2025-08-26T19:56:09.2020905Z 2025-08-26T19:56:09.2021182Z If there are multiple inputs each of which is batched along different dimensions, 2025-08-26T19:56:09.2021384Z ``in_dims`` must be a tuple with the batch dimension for each input as 2025-08-26T19:56:09.2021478Z 2025-08-26T19:56:09.2021584Z >>> torch.dot # [D], [D] -> [] 2025-08-26T19:56:09.2021823Z >>> batched_dot = torch.vmap(torch.dot, in_dims=(0, None)) # [N, D], [D] -> [N] 2025-08-26T19:56:09.2021962Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T19:56:09.2022055Z >>> batched_dot( 2025-08-26T19:56:09.2022152Z ... x, y 2025-08-26T19:56:09.2022350Z ... ) # second arg doesn't have a batch dim because in_dim[1] was None 2025-08-26T19:56:09.2022431Z 2025-08-26T19:56:09.2022688Z If the input is a Python struct, ``in_dims`` must be a tuple containing a struct 2025-08-26T19:56:09.2022802Z matching the shape of the input: 2025-08-26T19:56:09.2022898Z 2025-08-26T19:56:09.2023042Z >>> f = lambda dict: torch.dot(dict["x"], dict["y"]) 2025-08-26T19:56:09.2023167Z >>> x, y = torch.randn(2, 5), torch.randn(5) 2025-08-26T19:56:09.2023281Z >>> input = {"x": x, "y": y} 2025-08-26T19:56:09.2023461Z >>> batched_dot = torch.vmap(f, in_dims=({"x": 0, "y": None},)) 2025-08-26T19:56:09.2023575Z >>> batched_dot(input) 2025-08-26T19:56:09.2023657Z 2025-08-26T19:56:09.2023939Z By default, the output is batched along the first dimension. However, it can be batched 2025-08-26T19:56:09.2024077Z along any dimension by using ``out_dims`` 2025-08-26T19:56:09.2024159Z 2025-08-26T19:56:09.2024258Z >>> f = lambda x: x**2 2025-08-26T19:56:09.2024370Z >>> x = torch.randn(2, 5) 2025-08-26T19:56:09.2024500Z >>> batched_pow = torch.vmap(f, out_dims=1) 2025-08-26T19:56:09.2024646Z >>> batched_pow(x) # [5, 2] 2025-08-26T19:56:09.2024728Z 2025-08-26T19:56:09.2025026Z For any function that uses kwargs, the returned function will not batch the kwargs but will 2025-08-26T19:56:09.2025130Z accept kwargs 2025-08-26T19:56:09.2025212Z 2025-08-26T19:56:09.2025326Z >>> x = torch.randn([2, 5]) 2025-08-26T19:56:09.2025425Z >>> def fn(x, scale=4.): 2025-08-26T19:56:09.2025522Z >>> return x * scale 2025-08-26T19:56:09.2025617Z >>> 2025-08-26T19:56:09.2025729Z >>> batched_pow = torch.vmap(fn) 2025-08-26T19:56:09.2025887Z >>> assert torch.allclose(batched_pow(x), x * 4) 2025-08-26T19:56:09.2026116Z >>> batched_pow(x, scale=x) # scale is not batched, output has shape [2, 2, 5] 2025-08-26T19:56:09.2026198Z 2025-08-26T19:56:09.2026302Z .. note:: 2025-08-26T19:56:09.2026528Z vmap does not provide general autobatching or handle variable-length 2025-08-26T19:56:09.2026651Z sequences out of the box. 2025-08-26T19:56:09.2026760Z 2025-08-26T19:56:09.2027019Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2027112Z 2025-08-26T19:56:09.2027213Z warnings.warn(msg) 2025-08-26T19:56:09.2027295Z 2025-08-26T19:56:09.2027531Z --- Parse Warning: 24 / 146 --- 2025-08-26T19:56:09.2028426Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=grad in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_functorch/apis.py line=306. 2025-08-26T19:56:09.2028711Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2028955Z ``grad`` operator helps computing gradients of ``func`` with respect to the 2025-08-26T19:56:09.2029173Z input(s) specified by ``argnums``. This operator can be nested to 2025-08-26T19:56:09.2029320Z compute higher-order gradients. 2025-08-26T19:56:09.2029404Z 2025-08-26T19:56:09.2029504Z Args: 2025-08-26T19:56:09.2029718Z func (Callable): A Python function that takes one or more arguments. 2025-08-26T19:56:09.2029997Z Must return a single-element Tensor. If specified ``has_aux`` equals ``True``, 2025-08-26T19:56:09.2030269Z function can return a tuple of single-element Tensor and other auxiliary objects: 2025-08-26T19:56:09.2030367Z ``(output, aux)``. 2025-08-26T19:56:09.2030661Z argnums (int or Tuple[int]): Specifies arguments to compute gradients with respect to. 2025-08-26T19:56:09.2030868Z ``argnums`` can be single integer or tuple of integers. Default: 0. 2025-08-26T19:56:09.2031099Z has_aux (bool): Flag indicating that ``func`` returns a tensor and other 2025-08-26T19:56:09.2031268Z auxiliary objects: ``(output, aux)``. Default: False. 2025-08-26T19:56:09.2031349Z 2025-08-26T19:56:09.2031450Z Returns: 2025-08-26T19:56:09.2031742Z Function to compute gradients with respect to its inputs. By default, the output of 2025-08-26T19:56:09.2031990Z the function is the gradient tensor(s) with respect to the first argument. 2025-08-26T19:56:09.2032265Z If specified ``has_aux`` equals ``True``, tuple of gradients and output auxiliary objects 2025-08-26T19:56:09.2032518Z is returned. If ``argnums`` is a tuple of integers, a tuple of output gradients with 2025-08-26T19:56:09.2032676Z respect to each ``argnums`` value is returned. 2025-08-26T19:56:09.2032758Z 2025-08-26T19:56:09.2032874Z Example of using ``grad``: 2025-08-26T19:56:09.2032954Z 2025-08-26T19:56:09.2033055Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2033182Z >>> from torch.func import grad 2025-08-26T19:56:09.2033282Z >>> x = torch.randn([]) 2025-08-26T19:56:09.2033424Z >>> cos_x = grad(lambda x: torch.sin(x))(x) 2025-08-26T19:56:09.2033578Z >>> assert torch.allclose(cos_x, x.cos()) 2025-08-26T19:56:09.2033666Z >>> 2025-08-26T19:56:09.2033786Z >>> # Second-order gradients 2025-08-26T19:56:09.2033938Z >>> neg_sin_x = grad(grad(lambda x: torch.sin(x)))(x) 2025-08-26T19:56:09.2034086Z >>> assert torch.allclose(neg_sin_x, -x.sin()) 2025-08-26T19:56:09.2034165Z 2025-08-26T19:56:09.2034420Z When composed with ``vmap``, ``grad`` can be used to compute per-sample-gradients: 2025-08-26T19:56:09.2034514Z 2025-08-26T19:56:09.2034615Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2034741Z >>> from torch.func import grad, vmap 2025-08-26T19:56:09.2034867Z >>> batch_size, feature_size = 3, 5 2025-08-26T19:56:09.2034952Z >>> 2025-08-26T19:56:09.2035084Z >>> def model(weights, feature_vec): 2025-08-26T19:56:09.2035217Z >>> # Very simple linear model with activation 2025-08-26T19:56:09.2035338Z >>> assert feature_vec.dim() == 1 2025-08-26T19:56:09.2035507Z >>> return feature_vec.dot(weights).relu() 2025-08-26T19:56:09.2035591Z >>> 2025-08-26T19:56:09.2035743Z >>> def compute_loss(weights, example, target): 2025-08-26T19:56:09.2035858Z >>> y = model(weights, example) 2025-08-26T19:56:09.2035996Z >>> return ((y - target) ** 2).mean() # MSELoss 2025-08-26T19:56:09.2036091Z >>> 2025-08-26T19:56:09.2036272Z >>> weights = torch.randn(feature_size, requires_grad=True) 2025-08-26T19:56:09.2036476Z >>> examples = torch.randn(batch_size, feature_size) 2025-08-26T19:56:09.2036600Z >>> targets = torch.randn(batch_size) 2025-08-26T19:56:09.2036729Z >>> inputs = (weights, examples, targets) 2025-08-26T19:56:09.2036980Z >>> grad_weight_per_example = vmap(grad(compute_loss), in_dims=(None, 0, 0))( 2025-08-26T19:56:09.2037103Z ... *inputs 2025-08-26T19:56:09.2037206Z ... ) 2025-08-26T19:56:09.2037290Z 2025-08-26T19:56:09.2037649Z Example of using ``grad`` with ``has_aux`` and ``argnums``: 2025-08-26T19:56:09.2037745Z 2025-08-26T19:56:09.2037846Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2037972Z >>> from torch.func import grad 2025-08-26T19:56:09.2038085Z >>> def my_loss_func(y, y_pred): 2025-08-26T19:56:09.2038218Z >>> loss_per_sample = (0.5 * y_pred - y) ** 2 2025-08-26T19:56:09.2038350Z >>> loss = loss_per_sample.mean() 2025-08-26T19:56:09.2038481Z >>> return loss, (y_pred, loss_per_sample) 2025-08-26T19:56:09.2038576Z >>> 2025-08-26T19:56:09.2038732Z >>> fn = grad(my_loss_func, argnums=(0, 1), has_aux=True) 2025-08-26T19:56:09.2038841Z >>> y_true = torch.rand(4) 2025-08-26T19:56:09.2038987Z >>> y_preds = torch.rand(4, requires_grad=True) 2025-08-26T19:56:09.2039098Z >>> out = fn(y_true, y_preds) 2025-08-26T19:56:09.2039362Z >>> # > output is ((grads w.r.t y_true, grads w.r.t y_preds), (y_pred, loss_per_sample)) 2025-08-26T19:56:09.2039444Z 2025-08-26T19:56:09.2039536Z .. note:: 2025-08-26T19:56:09.2039720Z Using PyTorch ``torch.no_grad`` together with ``grad``. 2025-08-26T19:56:09.2039802Z 2025-08-26T19:56:09.2039953Z Case 1: Using ``torch.no_grad`` inside a function: 2025-08-26T19:56:09.2040046Z 2025-08-26T19:56:09.2040153Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2040258Z >>> def f(x): 2025-08-26T19:56:09.2040371Z >>> with torch.no_grad(): 2025-08-26T19:56:09.2040468Z >>> c = x ** 2 2025-08-26T19:56:09.2040577Z >>> return x - c 2025-08-26T19:56:09.2040659Z 2025-08-26T19:56:09.2040873Z In this case, ``grad(f)(x)`` will respect the inner ``torch.no_grad``. 2025-08-26T19:56:09.2040955Z 2025-08-26T19:56:09.2041222Z Case 2: Using ``grad`` inside ``torch.no_grad`` context manager: 2025-08-26T19:56:09.2041322Z 2025-08-26T19:56:09.2041428Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2041549Z >>> with torch.no_grad(): 2025-08-26T19:56:09.2041646Z >>> grad(f)(x) 2025-08-26T19:56:09.2041730Z 2025-08-26T19:56:09.2041969Z In this case, ``grad`` will respect the inner ``torch.no_grad``, but not the 2025-08-26T19:56:09.2042193Z outer one. This is because ``grad`` is a "function transform": its result 2025-08-26T19:56:09.2042435Z should not depend on the result of a context manager outside of ``f``. 2025-08-26T19:56:09.2042517Z 2025-08-26T19:56:09.2042601Z 2025-08-26T19:56:09.2042875Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2042959Z 2025-08-26T19:56:09.2043058Z warnings.warn(msg) 2025-08-26T19:56:09.2043151Z 2025-08-26T19:56:09.2043374Z --- Parse Warning: 25 / 146 --- 2025-08-26T19:56:09.2044423Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CustomOpDef.register_fake in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/custom_ops.py line=397. 2025-08-26T19:56:09.2044677Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.2044875Z Register a FakeTensor implementation for this custom op. 2025-08-26T19:56:09.2044955Z 2025-08-26T19:56:09.2045242Z This is necessary to get the operator to work efficiently with torch.compile. 2025-08-26T19:56:09.2045339Z 2025-08-26T19:56:09.2045563Z The Fake impl (sometimes also known as a meta kernel or abstract impl) 2025-08-26T19:56:09.2045808Z specifies the behavior of this operator on Tensors that carry no data. 2025-08-26T19:56:09.2046005Z Given some input Tensors with certain properties 2025-08-26T19:56:09.2046273Z (sizes/strides/storage_offset/device), it specifies what the properties of 2025-08-26T19:56:09.2046399Z the output Tensors are. 2025-08-26T19:56:09.2046482Z 2025-08-26T19:56:09.2046701Z Please see :func:`torch.library.register_fake` for more details. 2025-08-26T19:56:09.2046782Z 2025-08-26T19:56:09.2046868Z Args: 2025-08-26T19:56:09.2047055Z fn (Callable): The function to register as the FakeTensor 2025-08-26T19:56:09.2047155Z implementation. 2025-08-26T19:56:09.2047241Z 2025-08-26T19:56:09.2047346Z Examples: 2025-08-26T19:56:09.2047443Z >>> import torch 2025-08-26T19:56:09.2047563Z >>> import numpy as np 2025-08-26T19:56:09.2047678Z >>> from torch import Tensor 2025-08-26T19:56:09.2047762Z >>> 2025-08-26T19:56:09.2047971Z >>> # Example 1: an operator without data-dependent output shape 2025-08-26T19:56:09.2048166Z >>> @torch.library.custom_op("mylib::linear", mutates_args=()) 2025-08-26T19:56:09.2048373Z >>> def linear(x: Tensor, weight: Tensor, bias: Tensor) -> Tensor: 2025-08-26T19:56:09.2048498Z >>> return (x @ weight.t()) + bias 2025-08-26T19:56:09.2048582Z >>> 2025-08-26T19:56:09.2048705Z >>> @linear.register_fake 2025-08-26T19:56:09.2048877Z >>> def _(x, weight, bias): 2025-08-26T19:56:09.2049005Z >>> assert x.dim() == 2 2025-08-26T19:56:09.2049126Z >>> assert weight.dim() == 2 2025-08-26T19:56:09.2049236Z >>> assert bias.dim() == 1 2025-08-26T19:56:09.2049380Z >>> assert x.shape[1] == weight.shape[1] 2025-08-26T19:56:09.2049516Z >>> assert weight.shape[0] == bias.shape[0] 2025-08-26T19:56:09.2049655Z >>> assert x.device == weight.device 2025-08-26T19:56:09.2049843Z >>> return x.new_empty(x.size(0), weight.size(0)) 2025-08-26T19:56:09.2049929Z >>> 2025-08-26T19:56:09.2050046Z >>> x = torch.randn(2, 2) 2025-08-26T19:56:09.2050160Z >>> weight = torch.randn(2, 2) 2025-08-26T19:56:09.2050276Z >>> bias = torch.randn(2) 2025-08-26T19:56:09.2050415Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:56:09.2050611Z >>> out = torch.compile(linear, fullgraph=True)(x, weight, bias) 2025-08-26T19:56:09.2050767Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:56:09.2051020Z >>> assert torch.allclose(out, torch.nn.functional.linear(x, weight, bias)) 2025-08-26T19:56:09.2051120Z >>> 2025-08-26T19:56:09.2051303Z >>> # Example 2: an operator with data-dependent output shape 2025-08-26T19:56:09.2051513Z >>> @torch.library.custom_op("mylib::nonzero", mutates_args=()) 2025-08-26T19:56:09.2051650Z >>> def nonzero(x: Tensor) -> Tensor: 2025-08-26T19:56:09.2051791Z >>> x_np = x.cpu().numpy() 2025-08-26T19:56:09.2051939Z >>> res = np.stack(np.nonzero(x_np), axis=1) 2025-08-26T19:56:09.2052079Z >>> return torch.tensor(res, device=x.device) 2025-08-26T19:56:09.2052166Z >>> 2025-08-26T19:56:09.2052289Z >>> @nonzero.register_fake 2025-08-26T19:56:09.2052379Z >>> def _(x): 2025-08-26T19:56:09.2052544Z >>> # Number of nonzero-elements is data-dependent. 2025-08-26T19:56:09.2052740Z >>> # Since we cannot peek at the data in an abstract impl, 2025-08-26T19:56:09.2052904Z >>> # we use the ctx object to construct a new symint that 2025-08-26T19:56:09.2053046Z >>> # represents the data-dependent size. 2025-08-26T19:56:09.2053168Z >>> ctx = torch.library.get_ctx() 2025-08-26T19:56:09.2053333Z >>> nnz = ctx.new_dynamic_size() 2025-08-26T19:56:09.2053448Z >>> shape = [nnz, x.dim()] 2025-08-26T19:56:09.2053600Z >>> result = x.new_empty(shape, dtype=torch.int64) 2025-08-26T19:56:09.2053713Z >>> return result 2025-08-26T19:56:09.2053794Z >>> 2025-08-26T19:56:09.2053923Z >>> x = torch.tensor([0, 1, 2, 0, 0, 1]) 2025-08-26T19:56:09.2054061Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:56:09.2054210Z >>> out = torch.compile(nonzero, fullgraph=True)(x) 2025-08-26T19:56:09.2054359Z >>> # xdoctest: +SKIP("Requires Python <= 3.11") 2025-08-26T19:56:09.2054493Z >>> assert torch.allclose(out, x.nonzero()) 2025-08-26T19:56:09.2054586Z 2025-08-26T19:56:09.2054672Z 2025-08-26T19:56:09.2055218Z Original Error: IndentationError('expected an indented block after function definition on line 36', ('', 37, 1, '_._ = None\n', 37, 2)) 2025-08-26T19:56:09.2055317Z 2025-08-26T19:56:09.2055404Z _._ = None 2025-08-26T19:56:09.2055498Z ^ 2025-08-26T19:56:09.2055599Z warnings.warn(msg) 2025-08-26T19:56:09.2055681Z 2025-08-26T19:56:09.2055904Z --- Parse Warning: 26 / 146 --- 2025-08-26T19:56:09.2056899Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=unsafe_generate_fake_kernels in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/fake_profile.py line=94. 2025-08-26T19:56:09.2057185Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2057268Z 2025-08-26T19:56:09.2057505Z Registers a fake kernel based on the given operator profiles. This fake 2025-08-26T19:56:09.2057772Z kernel registration will override any existing fake kernel registrations. 2025-08-26T19:56:09.2057854Z 2025-08-26T19:56:09.2058115Z The input is a dictionary mapping operator names to a set of operator 2025-08-26T19:56:09.2058355Z profiles, which we will use to generate fake kernels. The operator profiles 2025-08-26T19:56:09.2058558Z are a record of the input and output tensor metadata. Based on this 2025-08-26T19:56:09.2058817Z information we will match a given input to the recorded profile, and return 2025-08-26T19:56:09.2059047Z an output with the same metadata as in the recorded profile. If a profile 2025-08-26T19:56:09.2059204Z doesn't exist then an exception will be thrown. 2025-08-26T19:56:09.2059286Z 2025-08-26T19:56:09.2059522Z The fake kernel generation is considered unsafe because it relies on the 2025-08-26T19:56:09.2059766Z rigid, pre-defined operator profiles that do not account for potential 2025-08-26T19:56:09.2060019Z variations in output behavior. Specifically, the generated kernels assume a 2025-08-26T19:56:09.2060292Z fixed relationship between input and output ranks. However, in reality, it's 2025-08-26T19:56:09.2060565Z possible that data-dependent operations may produce outputs of different 2025-08-26T19:56:09.2060798Z ranks even when given inputs of the same rank. The generated fake kernels 2025-08-26T19:56:09.2061017Z are inflexible and unable to accommodate these nuances, making them 2025-08-26T19:56:09.2061116Z potentially unsafe. 2025-08-26T19:56:09.2061209Z 2025-08-26T19:56:09.2061292Z Args: 2025-08-26T19:56:09.2061512Z op_profiles (dict[str, set[OpProfile]]): A dictionary mapping operator 2025-08-26T19:56:09.2061751Z name to a set of operator profiles from which we will generate fake 2025-08-26T19:56:09.2061839Z kernels. 2025-08-26T19:56:09.2061931Z 2025-08-26T19:56:09.2062019Z Examples: 2025-08-26T19:56:09.2062097Z 2025-08-26T19:56:09.2062281Z >>> # Example: Registering an op-profile from draft-export 2025-08-26T19:56:09.2062376Z >>> import torch 2025-08-26T19:56:09.2062587Z >>> from torch.export._draft_export import draft_export 2025-08-26T19:56:09.2062674Z >>> 2025-08-26T19:56:09.2062859Z >>> @torch.library.custom_op("mylib::foo", mutates_args=()) 2025-08-26T19:56:09.2063000Z >>> def foo(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T19:56:09.2063097Z >>> return x + y 2025-08-26T19:56:09.2063189Z >>> 2025-08-26T19:56:09.2063300Z >>> class M(torch.nn.Module): 2025-08-26T19:56:09.2063407Z >>> def forward(self, a, b): 2025-08-26T19:56:09.2063566Z >>> res = torch.ops.mylib.foo(a, b) # no fake impl 2025-08-26T19:56:09.2063663Z >>> return res 2025-08-26T19:56:09.2063755Z >>> 2025-08-26T19:56:09.2063928Z >>> ep = draft_export(M(), (torch.ones(3, 4), torch.ones(3, 4)) 2025-08-26T19:56:09.2064013Z >>> 2025-08-26T19:56:09.2064326Z >>> with torch._library.fake_profile.unsafe_generate_fake_kernels(ep._report.op_profiles): 2025-08-26T19:56:09.2064456Z >>> decomp = ep.run_decompositions() 2025-08-26T19:56:09.2064551Z 2025-08-26T19:56:09.2064633Z 2025-08-26T19:56:09.2064889Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2064982Z 2025-08-26T19:56:09.2065081Z warnings.warn(msg) 2025-08-26T19:56:09.2065164Z 2025-08-26T19:56:09.2065374Z --- Parse Warning: 27 / 146 --- 2025-08-26T19:56:09.2066254Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=triton_op in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=96. 2025-08-26T19:56:09.2066535Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2066791Z Create a custom operator whose implementation is backed by 1+ triton kernels. 2025-08-26T19:56:09.2066886Z 2025-08-26T19:56:09.2067104Z This is a more structured way of using triton kernels with PyTorch. 2025-08-26T19:56:09.2067396Z Prefer using triton kernels with no ``torch.library`` custom operator wrappers 2025-08-26T19:56:09.2067670Z (like :func:`torch.library.custom_op`, :func:`torch.library.triton_op`) because 2025-08-26T19:56:09.2067767Z that is simpler; 2025-08-26T19:56:09.2068024Z only use :func:`torch.library.custom_op`/:func:`torch.library.triton_op` if you 2025-08-26T19:56:09.2068266Z want to create an operator that behaves like PyTorch built-in operators. 2025-08-26T19:56:09.2068480Z For example, you may use a ``torch.library`` wrapper API to define the 2025-08-26T19:56:09.2068713Z behavior of the triton kernel when passed a tensor subclass or under 2025-08-26T19:56:09.2068818Z a TorchDispatchMode. 2025-08-26T19:56:09.2068899Z 2025-08-26T19:56:09.2069162Z Use :func:`torch.library.triton_op` instead of :func:`torch.library.custom_op` 2025-08-26T19:56:09.2069264Z when the implementation 2025-08-26T19:56:09.2069495Z consists of 1+ triton kernels. :func:`torch.library.custom_op` treats 2025-08-26T19:56:09.2069707Z custom operators as opaque (:func:`torch.compile` and 2025-08-26T19:56:09.2069938Z :func:`torch.export.export` will never trace into them), but ``triton_op`` 2025-08-26T19:56:09.2070172Z makes the implementation visible to these subsystems, allowing them 2025-08-26T19:56:09.2070286Z to optimize the triton kernel(s). 2025-08-26T19:56:09.2070375Z 2025-08-26T19:56:09.2070566Z Note that ``fn`` must only consist of calls to PyTorch-understood 2025-08-26T19:56:09.2070823Z operators and triton kernels. Any triton kernels called inside ``fn`` 2025-08-26T19:56:09.2071030Z must be wrapped in a call to :func:`torch.library.wrap_triton`. 2025-08-26T19:56:09.2071111Z 2025-08-26T19:56:09.2071210Z Args: 2025-08-26T19:56:09.2071440Z name (str): A name for the custom op that looks like "{namespace}::{name}", 2025-08-26T19:56:09.2071701Z e.g. "mylib::my_linear". The name is used as the op's stable identifier 2025-08-26T19:56:09.2071884Z in PyTorch subsystems (e.g. torch.export, FX graphs). 2025-08-26T19:56:09.2072126Z To avoid name collisions, please use your project name as the namespace; 2025-08-26T19:56:09.2072345Z e.g. all custom ops in pytorch/fbgemm use "fbgemm" as the namespace. 2025-08-26T19:56:09.2072625Z mutates_args (Iterable[str] or "unknown"): The names of args that the function mutates. 2025-08-26T19:56:09.2072877Z This MUST be accurate, otherwise, the behavior is undefined. If "unknown", 2025-08-26T19:56:09.2073143Z it pessimistically assumes that all inputs to the operator are being mutated. 2025-08-26T19:56:09.2073330Z schema (None | str): A schema string for the operator. If None 2025-08-26T19:56:09.2073551Z (recommended) we'll infer a schema for the operator from its type 2025-08-26T19:56:09.2073761Z annotations. We recommend letting us infer a schema unless you 2025-08-26T19:56:09.2073890Z have a specific reason not to. 2025-08-26T19:56:09.2074041Z Example: "(Tensor x, int y) -> (Tensor, Tensor)". 2025-08-26T19:56:09.2074122Z 2025-08-26T19:56:09.2074229Z Example:: 2025-08-26T19:56:09.2074309Z 2025-08-26T19:56:09.2074464Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:09.2074561Z >>> import torch 2025-08-26T19:56:09.2074715Z >>> from torch.library import triton_op, wrap_triton 2025-08-26T19:56:09.2074815Z >>> 2025-08-26T19:56:09.2074909Z >>> import triton 2025-08-26T19:56:09.2075034Z >>> from triton import language as tl 2025-08-26T19:56:09.2075131Z >>> 2025-08-26T19:56:09.2075222Z >>> @triton.jit 2025-08-26T19:56:09.2075328Z >>> def add_kernel( 2025-08-26T19:56:09.2075423Z >>> in_ptr0, 2025-08-26T19:56:09.2075540Z >>> in_ptr1, 2025-08-26T19:56:09.2075645Z >>> out_ptr, 2025-08-26T19:56:09.2075739Z >>> n_elements, 2025-08-26T19:56:09.2075870Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T19:56:09.2075959Z >>> ): 2025-08-26T19:56:09.2076075Z >>> pid = tl.program_id(axis=0) 2025-08-26T19:56:09.2076205Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T19:56:09.2076358Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T19:56:09.2076484Z >>> mask = offsets < n_elements 2025-08-26T19:56:09.2076618Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T19:56:09.2076745Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T19:56:09.2076862Z >>> output = x + y 2025-08-26T19:56:09.2077012Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T19:56:09.2077113Z >>> 2025-08-26T19:56:09.2077247Z >>> @triton_op("mylib::add", mutates_args={}) 2025-08-26T19:56:09.2077458Z >>> def add(x: torch.Tensor, y: torch.Tensor) -> torch.Tensor: 2025-08-26T19:56:09.2077586Z >>> output = torch.empty_like(x) 2025-08-26T19:56:09.2077702Z >>> n_elements = output.numel() 2025-08-26T19:56:09.2077795Z >>> 2025-08-26T19:56:09.2077900Z >>> def grid(meta): 2025-08-26T19:56:09.2078071Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T19:56:09.2078164Z >>> 2025-08-26T19:56:09.2078376Z >>> # NB: we need to wrap the triton kernel in a call to wrap_triton 2025-08-26T19:56:09.2078580Z >>> wrap_triton(add_kernel)[grid](x, y, output, n_elements, 16) 2025-08-26T19:56:09.2078679Z >>> return output 2025-08-26T19:56:09.2078763Z >>> 2025-08-26T19:56:09.2078874Z >>> @torch.compile 2025-08-26T19:56:09.2079001Z >>> def f(x, y): 2025-08-26T19:56:09.2079114Z >>> return add(x, y) 2025-08-26T19:56:09.2079199Z >>> 2025-08-26T19:56:09.2079318Z >>> x = torch.randn(3, device="cuda") 2025-08-26T19:56:09.2079446Z >>> y = torch.randn(3, device="cuda") 2025-08-26T19:56:09.2079529Z >>> 2025-08-26T19:56:09.2079621Z >>> z = f(x, y) 2025-08-26T19:56:09.2079754Z >>> assert torch.allclose(z, x + y) 2025-08-26T19:56:09.2079838Z 2025-08-26T19:56:09.2079935Z 2025-08-26T19:56:09.2080197Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2080280Z 2025-08-26T19:56:09.2080389Z warnings.warn(msg) 2025-08-26T19:56:09.2080469Z 2025-08-26T19:56:09.2080681Z --- Parse Warning: 28 / 146 --- 2025-08-26T19:56:09.2081574Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=wrap_triton in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_library/triton.py line=296. 2025-08-26T19:56:09.2081849Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2082060Z Allows capture of a triton kernel into a graph via make_fx or 2025-08-26T19:56:09.2082170Z non-strict ``torch.export``. 2025-08-26T19:56:09.2082262Z 2025-08-26T19:56:09.2082452Z These technologies perform Dispatcher-based tracing (via 2025-08-26T19:56:09.2082655Z ``__torch_dispatch__``) and cannot see calls to raw triton kernels. 2025-08-26T19:56:09.2082869Z The ``wrap_triton`` API wraps a triton kernel into a callable that 2025-08-26T19:56:09.2082989Z can actually be traced into a graph. 2025-08-26T19:56:09.2083083Z 2025-08-26T19:56:09.2083298Z Please use this API together with :func:`torch.library.triton_op`. 2025-08-26T19:56:09.2083378Z 2025-08-26T19:56:09.2083481Z Examples: 2025-08-26T19:56:09.2083598Z 2025-08-26T19:56:09.2083714Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2083813Z >>> import torch 2025-08-26T19:56:09.2083911Z >>> import triton 2025-08-26T19:56:09.2084042Z >>> from triton import language as tl 2025-08-26T19:56:09.2084224Z >>> from torch.fx.experimental.proxy_tensor import make_fx 2025-08-26T19:56:09.2084368Z >>> from torch.library import wrap_triton 2025-08-26T19:56:09.2084453Z >>> 2025-08-26T19:56:09.2084545Z >>> @triton.jit 2025-08-26T19:56:09.2084654Z >>> def add_kernel( 2025-08-26T19:56:09.2084748Z >>> in_ptr0, 2025-08-26T19:56:09.2084839Z >>> in_ptr1, 2025-08-26T19:56:09.2084942Z >>> out_ptr, 2025-08-26T19:56:09.2085035Z >>> n_elements, 2025-08-26T19:56:09.2085165Z >>> BLOCK_SIZE: "tl.constexpr", 2025-08-26T19:56:09.2085248Z >>> ): 2025-08-26T19:56:09.2085367Z >>> pid = tl.program_id(axis=0) 2025-08-26T19:56:09.2085527Z >>> block_start = pid * BLOCK_SIZE 2025-08-26T19:56:09.2085680Z >>> offsets = block_start + tl.arange(0, BLOCK_SIZE) 2025-08-26T19:56:09.2085803Z >>> mask = offsets < n_elements 2025-08-26T19:56:09.2085935Z >>> x = tl.load(in_ptr0 + offsets, mask=mask) 2025-08-26T19:56:09.2086063Z >>> y = tl.load(in_ptr1 + offsets, mask=mask) 2025-08-26T19:56:09.2086174Z >>> output = x + y 2025-08-26T19:56:09.2086320Z >>> tl.store(out_ptr + offsets, output, mask=mask) 2025-08-26T19:56:09.2086438Z >>> 2025-08-26T19:56:09.2086537Z >>> def add(x, y): 2025-08-26T19:56:09.2086657Z >>> output = torch.empty_like(x) 2025-08-26T19:56:09.2086782Z >>> n_elements = output.numel() 2025-08-26T19:56:09.2086868Z >>> 2025-08-26T19:56:09.2086984Z >>> def grid_fn(meta): 2025-08-26T19:56:09.2087184Z >>> return (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),) 2025-08-26T19:56:09.2087273Z >>> 2025-08-26T19:56:09.2087482Z >>> wrap_triton(add_kernel)[grid_fn](x, y, output, n_elements, 16) 2025-08-26T19:56:09.2087584Z >>> return output 2025-08-26T19:56:09.2087677Z >>> 2025-08-26T19:56:09.2087796Z >>> x = torch.randn(3, device="cuda") 2025-08-26T19:56:09.2087910Z >>> y = torch.randn(3, device="cuda") 2025-08-26T19:56:09.2088029Z >>> gm = make_fx(add)(x, y) 2025-08-26T19:56:09.2088131Z >>> print(gm.code) 2025-08-26T19:56:09.2088245Z >>> # def forward(self, x_1, y_1): 2025-08-26T19:56:09.2088495Z >>> # empty_like = torch.ops.aten.empty_like.default(x_1, pin_memory = False) 2025-08-26T19:56:09.2088739Z >>> # triton_kernel_wrapper_mutation_proxy = triton_kernel_wrapper_mutation( 2025-08-26T19:56:09.2088988Z >>> # kernel_idx = 0, constant_args_idx = 0, 2025-08-26T19:56:09.2089112Z >>> # grid = [(1, 1, 1)], kwargs = { 2025-08-26T19:56:09.2089281Z >>> # 'in_ptr0': x_1, 'in_ptr1': y_1, 'out_ptr': empty_like, 2025-08-26T19:56:09.2089409Z >>> # 'n_elements': 3, 'BLOCK_SIZE': 16 2025-08-26T19:56:09.2089499Z >>> # }) 2025-08-26T19:56:09.2089616Z >>> # return empty_like 2025-08-26T19:56:09.2089699Z 2025-08-26T19:56:09.2089780Z 2025-08-26T19:56:09.2090050Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2090134Z 2025-08-26T19:56:09.2090244Z warnings.warn(msg) 2025-08-26T19:56:09.2090326Z 2025-08-26T19:56:09.2090534Z --- Parse Warning: 29 / 146 --- 2025-08-26T19:56:09.2091494Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=print_assert_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=286. 2025-08-26T19:56:09.2091806Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2091899Z 2025-08-26T19:56:09.2092122Z Test if two objects are equal, and print an error message if test fails. 2025-08-26T19:56:09.2092202Z 2025-08-26T19:56:09.2092364Z The test is performed with ``actual == desired``. 2025-08-26T19:56:09.2092445Z 2025-08-26T19:56:09.2092546Z Parameters 2025-08-26T19:56:09.2092635Z ---------- 2025-08-26T19:56:09.2092731Z test_string : str 2025-08-26T19:56:09.2092881Z The message supplied to AssertionError. 2025-08-26T19:56:09.2092973Z actual : object 2025-08-26T19:56:09.2093147Z The object to test for equality against `desired`. 2025-08-26T19:56:09.2093239Z desired : object 2025-08-26T19:56:09.2093340Z The expected result. 2025-08-26T19:56:09.2093434Z 2025-08-26T19:56:09.2093521Z Examples 2025-08-26T19:56:09.2093612Z -------- 2025-08-26T19:56:09.2093770Z >>> np.testing.print_assert_equal( 2025-08-26T19:56:09.2093889Z ... "Test XYZ of func xyz", [0, 1], [0, 1] 2025-08-26T19:56:09.2093999Z ... ) # doctest: +SKIP 2025-08-26T19:56:09.2094114Z >>> np.testing.print_assert_equal( 2025-08-26T19:56:09.2094233Z ... "Test XYZ of func xyz", [0, 1], [0, 2] 2025-08-26T19:56:09.2094342Z ... ) # doctest: +SKIP 2025-08-26T19:56:09.2094454Z Traceback (most recent call last): 2025-08-26T19:56:09.2094551Z ... 2025-08-26T19:56:09.2094678Z AssertionError: Test XYZ of func xyz failed 2025-08-26T19:56:09.2094788Z ACTUAL: 2025-08-26T19:56:09.2094885Z [0, 1] 2025-08-26T19:56:09.2094971Z DESIRED: 2025-08-26T19:56:09.2095065Z [0, 2] 2025-08-26T19:56:09.2095144Z 2025-08-26T19:56:09.2095225Z 2025-08-26T19:56:09.2095494Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2095574Z 2025-08-26T19:56:09.2095700Z warnings.warn(msg) 2025-08-26T19:56:09.2095794Z 2025-08-26T19:56:09.2095982Z --- Parse Warning: 30 / 146 --- 2025-08-26T19:56:09.2096940Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=331. 2025-08-26T19:56:09.2097206Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2097286Z 2025-08-26T19:56:09.2097507Z Raises an AssertionError if two items are not equal up to desired 2025-08-26T19:56:09.2097592Z precision. 2025-08-26T19:56:09.2097684Z 2025-08-26T19:56:09.2097868Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T19:56:09.2098052Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T19:56:09.2098266Z instead of this function for more consistent floating point 2025-08-26T19:56:09.2098362Z comparisons. 2025-08-26T19:56:09.2098455Z 2025-08-26T19:56:09.2098674Z The test verifies that the elements of `actual` and `desired` satisfy. 2025-08-26T19:56:09.2098756Z 2025-08-26T19:56:09.2098933Z ``abs(desired-actual) < float64(1.5 * 10**(-decimal))`` 2025-08-26T19:56:09.2099014Z 2025-08-26T19:56:09.2099259Z That is a looser test than originally documented, but agrees with what the 2025-08-26T19:56:09.2099499Z actual implementation in `assert_array_almost_equal` did up to rounding 2025-08-26T19:56:09.2099741Z vagaries. An exception is raised at conflicting values. For ndarrays this 2025-08-26T19:56:09.2099872Z delegates to assert_array_almost_equal 2025-08-26T19:56:09.2099951Z 2025-08-26T19:56:09.2100049Z Parameters 2025-08-26T19:56:09.2100136Z ---------- 2025-08-26T19:56:09.2100229Z actual : array_like 2025-08-26T19:56:09.2100340Z The object to check. 2025-08-26T19:56:09.2100442Z desired : array_like 2025-08-26T19:56:09.2100583Z The expected object. 2025-08-26T19:56:09.2100695Z decimal : int, optional 2025-08-26T19:56:09.2100812Z Desired precision, default is 7. 2025-08-26T19:56:09.2100921Z err_msg : str, optional 2025-08-26T19:56:09.2101080Z The error message to be printed in case of failure. 2025-08-26T19:56:09.2101179Z verbose : bool, optional 2025-08-26T19:56:09.2101402Z If True, the conflicting values are appended to the error message. 2025-08-26T19:56:09.2101482Z 2025-08-26T19:56:09.2101580Z Raises 2025-08-26T19:56:09.2101666Z ------ 2025-08-26T19:56:09.2101762Z AssertionError 2025-08-26T19:56:09.2101974Z If actual and desired are not equal up to specified precision. 2025-08-26T19:56:09.2102055Z 2025-08-26T19:56:09.2102152Z See Also 2025-08-26T19:56:09.2102238Z -------- 2025-08-26T19:56:09.2102480Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:56:09.2102625Z relative and/or absolute precision. 2025-08-26T19:56:09.2103265Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:56:09.2103362Z 2025-08-26T19:56:09.2103448Z Examples 2025-08-26T19:56:09.2103533Z -------- 2025-08-26T19:56:09.2103711Z >>> from torch._numpy.testing import assert_almost_equal 2025-08-26T19:56:09.2103848Z >>> assert_almost_equal(2.3333333333333, 2.33333334) 2025-08-26T19:56:09.2104025Z >>> assert_almost_equal(2.3333333333333, 2.33333334, decimal=10) 2025-08-26T19:56:09.2104155Z Traceback (most recent call last): 2025-08-26T19:56:09.2104270Z ... 2025-08-26T19:56:09.2104377Z AssertionError: 2025-08-26T19:56:09.2104501Z Arrays are not almost equal to 10 decimals 2025-08-26T19:56:09.2104595Z ACTUAL: 2.3333333333333 2025-08-26T19:56:09.2104700Z DESIRED: 2.33333334 2025-08-26T19:56:09.2104780Z 2025-08-26T19:56:09.2104891Z >>> assert_almost_equal( 2025-08-26T19:56:09.2105119Z ... np.array([1.0, 2.3333333333333]), np.array([1.0, 2.33333334]), decimal=9 2025-08-26T19:56:09.2105209Z ... ) 2025-08-26T19:56:09.2105336Z Traceback (most recent call last): 2025-08-26T19:56:09.2105418Z ... 2025-08-26T19:56:09.2105511Z AssertionError: 2025-08-26T19:56:09.2105646Z Arrays are not almost equal to 9 decimals 2025-08-26T19:56:09.2105733Z 2025-08-26T19:56:09.2105854Z Mismatched elements: 1 / 2 (50%) 2025-08-26T19:56:09.2105988Z Max absolute difference: 6.666699636781459e-09 2025-08-26T19:56:09.2106121Z Max relative difference: 2.8571569790287484e-09 2025-08-26T19:56:09.2106276Z x: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T19:56:09.2106417Z y: torch.ndarray([1.0000, 2.3333], dtype=float64) 2025-08-26T19:56:09.2106510Z 2025-08-26T19:56:09.2106591Z 2025-08-26T19:56:09.2106851Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2106944Z 2025-08-26T19:56:09.2107046Z warnings.warn(msg) 2025-08-26T19:56:09.2107135Z 2025-08-26T19:56:09.2107335Z --- Parse Warning: 31 / 146 --- 2025-08-26T19:56:09.2108288Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_approx_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=457. 2025-08-26T19:56:09.2108570Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2108652Z 2025-08-26T19:56:09.2108887Z Raises an AssertionError if two items are not equal up to significant 2025-08-26T19:56:09.2108971Z digits. 2025-08-26T19:56:09.2109053Z 2025-08-26T19:56:09.2109240Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T19:56:09.2109424Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T19:56:09.2109625Z instead of this function for more consistent floating point 2025-08-26T19:56:09.2109748Z comparisons. 2025-08-26T19:56:09.2109828Z 2025-08-26T19:56:09.2110023Z Given two numbers, check that they are approximately equal. 2025-08-26T19:56:09.2110248Z Approximately equal is defined as the number of significant digits 2025-08-26T19:56:09.2110344Z that agree. 2025-08-26T19:56:09.2110425Z 2025-08-26T19:56:09.2110513Z Parameters 2025-08-26T19:56:09.2110610Z ---------- 2025-08-26T19:56:09.2110701Z actual : scalar 2025-08-26T19:56:09.2110810Z The object to check. 2025-08-26T19:56:09.2110900Z desired : scalar 2025-08-26T19:56:09.2111002Z The expected object. 2025-08-26T19:56:09.2111113Z significant : int, optional 2025-08-26T19:56:09.2111230Z Desired precision, default is 7. 2025-08-26T19:56:09.2111330Z err_msg : str, optional 2025-08-26T19:56:09.2111496Z The error message to be printed in case of failure. 2025-08-26T19:56:09.2111594Z verbose : bool, optional 2025-08-26T19:56:09.2111814Z If True, the conflicting values are appended to the error message. 2025-08-26T19:56:09.2111924Z 2025-08-26T19:56:09.2112008Z Raises 2025-08-26T19:56:09.2112100Z ------ 2025-08-26T19:56:09.2112194Z AssertionError 2025-08-26T19:56:09.2112398Z If actual and desired are not equal up to specified precision. 2025-08-26T19:56:09.2112474Z 2025-08-26T19:56:09.2112556Z See Also 2025-08-26T19:56:09.2112651Z -------- 2025-08-26T19:56:09.2112892Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:56:09.2113055Z relative and/or absolute precision. 2025-08-26T19:56:09.2113267Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:56:09.2113347Z 2025-08-26T19:56:09.2113438Z Examples 2025-08-26T19:56:09.2113524Z -------- 2025-08-26T19:56:09.2113640Z >>> np.testing.assert_approx_equal( 2025-08-26T19:56:09.2113781Z ... 0.12345677777777e-20, 0.1234567e-20 2025-08-26T19:56:09.2113879Z ... ) # doctest: +SKIP 2025-08-26T19:56:09.2114007Z >>> np.testing.assert_approx_equal( 2025-08-26T19:56:09.2114095Z ... 0.12345670e-20, 2025-08-26T19:56:09.2114208Z ... 0.12345671e-20, # doctest: +SKIP 2025-08-26T19:56:09.2114313Z ... significant=8, 2025-08-26T19:56:09.2114393Z ... ) 2025-08-26T19:56:09.2114513Z >>> np.testing.assert_approx_equal( 2025-08-26T19:56:09.2114598Z ... 0.12345670e-20, 2025-08-26T19:56:09.2114707Z ... 0.12345672e-20, # doctest: +SKIP 2025-08-26T19:56:09.2114812Z ... significant=8, 2025-08-26T19:56:09.2114896Z ... ) 2025-08-26T19:56:09.2115007Z Traceback (most recent call last): 2025-08-26T19:56:09.2115094Z ... 2025-08-26T19:56:09.2115189Z AssertionError: 2025-08-26T19:56:09.2115329Z Items are not equal to 8 significant digits: 2025-08-26T19:56:09.2115421Z ACTUAL: 1.234567e-21 2025-08-26T19:56:09.2115517Z DESIRED: 1.2345672e-21 2025-08-26T19:56:09.2115612Z 2025-08-26T19:56:09.2115776Z the evaluated condition that raises the exception is 2025-08-26T19:56:09.2115866Z 2025-08-26T19:56:09.2116056Z >>> abs(0.12345670e-20 / 1e-21 - 0.12345672e-20 / 1e-21) >= 10 ** -(8 - 1) 2025-08-26T19:56:09.2116140Z True 2025-08-26T19:56:09.2116228Z 2025-08-26T19:56:09.2116306Z 2025-08-26T19:56:09.2116573Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2116652Z 2025-08-26T19:56:09.2116747Z warnings.warn(msg) 2025-08-26T19:56:09.2116836Z 2025-08-26T19:56:09.2117029Z --- Parse Warning: 32 / 146 --- 2025-08-26T19:56:09.2117975Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=744. 2025-08-26T19:56:09.2118250Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2118357Z 2025-08-26T19:56:09.2118579Z Raises an AssertionError if two array_like objects are not equal. 2025-08-26T19:56:09.2118657Z 2025-08-26T19:56:09.2118875Z Given two array_like objects, check that the shape is equal and all 2025-08-26T19:56:09.2119096Z elements of these objects are equal (but see the Notes for the special 2025-08-26T19:56:09.2119299Z handling of a scalar). An exception is raised at shape mismatch or 2025-08-26T19:56:09.2119536Z conflicting values. In contrast to the standard usage in numpy, NaNs 2025-08-26T19:56:09.2119759Z are compared like numbers, no assertion is raised if both objects have 2025-08-26T19:56:09.2119877Z NaNs in the same positions. 2025-08-26T19:56:09.2119958Z 2025-08-26T19:56:09.2120183Z The usual caution for verifying equality with floating point numbers is 2025-08-26T19:56:09.2120277Z advised. 2025-08-26T19:56:09.2120357Z 2025-08-26T19:56:09.2120445Z Parameters 2025-08-26T19:56:09.2120547Z ---------- 2025-08-26T19:56:09.2120633Z x : array_like 2025-08-26T19:56:09.2120779Z The actual object to check. 2025-08-26T19:56:09.2120868Z y : array_like 2025-08-26T19:56:09.2120977Z The desired, expected object. 2025-08-26T19:56:09.2121083Z err_msg : str, optional 2025-08-26T19:56:09.2121241Z The error message to be printed in case of failure. 2025-08-26T19:56:09.2121352Z verbose : bool, optional 2025-08-26T19:56:09.2121558Z If True, the conflicting values are appended to the error message. 2025-08-26T19:56:09.2121655Z strict : bool, optional 2025-08-26T19:56:09.2121888Z If True, raise an AssertionError when either the shape or the data 2025-08-26T19:56:09.2122066Z type of the array_like objects does not match. The special 2025-08-26T19:56:09.2122278Z handling for scalars mentioned in the Notes section is disabled. 2025-08-26T19:56:09.2122357Z 2025-08-26T19:56:09.2122437Z Raises 2025-08-26T19:56:09.2122559Z ------ 2025-08-26T19:56:09.2122649Z AssertionError 2025-08-26T19:56:09.2122787Z If actual and desired objects are not equal. 2025-08-26T19:56:09.2122874Z 2025-08-26T19:56:09.2122960Z See Also 2025-08-26T19:56:09.2123050Z -------- 2025-08-26T19:56:09.2123289Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:56:09.2123414Z relative and/or absolute precision. 2025-08-26T19:56:09.2123635Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:56:09.2123713Z 2025-08-26T19:56:09.2123804Z Notes 2025-08-26T19:56:09.2123890Z ----- 2025-08-26T19:56:09.2124073Z When one of `x` and `y` is a scalar and the other is array_like, the 2025-08-26T19:56:09.2124308Z function checks that each element of the array_like object is equal to 2025-08-26T19:56:09.2124535Z the scalar. This behaviour can be disabled with the `strict` parameter. 2025-08-26T19:56:09.2124623Z 2025-08-26T19:56:09.2124710Z Examples 2025-08-26T19:56:09.2124794Z -------- 2025-08-26T19:56:09.2124940Z The first assert does not raise an exception: 2025-08-26T19:56:09.2125020Z 2025-08-26T19:56:09.2125140Z >>> np.testing.assert_array_equal( 2025-08-26T19:56:09.2125282Z ... [1.0, 2.33333, np.nan], [np.exp(0), 2.33333, np.nan] 2025-08-26T19:56:09.2125362Z ... ) 2025-08-26T19:56:09.2125450Z 2025-08-26T19:56:09.2125680Z Use `assert_allclose` or one of the nulp (number of floating point values) 2025-08-26T19:56:09.2125787Z functions for these cases instead: 2025-08-26T19:56:09.2125880Z 2025-08-26T19:56:09.2125989Z >>> np.testing.assert_allclose( 2025-08-26T19:56:09.2126195Z ... [1.0, np.pi, np.nan], [1, np.sqrt(np.pi) ** 2, np.nan], rtol=1e-10, atol=0 2025-08-26T19:56:09.2126277Z ... ) 2025-08-26T19:56:09.2126354Z 2025-08-26T19:56:09.2126577Z As mentioned in the Notes section, `assert_array_equal` has special 2025-08-26T19:56:09.2126805Z handling for scalars. Here the test checks that each value in `x` is 3: 2025-08-26T19:56:09.2126925Z 2025-08-26T19:56:09.2127032Z >>> x = np.full((2, 5), fill_value=3) 2025-08-26T19:56:09.2127147Z >>> np.testing.assert_array_equal(x, 3) 2025-08-26T19:56:09.2127239Z 2025-08-26T19:56:09.2127453Z Use `strict` to raise an AssertionError when comparing a scalar with an 2025-08-26T19:56:09.2127549Z array: 2025-08-26T19:56:09.2127629Z 2025-08-26T19:56:09.2127775Z >>> np.testing.assert_array_equal(x, 3, strict=True) 2025-08-26T19:56:09.2127899Z Traceback (most recent call last): 2025-08-26T19:56:09.2127985Z ... 2025-08-26T19:56:09.2128075Z AssertionError: 2025-08-26T19:56:09.2128185Z Arrays are not equal 2025-08-26T19:56:09.2128271Z 2025-08-26T19:56:09.2128381Z (shapes (2, 5), () mismatch) 2025-08-26T19:56:09.2128487Z x: torch.ndarray([[3, 3, 3, 3, 3], 2025-08-26T19:56:09.2128576Z [3, 3, 3, 3, 3]]) 2025-08-26T19:56:09.2128689Z y: torch.ndarray(3) 2025-08-26T19:56:09.2128769Z 2025-08-26T19:56:09.2129113Z The `strict` parameter also ensures that the array data types match: 2025-08-26T19:56:09.2129194Z 2025-08-26T19:56:09.2129292Z >>> x = np.array([2, 2, 2]) 2025-08-26T19:56:09.2129438Z >>> y = np.array([2.0, 2.0, 2.0], dtype=np.float32) 2025-08-26T19:56:09.2129585Z >>> np.testing.assert_array_equal(x, y, strict=True) 2025-08-26T19:56:09.2129707Z Traceback (most recent call last): 2025-08-26T19:56:09.2129790Z ... 2025-08-26T19:56:09.2129881Z AssertionError: 2025-08-26T19:56:09.2129986Z Arrays are not equal 2025-08-26T19:56:09.2130094Z 2025-08-26T19:56:09.2130239Z (dtypes dtype("int64"), dtype("float32") mismatch) 2025-08-26T19:56:09.2130356Z x: torch.ndarray([2, 2, 2]) 2025-08-26T19:56:09.2130460Z y: torch.ndarray([2., 2., 2.]) 2025-08-26T19:56:09.2130556Z 2025-08-26T19:56:09.2130853Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2130939Z 2025-08-26T19:56:09.2131053Z warnings.warn(msg) 2025-08-26T19:56:09.2131133Z 2025-08-26T19:56:09.2131359Z --- Parse Warning: 33 / 146 --- 2025-08-26T19:56:09.2132338Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_array_almost_equal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=851. 2025-08-26T19:56:09.2132612Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2132710Z 2025-08-26T19:56:09.2132933Z Raises an AssertionError if two objects are not equal up to desired 2025-08-26T19:56:09.2133041Z precision. 2025-08-26T19:56:09.2133128Z 2025-08-26T19:56:09.2133308Z .. note:: It is recommended to use one of `assert_allclose`, 2025-08-26T19:56:09.2133510Z `assert_array_almost_equal_nulp` or `assert_array_max_ulp` 2025-08-26T19:56:09.2133707Z instead of this function for more consistent floating point 2025-08-26T19:56:09.2133821Z comparisons. 2025-08-26T19:56:09.2133903Z 2025-08-26T19:56:09.2134150Z The test verifies identical shapes and that the elements of ``actual`` and 2025-08-26T19:56:09.2134261Z ``desired`` satisfy. 2025-08-26T19:56:09.2134345Z 2025-08-26T19:56:09.2134495Z ``abs(desired-actual) < 1.5 * 10**(-decimal)`` 2025-08-26T19:56:09.2134578Z 2025-08-26T19:56:09.2134812Z That is a looser test than originally documented, but agrees with what the 2025-08-26T19:56:09.2135078Z actual implementation did up to rounding vagaries. An exception is raised 2025-08-26T19:56:09.2135318Z at shape mismatch or conflicting values. In contrast to the standard usage 2025-08-26T19:56:09.2135557Z in numpy, NaNs are compared like numbers, no assertion is raised if both 2025-08-26T19:56:09.2135687Z objects have NaNs in the same positions. 2025-08-26T19:56:09.2135772Z 2025-08-26T19:56:09.2135905Z Parameters 2025-08-26T19:56:09.2135997Z ---------- 2025-08-26T19:56:09.2136088Z x : array_like 2025-08-26T19:56:09.2136211Z The actual object to check. 2025-08-26T19:56:09.2136301Z y : array_like 2025-08-26T19:56:09.2136428Z The desired, expected object. 2025-08-26T19:56:09.2136530Z decimal : int, optional 2025-08-26T19:56:09.2136648Z Desired precision, default is 6. 2025-08-26T19:56:09.2136765Z err_msg : str, optional 2025-08-26T19:56:09.2136924Z The error message to be printed in case of failure. 2025-08-26T19:56:09.2137037Z verbose : bool, optional 2025-08-26T19:56:09.2137248Z If True, the conflicting values are appended to the error message. 2025-08-26T19:56:09.2137329Z 2025-08-26T19:56:09.2137593Z Raises 2025-08-26T19:56:09.2137682Z ------ 2025-08-26T19:56:09.2137793Z AssertionError 2025-08-26T19:56:09.2137995Z If actual and desired are not equal up to specified precision. 2025-08-26T19:56:09.2138084Z 2025-08-26T19:56:09.2138185Z See Also 2025-08-26T19:56:09.2138335Z -------- 2025-08-26T19:56:09.2138575Z assert_allclose: Compare two array_like objects for equality with desired 2025-08-26T19:56:09.2138723Z relative and/or absolute precision. 2025-08-26T19:56:09.2138936Z assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal 2025-08-26T19:56:09.2139031Z 2025-08-26T19:56:09.2139117Z Examples 2025-08-26T19:56:09.2139203Z -------- 2025-08-26T19:56:09.2139352Z the first assert does not raise an exception 2025-08-26T19:56:09.2139433Z 2025-08-26T19:56:09.2139740Z >>> np.testing.assert_array_almost_equal([1.0, 2.333, np.nan], [1.0, 2.333, np.nan]) 2025-08-26T19:56:09.2139823Z 2025-08-26T19:56:09.2139949Z >>> np.testing.assert_array_almost_equal( 2025-08-26T19:56:09.2140113Z ... [1.0, 2.33333, np.nan], [1.0, 2.33339, np.nan], decimal=5 2025-08-26T19:56:09.2140200Z ... ) 2025-08-26T19:56:09.2140361Z Traceback (most recent call last): 2025-08-26T19:56:09.2140449Z ... 2025-08-26T19:56:09.2140543Z AssertionError: 2025-08-26T19:56:09.2140677Z Arrays are not almost equal to 5 decimals 2025-08-26T19:56:09.2140766Z 2025-08-26T19:56:09.2140877Z Mismatched elements: 1 / 3 (33.3%) 2025-08-26T19:56:09.2141019Z Max absolute difference: 5.999999999994898e-05 2025-08-26T19:56:09.2141151Z Max relative difference: 2.5713661239633743e-05 2025-08-26T19:56:09.2141330Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T19:56:09.2141494Z y: torch.ndarray([1.0000, 2.3334, nan], dtype=float64) 2025-08-26T19:56:09.2141576Z 2025-08-26T19:56:09.2141715Z >>> np.testing.assert_array_almost_equal( 2025-08-26T19:56:09.2141853Z ... [1.0, 2.33333, np.nan], [1.0, 2.33333, 5], decimal=5 2025-08-26T19:56:09.2141951Z ... ) 2025-08-26T19:56:09.2142064Z Traceback (most recent call last): 2025-08-26T19:56:09.2142148Z ... 2025-08-26T19:56:09.2142262Z AssertionError: 2025-08-26T19:56:09.2142386Z Arrays are not almost equal to 5 decimals 2025-08-26T19:56:09.2142489Z 2025-08-26T19:56:09.2142600Z x and y nan location mismatch: 2025-08-26T19:56:09.2142764Z x: torch.ndarray([1.0000, 2.3333, nan], dtype=float64) 2025-08-26T19:56:09.2142934Z y: torch.ndarray([1.0000, 2.3333, 5.0000], dtype=float64) 2025-08-26T19:56:09.2143019Z 2025-08-26T19:56:09.2143112Z 2025-08-26T19:56:09.2143373Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2143454Z 2025-08-26T19:56:09.2143565Z warnings.warn(msg) 2025-08-26T19:56:09.2143644Z 2025-08-26T19:56:09.2143856Z --- Parse Warning: 34 / 146 --- 2025-08-26T19:56:09.2144844Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=clear_and_catch_warnings in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_numpy/testing/utils.py line=1848. 2025-08-26T19:56:09.2145168Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2145399Z Context manager that resets warning registry for catching warnings 2025-08-26T19:56:09.2145480Z 2025-08-26T19:56:09.2145739Z Warnings can be slippery, because, whenever a warning is triggered, Python 2025-08-26T19:56:09.2145969Z adds a ``__warningregistry__`` member to the *calling* module. This makes 2025-08-26T19:56:09.2146212Z it impossible to retrigger the warning in this module, whatever you put in 2025-08-26T19:56:09.2146476Z the warnings filters. This context manager accepts a sequence of `modules` 2025-08-26T19:56:09.2146619Z as a keyword argument to its constructor and: 2025-08-26T19:56:09.2146716Z 2025-08-26T19:56:09.2146949Z * stores and removes any ``__warningregistry__`` entries in given `modules` 2025-08-26T19:56:09.2147039Z on entry; 2025-08-26T19:56:09.2147248Z * resets ``__warningregistry__`` to its previous state on exit. 2025-08-26T19:56:09.2147392Z 2025-08-26T19:56:09.2147633Z This makes it possible to trigger any warning afresh inside the context 2025-08-26T19:56:09.2147822Z manager without disturbing the state of warnings outside. 2025-08-26T19:56:09.2147905Z 2025-08-26T19:56:09.2148157Z For compatibility with Python 3.0, please consider all arguments to be 2025-08-26T19:56:09.2148252Z keyword-only. 2025-08-26T19:56:09.2148350Z 2025-08-26T19:56:09.2148443Z Parameters 2025-08-26T19:56:09.2148536Z ---------- 2025-08-26T19:56:09.2148682Z record : bool, optional 2025-08-26T19:56:09.2148877Z Specifies whether warnings should be captured by a custom 2025-08-26T19:56:09.2149119Z implementation of ``warnings.showwarning()`` and be appended to a list 2025-08-26T19:56:09.2149346Z returned by the context manager. Otherwise None is returned by the 2025-08-26T19:56:09.2149609Z context manager. The objects appended to the list are arguments whose 2025-08-26T19:56:09.2149801Z attributes mirror the arguments to ``showwarning()``. 2025-08-26T19:56:09.2149911Z modules : sequence, optional 2025-08-26T19:56:09.2150148Z Sequence of modules for which to reset warnings registry on entry and 2025-08-26T19:56:09.2150343Z restore on exit. To work correctly, all 'ignore' filters should 2025-08-26T19:56:09.2150457Z filter by one of these modules. 2025-08-26T19:56:09.2150550Z 2025-08-26T19:56:09.2150636Z Examples 2025-08-26T19:56:09.2150725Z -------- 2025-08-26T19:56:09.2150834Z >>> import warnings 2025-08-26T19:56:09.2151021Z >>> with np.testing.clear_and_catch_warnings( # doctest: +SKIP 2025-08-26T19:56:09.2151154Z ... modules=[np.core.fromnumeric] 2025-08-26T19:56:09.2151237Z ... ): 2025-08-26T19:56:09.2151364Z ... warnings.simplefilter("always") 2025-08-26T19:56:09.2151604Z ... warnings.filterwarnings("ignore", module="np.core.fromnumeric") 2025-08-26T19:56:09.2151779Z ... # do something that raises a warning but ignore those in 2025-08-26T19:56:09.2151899Z ... # np.core.fromnumeric 2025-08-26T19:56:09.2151982Z 2025-08-26T19:56:09.2152239Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2152332Z 2025-08-26T19:56:09.2152430Z warnings.warn(msg) 2025-08-26T19:56:09.2152523Z 2025-08-26T19:56:09.2152719Z --- Parse Warning: 35 / 146 --- 2025-08-26T19:56:09.2153663Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Conv1d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/conv.py line=354. 2025-08-26T19:56:09.2153944Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2154192Z Applies a 1D convolution over a quantized input signal composed of 2025-08-26T19:56:09.2154326Z several quantized input planes. 2025-08-26T19:56:09.2154408Z 2025-08-26T19:56:09.2154622Z For details on input arguments, parameters, and implementation see 2025-08-26T19:56:09.2154740Z :class:`~torch.nn.Conv1d`. 2025-08-26T19:56:09.2154821Z 2025-08-26T19:56:09.2154924Z .. note:: 2025-08-26T19:56:09.2155124Z Only `zeros` is supported for the :attr:`padding_mode` argument. 2025-08-26T19:56:09.2155205Z 2025-08-26T19:56:09.2155303Z .. note:: 2025-08-26T19:56:09.2155481Z Only `torch.quint8` is supported for the input data type. 2025-08-26T19:56:09.2155573Z 2025-08-26T19:56:09.2155654Z 2025-08-26T19:56:09.2155745Z Attributes: 2025-08-26T19:56:09.2155970Z weight (Tensor): packed tensor derived from the learnable weight 2025-08-26T19:56:09.2156080Z parameter. 2025-08-26T19:56:09.2156244Z scale (Tensor): scalar for the output scale 2025-08-26T19:56:09.2156440Z zero_point (Tensor): scalar for the output zero point 2025-08-26T19:56:09.2156520Z 2025-08-26T19:56:09.2156689Z See :class:`~torch.nn.Conv1d` for other attributes. 2025-08-26T19:56:09.2156770Z 2025-08-26T19:56:09.2156863Z Examples:: 2025-08-26T19:56:09.2156956Z 2025-08-26T19:56:09.2157107Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_QENGINE) 2025-08-26T19:56:09.2157254Z >>> m = nn.quantized.Conv1d(16, 33, 3, stride=2) 2025-08-26T19:56:09.2157399Z >>> input = torch.randn(20, 16, 100) 2025-08-26T19:56:09.2157511Z >>> # quantize input to quint8 2025-08-26T19:56:09.2157625Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2157847Z >>> q_input = torch.quantize_per_tensor(input, scale=1.0, zero_point=0, 2025-08-26T19:56:09.2158020Z ... dtype=torch.quint8) 2025-08-26T19:56:09.2158125Z >>> output = m(q_input) 2025-08-26T19:56:09.2158211Z 2025-08-26T19:56:09.2158312Z 2025-08-26T19:56:09.2158569Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2158665Z 2025-08-26T19:56:09.2158764Z warnings.warn(msg) 2025-08-26T19:56:09.2158847Z 2025-08-26T19:56:09.2159050Z --- Parse Warning: 36 / 146 --- 2025-08-26T19:56:09.2159967Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LSTM in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/nn/quantized/modules/rnn.py line=12. 2025-08-26T19:56:09.2160246Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2160376Z A quantized long short-term memory (LSTM). 2025-08-26T19:56:09.2160458Z 2025-08-26T19:56:09.2160756Z For the description and the argument types, please, refer to :class:`~torch.nn.LSTM` 2025-08-26T19:56:09.2160842Z 2025-08-26T19:56:09.2160944Z Attributes: 2025-08-26T19:56:09.2161072Z layers : instances of the `_LSTMLayer` 2025-08-26T19:56:09.2161155Z 2025-08-26T19:56:09.2161255Z .. note:: 2025-08-26T19:56:09.2161472Z To access the weights and biases, you need to access them per layer. 2025-08-26T19:56:09.2161661Z See examples in :class:`~torch.ao.nn.quantizable.LSTM` 2025-08-26T19:56:09.2161749Z 2025-08-26T19:56:09.2161839Z Examples:: 2025-08-26T19:56:09.2161953Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2162067Z >>> custom_module_config = { 2025-08-26T19:56:09.2162217Z ... 'float_to_observed_custom_module_class': { 2025-08-26T19:56:09.2162348Z ... nn.LSTM: nn.quantizable.LSTM, 2025-08-26T19:56:09.2162434Z ... }, 2025-08-26T19:56:09.2162601Z ... 'observed_to_quantized_custom_module_class': { 2025-08-26T19:56:09.2162779Z ... nn.quantizable.LSTM: nn.quantized.LSTM, 2025-08-26T19:56:09.2162868Z ... } 2025-08-26T19:56:09.2162965Z ... } 2025-08-26T19:56:09.2163190Z >>> tq.prepare(model, prepare_custom_module_class=custom_module_config) 2025-08-26T19:56:09.2163420Z >>> tq.convert(model, convert_custom_module_class=custom_module_config) 2025-08-26T19:56:09.2163505Z 2025-08-26T19:56:09.2163764Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2163856Z 2025-08-26T19:56:09.2163958Z warnings.warn(msg) 2025-08-26T19:56:09.2164048Z 2025-08-26T19:56:09.2164239Z --- Parse Warning: 37 / 146 --- 2025-08-26T19:56:09.2165458Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ActivationSparsifier in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/activation_sparsifier/activation_sparsifier.py line=16. 2025-08-26T19:56:09.2165774Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2165858Z 2025-08-26T19:56:09.2166139Z The Activation sparsifier class aims to sparsify/prune activations in a neural 2025-08-26T19:56:09.2166371Z network. The idea is to attach the sparsifier to a layer (or layers) and it 2025-08-26T19:56:09.2166631Z zeroes out the activations based on the mask_fn (or sparsification function) 2025-08-26T19:56:09.2166727Z input by the user. 2025-08-26T19:56:09.2166994Z The mask_fn is applied once all the inputs are aggregated and reduced i.e. 2025-08-26T19:56:09.2167167Z mask = mask_fn(reduce_fn(aggregate_fn(activations))) 2025-08-26T19:56:09.2167249Z 2025-08-26T19:56:09.2167351Z Note:: 2025-08-26T19:56:09.2167679Z The sparsification mask is computed on the input **before it goes through the attached layer**. 2025-08-26T19:56:09.2167762Z 2025-08-26T19:56:09.2167890Z Args: 2025-08-26T19:56:09.2167994Z model (nn.Module): 2025-08-26T19:56:09.2168221Z The model whose layers will be sparsified. The layers that needs to be 2025-08-26T19:56:09.2168477Z sparsified should be added separately using the register_layer() function 2025-08-26T19:56:09.2168598Z aggregate_fn (Optional, Callable): 2025-08-26T19:56:09.2168951Z default aggregate_fn that is used if not specified while registering the layer. 2025-08-26T19:56:09.2169126Z specifies how inputs should be aggregated over time. 2025-08-26T19:56:09.2169437Z The aggregate_fn should usually take 2 torch tensors and return the aggregated tensor. 2025-08-26T19:56:09.2169523Z Example 2025-08-26T19:56:09.2169700Z def add_agg_fn(tensor1, tensor2): return tensor1 + tensor2 2025-08-26T19:56:09.2169830Z reduce_fn (Optional, Callable): 2025-08-26T19:56:09.2170081Z default reduce_fn that is used if not specified while registering the layer. 2025-08-26T19:56:09.2170355Z reduce_fn will be called on the aggregated tensor i.e. the tensor obtained after 2025-08-26T19:56:09.2170474Z calling agg_fn() on all inputs. 2025-08-26T19:56:09.2170564Z Example 2025-08-26T19:56:09.2170776Z def mean_reduce_fn(agg_tensor): return agg_tensor.mean(dim=0) 2025-08-26T19:56:09.2170893Z mask_fn (Optional, Callable): 2025-08-26T19:56:09.2171221Z default mask_fn that is used to create the sparsification mask using the tensor obtained after 2025-08-26T19:56:09.2171477Z calling the reduce_fn(). This is used by default if a custom one is passed in the 2025-08-26T19:56:09.2171579Z register_layer(). 2025-08-26T19:56:09.2171941Z Note that the mask_fn() definition should contain the sparse arguments that is passed in sparse_config 2025-08-26T19:56:09.2172079Z arguments. 2025-08-26T19:56:09.2172205Z features (Optional, list): 2025-08-26T19:56:09.2172343Z default selected features to sparsify. 2025-08-26T19:56:09.2172611Z If this is non-empty, then the mask_fn will be applied for each feature of the input. 2025-08-26T19:56:09.2172716Z For example, 2025-08-26T19:56:09.2172972Z mask = [mask_fn(reduce_fn(aggregated_fn(input[feature])) for feature in features] 2025-08-26T19:56:09.2173101Z feature_dim (Optional, int): 2025-08-26T19:56:09.2173383Z default dimension of input features. Again, features along this dim will be chosen 2025-08-26T19:56:09.2173492Z for sparsification. 2025-08-26T19:56:09.2173611Z sparse_config (Dict): 2025-08-26T19:56:09.2173832Z Default configuration for the mask_fn. This config will be passed 2025-08-26T19:56:09.2173952Z with the mask_fn() 2025-08-26T19:56:09.2174060Z 2025-08-26T19:56:09.2174145Z Example: 2025-08-26T19:56:09.2174254Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2174354Z >>> model = SomeModel() 2025-08-26T19:56:09.2174616Z >>> act_sparsifier = ActivationSparsifier(...) # init activation sparsifier 2025-08-26T19:56:09.2174729Z >>> # Initialize aggregate_fn 2025-08-26T19:56:09.2174826Z >>> def agg_fn(x, y): 2025-08-26T19:56:09.2174932Z >>> return x + y 2025-08-26T19:56:09.2175012Z >>> 2025-08-26T19:56:09.2175126Z >>> # Initialize reduce_fn 2025-08-26T19:56:09.2175246Z >>> def reduce_fn(x): 2025-08-26T19:56:09.2175359Z >>> return torch.mean(x, dim=0) 2025-08-26T19:56:09.2175455Z >>> 2025-08-26T19:56:09.2175558Z >>> # Initialize mask_fn 2025-08-26T19:56:09.2175656Z >>> def mask_fn(data): 2025-08-26T19:56:09.2175813Z >>> return torch.eye(data.shape).to(data.device) 2025-08-26T19:56:09.2175921Z >>> 2025-08-26T19:56:09.2176017Z >>> 2025-08-26T19:56:09.2176133Z >>> act_sparsifier.register_layer( 2025-08-26T19:56:09.2176232Z ... model.some_layer, 2025-08-26T19:56:09.2176345Z ... aggregate_fn=agg_fn, 2025-08-26T19:56:09.2176443Z ... reduce_fn=reduce_fn, 2025-08-26T19:56:09.2176550Z ... mask_fn=mask_fn, 2025-08-26T19:56:09.2176635Z ... ) 2025-08-26T19:56:09.2176717Z >>> 2025-08-26T19:56:09.2176832Z >>> # start training process 2025-08-26T19:56:09.2176924Z >>> for _ in [...]: 2025-08-26T19:56:09.2177033Z >>> # epoch starts 2025-08-26T19:56:09.2177211Z >>> # model.forward(), compute_loss() and model.backwards() 2025-08-26T19:56:09.2177306Z >>> # epoch ends 2025-08-26T19:56:09.2177429Z >>> act_sparsifier.step() 2025-08-26T19:56:09.2177529Z >>> # end training process 2025-08-26T19:56:09.2177635Z >>> sparsifier.squash_mask() 2025-08-26T19:56:09.2177731Z 2025-08-26T19:56:09.2177988Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2178079Z 2025-08-26T19:56:09.2178177Z warnings.warn(msg) 2025-08-26T19:56:09.2178257Z 2025-08-26T19:56:09.2178479Z --- Parse Warning: 38 / 146 --- 2025-08-26T19:56:09.2179714Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseDataScheduler.get_schedule_param in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/_experimental/data_scheduler/base_data_scheduler.py line=91. 2025-08-26T19:56:09.2179996Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2180079Z 2025-08-26T19:56:09.2180302Z Abstract method that needs to be implemented by the child class. 2025-08-26T19:56:09.2180563Z The expected return type should is a dictionary of name to schedule_param value 2025-08-26T19:56:09.2180868Z The returned values will be updated in sparsifier when the scheduler step() function 2025-08-26T19:56:09.2180974Z is called. 2025-08-26T19:56:09.2181054Z 2025-08-26T19:56:09.2181137Z Example: 2025-08-26T19:56:09.2181262Z >>> def get_schedule_param(self): 2025-08-26T19:56:09.2181360Z ... new_param = {} 2025-08-26T19:56:09.2181529Z ... for name in self.sparsifier.data_groups.keys(): 2025-08-26T19:56:09.2181631Z ... new_param[name] = ( 2025-08-26T19:56:09.2181842Z ... self.sparsifier.data_groups[name][self.schedule_param] * 0.5 2025-08-26T19:56:09.2181942Z ... ) 2025-08-26T19:56:09.2182043Z ... return new_param 2025-08-26T19:56:09.2182138Z 2025-08-26T19:56:09.2182486Z When the step() function is called, the value in self.sparsifier.data_groups[name][self.schedule_param] 2025-08-26T19:56:09.2182576Z would be halved 2025-08-26T19:56:09.2182665Z 2025-08-26T19:56:09.2182923Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2183043Z 2025-08-26T19:56:09.2183140Z warnings.warn(msg) 2025-08-26T19:56:09.2183221Z 2025-08-26T19:56:09.2183422Z --- Parse Warning: 39 / 146 --- 2025-08-26T19:56:09.2184513Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BaseSparsifier.squash_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/pruning/sparsifier/base_sparsifier.py line=229. 2025-08-26T19:56:09.2184814Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2184989Z Squashes the sparse masks into the appropriate tensors. 2025-08-26T19:56:09.2185069Z 2025-08-26T19:56:09.2185290Z If either the `params_to_keep` or `params_to_keep_per_layer` is set, 2025-08-26T19:56:09.2185506Z the module will have a `sparse_params` dict attached to it. 2025-08-26T19:56:09.2185601Z 2025-08-26T19:56:09.2185687Z Args: 2025-08-26T19:56:09.2185874Z params_to_keep: List of keys to save in the module or a dict 2025-08-26T19:56:09.2186041Z representing the modules and keys that will have 2025-08-26T19:56:09.2186168Z sparsity parameters saved 2025-08-26T19:56:09.2186398Z params_to_keep_per_layer: Dict to specify the params that should be 2025-08-26T19:56:09.2186553Z saved for specific layers. The keys in the dict 2025-08-26T19:56:09.2186713Z should be the module fqn, while the values should 2025-08-26T19:56:09.2186882Z be a list of strings with the names of the variables 2025-08-26T19:56:09.2187008Z to save in the `sparse_params` 2025-08-26T19:56:09.2187101Z 2025-08-26T19:56:09.2187190Z Examples: 2025-08-26T19:56:09.2187328Z >>> # xdoctest: +SKIP("locals are undefined") 2025-08-26T19:56:09.2187458Z >>> # Don't save any sparse params 2025-08-26T19:56:09.2187575Z >>> sparsifier.squash_mask() 2025-08-26T19:56:09.2187727Z >>> hasattr(model.submodule1, "sparse_params") 2025-08-26T19:56:09.2187811Z False 2025-08-26T19:56:09.2187890Z 2025-08-26T19:56:09.2188021Z >>> # Keep sparse params per layer 2025-08-26T19:56:09.2188137Z >>> sparsifier.squash_mask( 2025-08-26T19:56:09.2188265Z ... params_to_keep_per_layer={ 2025-08-26T19:56:09.2188400Z ... "submodule1.linear1": ("foo", "bar"), 2025-08-26T19:56:09.2188532Z ... "submodule2.linear42": ("baz",), 2025-08-26T19:56:09.2188629Z ... } 2025-08-26T19:56:09.2188710Z ... ) 2025-08-26T19:56:09.2188882Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T19:56:09.2189014Z {'foo': 42, 'bar': 24} 2025-08-26T19:56:09.2189176Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T19:56:09.2189287Z {'baz': 0.1} 2025-08-26T19:56:09.2189367Z 2025-08-26T19:56:09.2189505Z >>> # Keep sparse params for all layers 2025-08-26T19:56:09.2189683Z >>> sparsifier.squash_mask(params_to_keep=("foo", "bar")) 2025-08-26T19:56:09.2189839Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T19:56:09.2189953Z {'foo': 42, 'bar': 24} 2025-08-26T19:56:09.2190110Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T19:56:09.2190219Z {'foo': 42, 'bar': 24} 2025-08-26T19:56:09.2190299Z 2025-08-26T19:56:09.2190499Z >>> # Keep some sparse params for all layers, and specific ones for 2025-08-26T19:56:09.2190611Z >>> # some other layers 2025-08-26T19:56:09.2190729Z >>> sparsifier.squash_mask( 2025-08-26T19:56:09.2190889Z ... params_to_keep=("foo", "bar"), 2025-08-26T19:56:09.2191085Z ... params_to_keep_per_layer={"submodule2.linear42": ("baz",)}, 2025-08-26T19:56:09.2191171Z ... ) 2025-08-26T19:56:09.2191338Z >>> print(model.submodule1.linear1.sparse_params) 2025-08-26T19:56:09.2191437Z {'foo': 42, 'bar': 24} 2025-08-26T19:56:09.2191605Z >>> print(model.submodule2.linear42.sparse_params) 2025-08-26T19:56:09.2191716Z {'foo': 42, 'bar': 24, 'baz': 0.1} 2025-08-26T19:56:09.2191824Z 2025-08-26T19:56:09.2192097Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2192179Z 2025-08-26T19:56:09.2192277Z warnings.warn(msg) 2025-08-26T19:56:09.2192370Z 2025-08-26T19:56:09.2192560Z --- Parse Warning: 40 / 146 --- 2025-08-26T19:56:09.2193663Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DTypeConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/backend_config/backend_config.py line=181. 2025-08-26T19:56:09.2193937Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2194031Z 2025-08-26T19:56:09.2194290Z Config object that specifies the supported data types passed as arguments to 2025-08-26T19:56:09.2194534Z quantize ops in the reference model spec, for input and output activations, 2025-08-26T19:56:09.2194644Z weights, and biases. 2025-08-26T19:56:09.2194726Z 2025-08-26T19:56:09.2194901Z For example, consider the following reference model: 2025-08-26T19:56:09.2194983Z 2025-08-26T19:56:09.2195147Z quant1 - [dequant1 - fp32_linear - quant2] - dequant2 2025-08-26T19:56:09.2195242Z 2025-08-26T19:56:09.2195463Z The pattern in the square brackets refers to the reference pattern of 2025-08-26T19:56:09.2195706Z statically quantized linear. Setting the input dtype as `torch.quint8` 2025-08-26T19:56:09.2195952Z in the DTypeConfig means we pass in `torch.quint8` as the dtype argument 2025-08-26T19:56:09.2196181Z to the first quantize op (quant1). Similarly, setting the output dtype as 2025-08-26T19:56:09.2196417Z `torch.quint8` means we pass in `torch.quint8` as the dtype argument to 2025-08-26T19:56:09.2196530Z the second quantize op (quant2). 2025-08-26T19:56:09.2196612Z 2025-08-26T19:56:09.2196845Z Note that the dtype here does not refer to the interface dtypes of the 2025-08-26T19:56:09.2197060Z op. For example, the "input dtype" here is not the dtype of the input 2025-08-26T19:56:09.2197290Z tensor passed to the quantized linear op. Though it can still be the 2025-08-26T19:56:09.2197493Z same as the interface dtype, this is not always the case, e.g. the 2025-08-26T19:56:09.2197728Z interface dtype is fp32 in dynamic quantization but the "input dtype" 2025-08-26T19:56:09.2197973Z specified in the DTypeConfig would still be quint8. The semantics of 2025-08-26T19:56:09.2198186Z dtypes here are the same as the semantics of the dtypes specified in 2025-08-26T19:56:09.2198289Z the observers. 2025-08-26T19:56:09.2198369Z 2025-08-26T19:56:09.2198576Z These dtypes are matched against the ones specified in the user's 2025-08-26T19:56:09.2198801Z QConfig. If there is a match, and the QConfig satisfies the constraints 2025-08-26T19:56:09.2199023Z specified in the DTypeConfig (if any), then we will quantize the given 2025-08-26T19:56:09.2199259Z pattern using this DTypeConfig. Otherwise, the QConfig is ignored and 2025-08-26T19:56:09.2199372Z the pattern will not be quantized. 2025-08-26T19:56:09.2199465Z 2025-08-26T19:56:09.2199562Z Example usage:: 2025-08-26T19:56:09.2199646Z 2025-08-26T19:56:09.2199760Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:56:09.2199873Z >>> dtype_config1 = DTypeConfig( 2025-08-26T19:56:09.2199988Z ... input_dtype=torch.quint8, 2025-08-26T19:56:09.2200146Z ... output_dtype=torch.quint8, 2025-08-26T19:56:09.2200256Z ... weight_dtype=torch.qint8, 2025-08-26T19:56:09.2200370Z ... bias_dtype=torch.float) 2025-08-26T19:56:09.2200448Z 2025-08-26T19:56:09.2200560Z >>> dtype_config2 = DTypeConfig( 2025-08-26T19:56:09.2200698Z ... input_dtype=DTypeWithConstraints( 2025-08-26T19:56:09.2200798Z ... dtype=torch.quint8, 2025-08-26T19:56:09.2200918Z ... quant_min_lower_bound=0, 2025-08-26T19:56:09.2201055Z ... quant_max_upper_bound=255, 2025-08-26T19:56:09.2201140Z ... ), 2025-08-26T19:56:09.2201282Z ... output_dtype=DTypeWithConstraints( 2025-08-26T19:56:09.2201383Z ... dtype=torch.quint8, 2025-08-26T19:56:09.2201504Z ... quant_min_lower_bound=0, 2025-08-26T19:56:09.2201641Z ... quant_max_upper_bound=255, 2025-08-26T19:56:09.2201728Z ... ), 2025-08-26T19:56:09.2201867Z ... weight_dtype=DTypeWithConstraints( 2025-08-26T19:56:09.2201968Z ... dtype=torch.qint8, 2025-08-26T19:56:09.2202085Z ... quant_min_lower_bound=-128, 2025-08-26T19:56:09.2202207Z ... quant_max_upper_bound=127, 2025-08-26T19:56:09.2202291Z ... ), 2025-08-26T19:56:09.2202408Z ... bias_dtype=torch.float) 2025-08-26T19:56:09.2202488Z 2025-08-26T19:56:09.2202598Z >>> dtype_config1.input_dtype 2025-08-26T19:56:09.2202696Z torch.quint8 2025-08-26T19:56:09.2202779Z 2025-08-26T19:56:09.2202900Z >>> dtype_config2.input_dtype 2025-08-26T19:56:09.2202987Z torch.quint8 2025-08-26T19:56:09.2203067Z 2025-08-26T19:56:09.2203221Z >>> dtype_config2.input_dtype_with_constraints 2025-08-26T19:56:09.2203775Z DTypeWithConstraints(dtype=torch.quint8, quant_min_lower_bound=0, quant_max_upper_bound=255, scale_min_lower_bound=None, scale_max_upper_bound=None) 2025-08-26T19:56:09.2203874Z 2025-08-26T19:56:09.2204131Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2204213Z 2025-08-26T19:56:09.2204326Z warnings.warn(msg) 2025-08-26T19:56:09.2204412Z 2025-08-26T19:56:09.2204622Z --- Parse Warning: 41 / 146 --- 2025-08-26T19:56:09.2205678Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReport in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report.py line=24. 2025-08-26T19:56:09.2205946Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2206038Z 2025-08-26T19:56:09.2206350Z The ModelReport class aims to provide users an easy way to diagnose issues that they run into 2025-08-26T19:56:09.2206667Z with their models. The class works with all traceable GraphModules to help diagnose issues, 2025-08-26T19:56:09.2207008Z though the requirements on the type of model more-so depends on the specific report the user 2025-08-26T19:56:09.2207310Z is trying to generate. With respect to the reports, the ModelReport class is initialized with 2025-08-26T19:56:09.2207601Z a set of Detector classes, each of which generate reports on quantization configuration 2025-08-26T19:56:09.2207704Z issues a use might have. 2025-08-26T19:56:09.2207796Z 2025-08-26T19:56:09.2207931Z Currently supports generating reports on: 2025-08-26T19:56:09.2208164Z - Suggestions for per-channel vs. per-tensor quantization (nn.Module) 2025-08-26T19:56:09.2208449Z - Suggestions for dynamic vs static quantization for linear layers (Graph Modules) 2025-08-26T19:56:09.2208745Z - Suggestions for input-weight equalization for linear and conv layers (Graph Modules) 2025-08-26T19:56:09.2209066Z - Suggestions for outlier detection for all layers (Graph Modules) 2025-08-26T19:56:09.2209189Z 2025-08-26T19:56:09.2209599Z The ModelReport class has the primary functionality of inserting observers (primarily the ModelReportObserver) 2025-08-26T19:56:09.2209999Z where needed for each detector to gather the information it needs, and then after calibration, the ModelReport 2025-08-26T19:56:09.2210381Z class compiles the report generated by each Detector class into a single report to return to the user. It also 2025-08-26T19:56:09.2210611Z has the capability to remove all the observers it inserted as well. 2025-08-26T19:56:09.2210695Z 2025-08-26T19:56:09.2211028Z * :attr:`_model` The model we wish to generate the report for. Must be a traceable GraphModule 2025-08-26T19:56:09.2211113Z 2025-08-26T19:56:09.2211499Z * :attr:`_desired_report_detectors` The set of Detectors representing desired reports from the ModelReport class 2025-08-26T19:56:09.2211872Z Make sure that these are all unique types of detectors [do not have more than 1 of the same class] 2025-08-26T19:56:09.2211958Z 2025-08-26T19:56:09.2212263Z * :attr:`_desired_detector_names` The set of detector names of the _desired_report_detectors. 2025-08-26T19:56:09.2212492Z This set is generated by calling the get_detector_name() of each detector 2025-08-26T19:56:09.2212571Z 2025-08-26T19:56:09.2212922Z * :attr:`_detector_name_to_observer_fqns` The mapping from each detector to fqns of observers of interest 2025-08-26T19:56:09.2213245Z The purpose of this is to keep track of what observers were inserted for each detector, so that they 2025-08-26T19:56:09.2213377Z can be removed at the end if desired 2025-08-26T19:56:09.2213456Z 2025-08-26T19:56:09.2213778Z * :attr:`_prepared_flag` A boolean flag that keeps track of whether we have prepared the model or not 2025-08-26T19:56:09.2214026Z This is to ensure we only insert observers once with the ModelReport instance 2025-08-26T19:56:09.2214112Z 2025-08-26T19:56:09.2214386Z * :attr:`_removed_observers` A boolean to track if we have removed observers already 2025-08-26T19:56:09.2214683Z The purpose is to ensure we don't attempt to remove observers twice with the same ModelReport 2025-08-26T19:56:09.2215008Z instance. This also allows the functionality where we can generate the report multiple times 2025-08-26T19:56:09.2215167Z as long as we haven't removed the observers yet. 2025-08-26T19:56:09.2215248Z 2025-08-26T19:56:09.2215346Z Note: 2025-08-26T19:56:09.2215648Z This class was initially designed to work with the Fx Graph Mode workflow in mind. However, 2025-08-26T19:56:09.2215966Z full functionality is available as long as there is a traceable GraphModule that is being used. 2025-08-26T19:56:09.2216274Z One method to get a traceable GraphModule without going through the Fx workflow is to use 2025-08-26T19:56:09.2216392Z the QuantizationTracer class. 2025-08-26T19:56:09.2216516Z 2025-08-26T19:56:09.2216620Z General Flow for Fx workflow: 2025-08-26T19:56:09.2217022Z 1.) Initialize ModelReport object with reports of interest by passing in initialized detector objects and model 2025-08-26T19:56:09.2217151Z 2.) Prepare your model with prepare_fx 2025-08-26T19:56:09.2217400Z 3.) Call model_report.prepare_detailed_calibration to add relevant observers 2025-08-26T19:56:09.2217522Z 4.) Calibrate your model with data 2025-08-26T19:56:09.2217887Z 5.) Call model_report.generate_report on your model to generate report and optionally remove added observers 2025-08-26T19:56:09.2217974Z Optional 2025-08-26T19:56:09.2218259Z 6.) Call model_report.generate_visualizer to get a ModelReportVisualizer instance 2025-08-26T19:56:09.2218508Z 7.) To help in parsing report information and debugging, view report info as a: 2025-08-26T19:56:09.2218605Z - Table 2025-08-26T19:56:09.2218697Z - Histogram 2025-08-26T19:56:09.2218793Z - Line plot 2025-08-26T19:56:09.2219127Z 8.) Call model_report.generate_qconfigs to generate the qconfigs based on the report suggestions 2025-08-26T19:56:09.2219264Z 2025-08-26T19:56:09.2219395Z Example (with QuantizationTracer): 2025-08-26T19:56:09.2219491Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2219599Z >>> # get the necessary qconfig 2025-08-26T19:56:09.2219729Z >>> config = PrepareCustomConfig() 2025-08-26T19:56:09.2219886Z >>> skipped_module_names, skipped_module_classes = ( 2025-08-26T19:56:09.2220063Z ... get_skipped_module_name_and_classes(config, False) 2025-08-26T19:56:09.2220170Z ... ) 2025-08-26T19:56:09.2220256Z 2025-08-26T19:56:09.2220401Z >>> # initialize our model and get GraphModule 2025-08-26T19:56:09.2220499Z >>> model = SomeModel() 2025-08-26T19:56:09.2220773Z >>> tracer = QuantizationTracer(skipped_module_names, skipped_module_classes) 2025-08-26T19:56:09.2220976Z >>> graph_module = GraphModule(model, tracer.trace(model)) 2025-08-26T19:56:09.2221061Z 2025-08-26T19:56:09.2221229Z >>> # get our set of detectors and ModelReport instance 2025-08-26T19:56:09.2221325Z >>> detector_set = set( 2025-08-26T19:56:09.2221421Z ... [ 2025-08-26T19:56:09.2221560Z ... DynamicStaticDetector(tolerance=0.5), 2025-08-26T19:56:09.2221760Z ... InputWeightEqualizationDetector(ratio_threshold=0.7), 2025-08-26T19:56:09.2221859Z ... ] 2025-08-26T19:56:09.2221945Z ... ) 2025-08-26T19:56:09.2222180Z >>> tracer_reporter = ModelReport(graph_module, tracer_detector_set) 2025-08-26T19:56:09.2222261Z 2025-08-26T19:56:09.2222417Z >>> # now we insert the observers and calibrate the model 2025-08-26T19:56:09.2222692Z >>> tracer_model_with_observers = tracer_reporter.prepare_detailed_calibration() 2025-08-26T19:56:09.2222826Z >>> for i in range(num_callibration_batches): 2025-08-26T19:56:09.2222979Z >>> example_input = get_callibration_input() 2025-08-26T19:56:09.2223122Z >>> tracer_model_with_observers(example_input) 2025-08-26T19:56:09.2223207Z 2025-08-26T19:56:09.2223484Z >>> # finally we generate the reports and optionally remove the observers we inserted 2025-08-26T19:56:09.2223637Z >>> reports = tracer_reporter.generate_model_report( 2025-08-26T19:56:09.2223768Z ... remove_inserted_observers=True 2025-08-26T19:56:09.2223851Z ... ) 2025-08-26T19:56:09.2223929Z 2025-08-26T19:56:09.2224171Z >>> # Optional: we can generate the qconfig mapping based on the suggestions 2025-08-26T19:56:09.2224331Z >>> qconfigs = model_report.generate_qconfig_mapping() 2025-08-26T19:56:09.2224413Z 2025-08-26T19:56:09.2224671Z >>> # Optional: we can generate the equalization mapping based on the suggestions 2025-08-26T19:56:09.2224853Z >>> qconfigs = model_report.generate_equalization_mapping() 2025-08-26T19:56:09.2224975Z 2025-08-26T19:56:09.2225260Z >>> # Optional: we get a ModelReportVisualizer instance to do any visualizations desired 2025-08-26T19:56:09.2225476Z >>> model_report_visualizer = tracer_reporter.generate_visualizer() 2025-08-26T19:56:09.2225569Z 2025-08-26T19:56:09.2225657Z 2025-08-26T19:56:09.2225926Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2226009Z 2025-08-26T19:56:09.2226110Z warnings.warn(msg) 2025-08-26T19:56:09.2226206Z 2025-08-26T19:56:09.2226418Z --- Parse Warning: 42 / 146 --- 2025-08-26T19:56:09.2227727Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_filtered_tables in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=301. 2025-08-26T19:56:09.2228001Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2228132Z 2025-08-26T19:56:09.2228407Z Takes in optional filter values and generates two tables with desired information. 2025-08-26T19:56:09.2228491Z 2025-08-26T19:56:09.2228717Z The generated tables are presented in both a list-of-lists format 2025-08-26T19:56:09.2228799Z 2025-08-26T19:56:09.2229011Z The reason for the two tables are that they handle different things: 2025-08-26T19:56:09.2229192Z 1.) the first table handles all tensor level information 2025-08-26T19:56:09.2229441Z 2.) the second table handles and displays all channel based information 2025-08-26T19:56:09.2229537Z 2025-08-26T19:56:09.2229866Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T19:56:09.2230215Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T19:56:09.2230613Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T19:56:09.2230701Z 2025-08-26T19:56:09.2230814Z Tensor table columns: 2025-08-26T19:56:09.2231012Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:56:09.2231186Z ---- --------- --------- --------- --------- --------- 2025-08-26T19:56:09.2231269Z 2025-08-26T19:56:09.2231382Z Per-Channel table columns: 2025-08-26T19:56:09.2231626Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:56:09.2231798Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T19:56:09.2231899Z 2025-08-26T19:56:09.2231987Z Args: 2025-08-26T19:56:09.2232258Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T19:56:09.2232389Z contain this filter substring 2025-08-26T19:56:09.2232560Z Default = "", results in all the features being printed 2025-08-26T19:56:09.2232843Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:56:09.2233098Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:56:09.2233178Z 2025-08-26T19:56:09.2233309Z Returns a dictionary with two keys: 2025-08-26T19:56:09.2233489Z (Dict[str, Tuple[List, List]]) A dict containing two keys: 2025-08-26T19:56:09.2233634Z "tensor_level_info", "channel_level_info" 2025-08-26T19:56:09.2233751Z Each key maps to a tuple with: 2025-08-26T19:56:09.2233872Z A list of the headers of each table 2025-08-26T19:56:09.2234070Z A list of lists containing the table information row by row 2025-08-26T19:56:09.2234245Z The 0th index row will contain the headers of the columns 2025-08-26T19:56:09.2234384Z The rest of the rows will contain data 2025-08-26T19:56:09.2234510Z 2025-08-26T19:56:09.2234601Z Example Use: 2025-08-26T19:56:09.2234747Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2234899Z >>> mod_report_visualizer.generate_filtered_tables( 2025-08-26T19:56:09.2235096Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:56:09.2235391Z ... ) # generates table with per_channel_min info for all modules in block 1 of the model 2025-08-26T19:56:09.2235472Z 2025-08-26T19:56:09.2235738Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2235820Z 2025-08-26T19:56:09.2235921Z warnings.warn(msg) 2025-08-26T19:56:09.2236015Z 2025-08-26T19:56:09.2236208Z --- Parse Warning: 43 / 146 --- 2025-08-26T19:56:09.2237703Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_table_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=399. 2025-08-26T19:56:09.2238047Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2238144Z 2025-08-26T19:56:09.2238422Z Takes in optional filter values and prints out formatted tables of the information. 2025-08-26T19:56:09.2238503Z 2025-08-26T19:56:09.2238865Z The reason for the two tables printed out instead of one large one are that they handle different things: 2025-08-26T19:56:09.2239032Z 1.) the first table handles all tensor level information 2025-08-26T19:56:09.2239303Z 2.) the second table handles and displays all channel based information 2025-08-26T19:56:09.2239386Z 2025-08-26T19:56:09.2239717Z The reasoning for this is that having all the info in one table can make it ambiguous which collected 2025-08-26T19:56:09.2240104Z statistics are global, and which are actually per-channel, so it's better to split it up into two 2025-08-26T19:56:09.2240470Z tables. This also makes the information much easier to digest given the plethora of statistics collected 2025-08-26T19:56:09.2240569Z 2025-08-26T19:56:09.2240670Z Tensor table columns: 2025-08-26T19:56:09.2240866Z idx layer_fqn feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:56:09.2241037Z ---- --------- --------- --------- --------- --------- 2025-08-26T19:56:09.2241121Z 2025-08-26T19:56:09.2241244Z Per-Channel table columns: 2025-08-26T19:56:09.2241326Z 2025-08-26T19:56:09.2241550Z idx layer_fqn channel feature_1 feature_2 feature_3 .... feature_n 2025-08-26T19:56:09.2241727Z ---- --------- ------- --------- --------- --------- --------- 2025-08-26T19:56:09.2241806Z 2025-08-26T19:56:09.2241904Z Args: 2025-08-26T19:56:09.2242175Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T19:56:09.2242292Z contain this filter substring 2025-08-26T19:56:09.2242473Z Default = "", results in all the features being printed 2025-08-26T19:56:09.2242738Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:56:09.2243000Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:56:09.2243083Z 2025-08-26T19:56:09.2243174Z Example Use: 2025-08-26T19:56:09.2243320Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2243489Z >>> mod_report_visualizer.generate_table_visualization( 2025-08-26T19:56:09.2243701Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:56:09.2243785Z ... ) 2025-08-26T19:56:09.2243980Z >>> # prints out neatly formatted table with per_channel_min info 2025-08-26T19:56:09.2244120Z >>> # for all modules in block 1 of the model 2025-08-26T19:56:09.2244202Z 2025-08-26T19:56:09.2244510Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2244605Z 2025-08-26T19:56:09.2244704Z warnings.warn(msg) 2025-08-26T19:56:09.2244800Z 2025-08-26T19:56:09.2245007Z --- Parse Warning: 44 / 146 --- 2025-08-26T19:56:09.2246315Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_plot_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=564. 2025-08-26T19:56:09.2246600Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2246682Z 2025-08-26T19:56:09.2246938Z Takes in a feature and optional module_filter and plots of the desired data. 2025-08-26T19:56:09.2247020Z 2025-08-26T19:56:09.2247313Z For per channel features, it averages the value across the channels and plots a point 2025-08-26T19:56:09.2247578Z per module. The reason for this is that for models with hundreds of channels, it can 2025-08-26T19:56:09.2247894Z be hard to differentiate one channel line from another, and so the point of generating 2025-08-26T19:56:09.2248180Z a single average point per module is to give a sense of general trends that encourage 2025-08-26T19:56:09.2248277Z further deep dives. 2025-08-26T19:56:09.2248371Z 2025-08-26T19:56:09.2248456Z Note: 2025-08-26T19:56:09.2248726Z Only features in the report that have tensor value data are plottable by this class 2025-08-26T19:56:09.2249007Z When the tensor information is plotted, it will plot: 2025-08-26T19:56:09.2249150Z idx as the x val, feature value as the y_val 2025-08-26T19:56:09.2249339Z When the channel information is plotted, it will plot: 2025-08-26T19:56:09.2249609Z the first idx of each module as the x val, feature value as the y_val [for each channel] 2025-08-26T19:56:09.2249874Z The reason for this is that we want to be able to compare values across the 2025-08-26T19:56:09.2250129Z channels for same layer, and it will be hard if values are staggered by idx 2025-08-26T19:56:09.2250305Z This means each module is represented by only 1 x value 2025-08-26T19:56:09.2250404Z Args: 2025-08-26T19:56:09.2250632Z feature_filter (str): Filters the features presented to only those that 2025-08-26T19:56:09.2250744Z contain this filter substring 2025-08-26T19:56:09.2251024Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:56:09.2251276Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:56:09.2251370Z 2025-08-26T19:56:09.2251458Z Example Use: 2025-08-26T19:56:09.2251590Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2251769Z >>> mod_report_visualizer.generate_plot_visualization( 2025-08-26T19:56:09.2251970Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:56:09.2252067Z ... ) 2025-08-26T19:56:09.2252250Z >>> # outputs line plot of per_channel_min information for all 2025-08-26T19:56:09.2252438Z >>> # modules in block1 of model each channel gets it's own line, 2025-08-26T19:56:09.2252627Z >>> # and it's plotted across the in-order modules on the x-axis 2025-08-26T19:56:09.2252712Z 2025-08-26T19:56:09.2252979Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2253061Z 2025-08-26T19:56:09.2253159Z warnings.warn(msg) 2025-08-26T19:56:09.2253250Z 2025-08-26T19:56:09.2253451Z --- Parse Warning: 45 / 146 --- 2025-08-26T19:56:09.2254793Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ModelReportVisualizer.generate_histogram_visualization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/ao/quantization/fx/_model_report/model_report_visualizer.py line=643. 2025-08-26T19:56:09.2255095Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2255177Z 2025-08-26T19:56:09.2255473Z Takes in a feature and optional module_filter and plots the histogram of desired data. 2025-08-26T19:56:09.2255554Z 2025-08-26T19:56:09.2255649Z Note: 2025-08-26T19:56:09.2255922Z Only features in the report that have tensor value data can be viewed as a histogram 2025-08-26T19:56:09.2256192Z If you want to plot a histogram from all the channel values of a specific feature for 2025-08-26T19:56:09.2256456Z a specific model, make sure to specify both the model and the feature properly 2025-08-26T19:56:09.2256705Z in the filters and you should be able to see a distribution of the channel data 2025-08-26T19:56:09.2256798Z 2025-08-26T19:56:09.2256885Z Args: 2025-08-26T19:56:09.2257154Z feature_filter (str, optional): Filters the features presented to only those that 2025-08-26T19:56:09.2257306Z contain this filter substring 2025-08-26T19:56:09.2257472Z Default = "", results in all the features being printed 2025-08-26T19:56:09.2257753Z module_fqn_filter (str, optional): Only includes modules that contains this string 2025-08-26T19:56:09.2258002Z Default = "", results in all the modules in the reports to be visible in the table 2025-08-26T19:56:09.2258232Z num_bins (int, optional): The number of bins to create the histogram with 2025-08-26T19:56:09.2258464Z Default = 10, the values will be split into 10 equal sized bins 2025-08-26T19:56:09.2258548Z 2025-08-26T19:56:09.2258655Z Example Use: 2025-08-26T19:56:09.2258757Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2259066Z >>> mod_report_visualizer.generategenerate_histogram_visualization_plot_visualization( 2025-08-26T19:56:09.2259310Z ... feature_filter="per_channel_min", module_fqn_filter="block1" 2025-08-26T19:56:09.2259398Z ... ) 2025-08-26T19:56:09.2259692Z # outputs histogram of per_channel_min information for all modules in block1 of model 2025-08-26T19:56:09.2259956Z information is gathered across all channels for all modules in block 1 for the 2025-08-26T19:56:09.2260194Z per_channel_min and is displayed in a histogram of equally sized bins 2025-08-26T19:56:09.2260275Z 2025-08-26T19:56:09.2260532Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2260629Z 2025-08-26T19:56:09.2260731Z warnings.warn(msg) 2025-08-26T19:56:09.2260812Z 2025-08-26T19:56:09.2261019Z --- Parse Warning: 46 / 146 --- 2025-08-26T19:56:09.2261945Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=record_function in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/autograd/profiler.py line=734. 2025-08-26T19:56:09.2262230Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2262623Z Context manager/function decorator that adds a label to a code block/function when running autograd profiler. 2025-08-26T19:56:09.2262822Z Label will only appear if CPU activity tracing is enabled. 2025-08-26T19:56:09.2262906Z 2025-08-26T19:56:09.2263042Z It is useful when tracing the code profile. 2025-08-26T19:56:09.2269160Z 2025-08-26T19:56:09.2269291Z Args: 2025-08-26T19:56:09.2269479Z name (str): Label assigned to the block of code. 2025-08-26T19:56:09.2269677Z node_id (int): ID of node, for distributed profiling. Unset in 2025-08-26T19:56:09.2269789Z non-distributed cases. 2025-08-26T19:56:09.2269885Z 2025-08-26T19:56:09.2269974Z Example: 2025-08-26T19:56:09.2270168Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_AUTOGRAD_PROFILER) 2025-08-26T19:56:09.2270410Z >>> x = torch.randn((1, 1), requires_grad=True) 2025-08-26T19:56:09.2270581Z >>> with torch.autograd.profiler.profile() as prof: 2025-08-26T19:56:09.2270690Z ... y = x**2 2025-08-26T19:56:09.2270854Z ... with torch.autograd.profiler.record_function( 2025-08-26T19:56:09.2270946Z ... "label-z" 2025-08-26T19:56:09.2271062Z ... ): # label the block 2025-08-26T19:56:09.2271159Z ... z = y**3 2025-08-26T19:56:09.2271270Z ... y.backward() 2025-08-26T19:56:09.2271384Z >>> # xdoctest: +IGNORE_WANT 2025-08-26T19:56:09.2271526Z >>> # NOTE: some columns were removed for brevity 2025-08-26T19:56:09.2271748Z >>> print(prof.key_averages().table(sort_by="self_cpu_time_total")) 2025-08-26T19:56:09.2271951Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2272153Z Name Self CPU total % CPU time avg Number of Calls 2025-08-26T19:56:09.2272388Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2272535Z pow 60.77% 47.470us 3 2025-08-26T19:56:09.2272666Z mul 21.73% 25.465us 2 2025-08-26T19:56:09.2272842Z PowBackward0 12.03% 121.891us 1 2025-08-26T19:56:09.2273111Z torch::autograd::AccumulateGrad 2.70% 6.324us 1 2025-08-26T19:56:09.2273259Z label-z 2.13% 12.421us 1 2025-08-26T19:56:09.2273473Z torch::autograd::GraphRoot 0.64% 1.503us 1 2025-08-26T19:56:09.2273715Z ----------------------------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2273836Z Self CPU time total: 234.344us 2025-08-26T19:56:09.2273950Z CUDA time total: 0.000us 2025-08-26T19:56:09.2274034Z 2025-08-26T19:56:09.2274128Z 2025-08-26T19:56:09.2274391Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2274474Z 2025-08-26T19:56:09.2274582Z warnings.warn(msg) 2025-08-26T19:56:09.2274663Z 2025-08-26T19:56:09.2274915Z --- Parse Warning: 47 / 146 --- 2025-08-26T19:56:09.2275914Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DeviceMesh.__getitem__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/device_mesh.py line=721. 2025-08-26T19:56:09.2276170Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.2276263Z 2025-08-26T19:56:09.2276544Z Slice the current DeviceMesh based on the mesh_dim_names given to create a submesh. 2025-08-26T19:56:09.2276831Z The submesh created consists of the dimensions and the communicators indicated by 2025-08-26T19:56:09.2276924Z ``mesh_dim_names`` 2025-08-26T19:56:09.2277008Z 2025-08-26T19:56:09.2277105Z Args: 2025-08-26T19:56:09.2277344Z mesh_dim_names (Union[str, Tuple[str]]): the name or the tuple of names of the 2025-08-26T19:56:09.2277543Z mesh dimension of the DeviceMesh to create the submesh for. 2025-08-26T19:56:09.2277630Z Returns: 2025-08-26T19:56:09.2277738Z A :class:`DeviceMesh` object 2025-08-26T19:56:09.2277832Z 2025-08-26T19:56:09.2278124Z The following program runs on each process/rank in an SPMD manner in a world size of 8. 2025-08-26T19:56:09.2278233Z In the first example: 2025-08-26T19:56:09.2278490Z Calling mesh_2d["tp"] on rank 0, 1, 2, 3 returns a 1D submesh of DeviceMesh:([0, 1, 2, 3]). 2025-08-26T19:56:09.2278745Z Calling mesh_2d["tp"] on rank 4, 5, 6, 7 returns a 1D submesh of DeviceMesh:([4, 5, 6, 7]). 2025-08-26T19:56:09.2279013Z Calling mesh_2d["dp"] on rank 0, 4 returns a 1D submesh of DeviceMesh:([0, 4]). 2025-08-26T19:56:09.2279239Z Calling mesh_2d["dp"] on rank 1, 5 returns a 1D submesh of DeviceMesh:([1, 5]). 2025-08-26T19:56:09.2279469Z Calling mesh_2d["dp"] on rank 2, 6 returns a 1D submesh of DeviceMesh:([2, 6]). 2025-08-26T19:56:09.2279690Z Calling mesh_2d["dp"] on rank 3, 7 returns a 1D submesh of DeviceMesh:([3, 7]). 2025-08-26T19:56:09.2279771Z 2025-08-26T19:56:09.2279881Z In the second example: 2025-08-26T19:56:09.2280152Z Calling mesh_3d["dp", "cp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 1], [4, 5]]). 2025-08-26T19:56:09.2280431Z Calling mesh_3d["dp", "cp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 3], [6, 7]]). 2025-08-26T19:56:09.2280700Z Calling mesh_3d["cp", "dp"] on rank 0, 1, 4, 5 returns a 2D submesh of DeviceMesh:([[0, 4], [1, 5]]). 2025-08-26T19:56:09.2281006Z Calling mesh_3d["cp", "dp"] on rank 2, 3, 6, 7 returns a 2D submesh of DeviceMesh:([[2, 6], [3, 7]]). 2025-08-26T19:56:09.2281087Z 2025-08-26T19:56:09.2281179Z Example:: 2025-08-26T19:56:09.2281272Z 2025-08-26T19:56:09.2281385Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T19:56:09.2281564Z >>> from torch.distributed.device_mesh import DeviceMesh 2025-08-26T19:56:09.2281659Z >>> 2025-08-26T19:56:09.2281866Z >>> # Initialize a 2D device mesh as (2, 4) to represent the topology 2025-08-26T19:56:09.2282049Z >>> # of cross-host(dim 0), and within-host (dim 1). 2025-08-26T19:56:09.2282309Z >>> mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T19:56:09.2282413Z >>> tp_mesh = mesh_2d["tp"] 2025-08-26T19:56:09.2282527Z >>> dp_mesh = mesh_2d["dp"] 2025-08-26T19:56:09.2282610Z >>> 2025-08-26T19:56:09.2282754Z >>> # Initialize a 3D mesh. 2025-08-26T19:56:09.2283036Z >>> mesh_3d = init_device_mesh(device_type="cuda", (2,2,2), mesh_dim_names=("dp", "pp", "cp")) 2025-08-26T19:56:09.2283349Z >>> # The order of the mesh_dim_names provided deteremines the order of dimensions in the submesh. 2025-08-26T19:56:09.2283480Z >>> dp_cp_mesh = mesh_3d["dp", "cp"] 2025-08-26T19:56:09.2283595Z >>> cp_dp_mesh = mesh_3d["cp", "dp"] 2025-08-26T19:56:09.2283686Z 2025-08-26T19:56:09.2284379Z Original Error: SyntaxError('positional argument follows keyword argument', ('', 6, 82, 'mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp"))\n', 6, 83)) 2025-08-26T19:56:09.2284472Z 2025-08-26T19:56:09.2284722Z mesh_2d = init_device_mesh(device_type="cuda", (2,4), mesh_dim_names=("dp", "tp")) 2025-08-26T19:56:09.2284842Z ^ 2025-08-26T19:56:09.2284951Z warnings.warn(msg) 2025-08-26T19:56:09.2285036Z 2025-08-26T19:56:09.2285237Z --- Parse Warning: 48 / 146 --- 2025-08-26T19:56:09.2286243Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=batch_isend_irecv in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2710. 2025-08-26T19:56:09.2286517Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2286606Z 2025-08-26T19:56:09.2286861Z Send or Receive a batch of tensors asynchronously and return a list of requests. 2025-08-26T19:56:09.2286956Z 2025-08-26T19:56:09.2287209Z Process each of the operations in ``p2p_op_list`` and return the corresponding 2025-08-26T19:56:09.2287409Z requests. NCCL, Gloo, and UCC backend are currently supported. 2025-08-26T19:56:09.2287499Z 2025-08-26T19:56:09.2287586Z Args: 2025-08-26T19:56:09.2287828Z p2p_op_list: A list of point-to-point operations(type of each operator is 2025-08-26T19:56:09.2288097Z ``torch.distributed.P2POp``). The order of the isend/irecv in the list 2025-08-26T19:56:09.2288310Z matters and it needs to match with corresponding isend/irecv on the 2025-08-26T19:56:09.2288414Z remote end. 2025-08-26T19:56:09.2288495Z 2025-08-26T19:56:09.2288594Z Returns: 2025-08-26T19:56:09.2288949Z A list of distributed request objects returned by calling the corresponding 2025-08-26T19:56:09.2289052Z op in the op_list. 2025-08-26T19:56:09.2289143Z 2025-08-26T19:56:09.2289230Z Examples: 2025-08-26T19:56:09.2289344Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T19:56:09.2289552Z >>> send_tensor = torch.arange(2, dtype=torch.float32) + 2 * rank 2025-08-26T19:56:09.2289708Z >>> recv_tensor = torch.randn(2, dtype=torch.float32) 2025-08-26T19:56:09.2289933Z >>> send_op = dist.P2POp(dist.isend, send_tensor, (rank + 1) % world_size) 2025-08-26T19:56:09.2290043Z >>> recv_op = dist.P2POp( 2025-08-26T19:56:09.2290272Z ... dist.irecv, recv_tensor, (rank - 1 + world_size) % world_size 2025-08-26T19:56:09.2290367Z ... ) 2025-08-26T19:56:09.2290506Z >>> reqs = batch_isend_irecv([send_op, recv_op]) 2025-08-26T19:56:09.2290616Z >>> for req in reqs: 2025-08-26T19:56:09.2290709Z >>> req.wait() 2025-08-26T19:56:09.2290800Z >>> recv_tensor 2025-08-26T19:56:09.2290906Z tensor([2, 3]) # Rank 0 2025-08-26T19:56:09.2291005Z tensor([0, 1]) # Rank 1 2025-08-26T19:56:09.2291095Z 2025-08-26T19:56:09.2291370Z .. note:: Note that when this API is used with the NCCL PG backend, users must set 2025-08-26T19:56:09.2291602Z the current GPU device with `torch.cuda.set_device`, otherwise it will 2025-08-26T19:56:09.2291722Z lead to unexpected hang issues. 2025-08-26T19:56:09.2291804Z 2025-08-26T19:56:09.2292057Z In addition, if this API is the first collective call in the ``group`` 2025-08-26T19:56:09.2292286Z passed to ``dist.P2POp``, all ranks of the ``group`` must participate in 2025-08-26T19:56:09.2292514Z this API call; otherwise, the behavior is undefined. If this API call is 2025-08-26T19:56:09.2292751Z not the first collective call in the ``group``, batched P2P operations 2025-08-26T19:56:09.2292950Z involving only a subset of ranks of the ``group`` are allowed. 2025-08-26T19:56:09.2293040Z 2025-08-26T19:56:09.2293295Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2293377Z 2025-08-26T19:56:09.2293488Z warnings.warn(msg) 2025-08-26T19:56:09.2293569Z 2025-08-26T19:56:09.2293782Z --- Parse Warning: 49 / 146 --- 2025-08-26T19:56:09.2294747Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_reduce in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=2842. 2025-08-26T19:56:09.2295021Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2295107Z 2025-08-26T19:56:09.2295378Z Reduces the tensor data across all machines in a way that all get the final result. 2025-08-26T19:56:09.2295469Z 2025-08-26T19:56:09.2295698Z After the call ``tensor`` is going to be bitwise identical in all processes. 2025-08-26T19:56:09.2295777Z 2025-08-26T19:56:09.2295903Z Complex tensors are supported. 2025-08-26T19:56:09.2295983Z 2025-08-26T19:56:09.2296079Z Args: 2025-08-26T19:56:09.2296285Z tensor (Tensor): Input and output of the collective. The function 2025-08-26T19:56:09.2296390Z operates in-place. 2025-08-26T19:56:09.2296520Z op (optional): One of the values from 2025-08-26T19:56:09.2296638Z ``torch.distributed.ReduceOp`` 2025-08-26T19:56:09.2296853Z enum. Specifies an operation used for element-wise reductions. 2025-08-26T19:56:09.2297160Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:56:09.2297291Z the default process group will be used. 2025-08-26T19:56:09.2297502Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T19:56:09.2297583Z 2025-08-26T19:56:09.2297685Z Returns: 2025-08-26T19:56:09.2297827Z Async work handle, if async_op is set to True. 2025-08-26T19:56:09.2297979Z None, if not async_op or if not part of the group 2025-08-26T19:56:09.2298074Z 2025-08-26T19:56:09.2298162Z Examples: 2025-08-26T19:56:09.2298275Z >>> # xdoctest: +SKIP("no rank") 2025-08-26T19:56:09.2298421Z >>> # All tensors below are of torch.int64 type. 2025-08-26T19:56:09.2298541Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:56:09.2298671Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T19:56:09.2298902Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T19:56:09.2299015Z >>> tensor 2025-08-26T19:56:09.2299140Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T19:56:09.2299255Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T19:56:09.2299398Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T19:56:09.2299483Z >>> tensor 2025-08-26T19:56:09.2299596Z tensor([4, 6], device='cuda:0') # Rank 0 2025-08-26T19:56:09.2299719Z tensor([4, 6], device='cuda:1') # Rank 1 2025-08-26T19:56:09.2299799Z 2025-08-26T19:56:09.2299975Z >>> # All tensors below are of torch.cfloat type. 2025-08-26T19:56:09.2300092Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:56:09.2300197Z >>> tensor = torch.tensor( 2025-08-26T19:56:09.2300355Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T19:56:09.2300454Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T19:56:09.2300546Z >>> tensor 2025-08-26T19:56:09.2300715Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T19:56:09.2300856Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T19:56:09.2301000Z >>> dist.all_reduce(tensor, op=ReduceOp.SUM) 2025-08-26T19:56:09.2301087Z >>> tensor 2025-08-26T19:56:09.2301234Z tensor([4.+4.j, 6.+6.j], device='cuda:0') # Rank 0 2025-08-26T19:56:09.2301369Z tensor([4.+4.j, 6.+6.j], device='cuda:1') # Rank 1 2025-08-26T19:56:09.2301450Z 2025-08-26T19:56:09.2301548Z 2025-08-26T19:56:09.2301808Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2301903Z 2025-08-26T19:56:09.2302006Z warnings.warn(msg) 2025-08-26T19:56:09.2302086Z 2025-08-26T19:56:09.2302295Z --- Parse Warning: 50 / 146 --- 2025-08-26T19:56:09.2303274Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=gather_object in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3202. 2025-08-26T19:56:09.2303561Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2303642Z 2025-08-26T19:56:09.2303867Z Gathers picklable objects from the whole group in a single process. 2025-08-26T19:56:09.2303958Z 2025-08-26T19:56:09.2304197Z Similar to :func:`gather`, but Python objects can be passed in. Note that the 2025-08-26T19:56:09.2304358Z object must be picklable in order to be gathered. 2025-08-26T19:56:09.2304439Z 2025-08-26T19:56:09.2304521Z Args: 2025-08-26T19:56:09.2304666Z obj (Any): Input object. Must be picklable. 2025-08-26T19:56:09.2304879Z object_gather_list (list[Any]): Output list. On the ``dst`` rank, it 2025-08-26T19:56:09.2305068Z should be correctly sized as the size of the group for this 2025-08-26T19:56:09.2305300Z collective and will contain the output. Must be ``None`` on non-dst 2025-08-26T19:56:09.2305440Z ranks. (default is ``None``) 2025-08-26T19:56:09.2305781Z dst (int, optional): Destination rank on global process group (regardless of ``group`` argument). 2025-08-26T19:56:09.2305980Z (If both ``dst`` and ``group_dst`` are None, default is global rank 0) 2025-08-26T19:56:09.2306229Z group: (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:56:09.2306423Z the default process group will be used. Default is ``None``. 2025-08-26T19:56:09.2306778Z group_dst (int, optional): Destination rank on ``group``. Invalid to specify both ``dst`` and ``group_dst`` 2025-08-26T19:56:09.2306870Z 2025-08-26T19:56:09.2306956Z Returns: 2025-08-26T19:56:09.2307153Z None. On the ``dst`` rank, ``object_gather_list`` will contain the 2025-08-26T19:56:09.2307257Z output of the collective. 2025-08-26T19:56:09.2307341Z 2025-08-26T19:56:09.2307572Z .. note:: Note that this API differs slightly from the gather collective 2025-08-26T19:56:09.2307820Z since it does not provide an async_op handle and thus will be a blocking 2025-08-26T19:56:09.2307919Z call. 2025-08-26T19:56:09.2308002Z 2025-08-26T19:56:09.2308238Z .. note:: For NCCL-based processed groups, internal tensor representations 2025-08-26T19:56:09.2308465Z of objects must be moved to the GPU device before communication takes 2025-08-26T19:56:09.2308611Z place. In this case, the device used is given by 2025-08-26T19:56:09.2308847Z ``torch.cuda.current_device()`` and it is the user's responsibility to 2025-08-26T19:56:09.2309094Z ensure that this is set so that each rank has an individual GPU, via 2025-08-26T19:56:09.2309204Z ``torch.cuda.set_device()``. 2025-08-26T19:56:09.2309296Z 2025-08-26T19:56:09.2309388Z .. warning:: 2025-08-26T19:56:09.2309640Z Object collectives have a number of serious performance and scalability 2025-08-26T19:56:09.2309848Z limitations. See :ref:`object_collectives` for details. 2025-08-26T19:56:09.2309930Z 2025-08-26T19:56:09.2310031Z .. warning:: 2025-08-26T19:56:09.2310229Z :func:`gather_object` uses ``pickle`` module implicitly, which is 2025-08-26T19:56:09.2310460Z known to be insecure. It is possible to construct malicious pickle data 2025-08-26T19:56:09.2310679Z which will execute arbitrary code during unpickling. Only call this 2025-08-26T19:56:09.2310788Z function with data you trust. 2025-08-26T19:56:09.2310881Z 2025-08-26T19:56:09.2310969Z .. warning:: 2025-08-26T19:56:09.2311185Z Calling :func:`gather_object` with GPU tensors is not well supported 2025-08-26T19:56:09.2311419Z and inefficient as it incurs GPU -> CPU transfer since tensors would be 2025-08-26T19:56:09.2311590Z pickled. Please consider using :func:`gather` instead. 2025-08-26T19:56:09.2311681Z 2025-08-26T19:56:09.2311767Z Example:: 2025-08-26T19:56:09.2311910Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T19:56:09.2312104Z >>> # Note: Process group initialization omitted on each rank. 2025-08-26T19:56:09.2312222Z >>> import torch.distributed as dist 2025-08-26T19:56:09.2312340Z >>> # Assumes world_size of 3. 2025-08-26T19:56:09.2312517Z >>> gather_objects = ["foo", 12, {1: 2}] # any picklable object 2025-08-26T19:56:09.2312639Z >>> output = [None for _ in gather_objects] 2025-08-26T19:56:09.2312748Z >>> dist.gather_object( 2025-08-26T19:56:09.2312871Z ... gather_objects[dist.get_rank()], 2025-08-26T19:56:09.2313014Z ... output if dist.get_rank() == 0 else None, 2025-08-26T19:56:09.2313100Z ... dst=0 2025-08-26T19:56:09.2313182Z ... ) 2025-08-26T19:56:09.2313279Z >>> # On rank 0 2025-08-26T19:56:09.2313363Z >>> output 2025-08-26T19:56:09.2313463Z ['foo', 12, {1: 2}] 2025-08-26T19:56:09.2313542Z 2025-08-26T19:56:09.2313804Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2313925Z 2025-08-26T19:56:09.2314022Z warnings.warn(msg) 2025-08-26T19:56:09.2314112Z 2025-08-26T19:56:09.2314310Z --- Parse Warning: 51 / 146 --- 2025-08-26T19:56:09.2315271Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_gather in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=3798. 2025-08-26T19:56:09.2315551Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2315632Z 2025-08-26T19:56:09.2315785Z Gathers tensors from the whole group in a list. 2025-08-26T19:56:09.2315865Z 2025-08-26T19:56:09.2316009Z Complex and uneven sized tensors are supported. 2025-08-26T19:56:09.2316105Z 2025-08-26T19:56:09.2316189Z Args: 2025-08-26T19:56:09.2316372Z tensor_list (list[Tensor]): Output list. It should contain 2025-08-26T19:56:09.2316640Z correctly-sized tensors to be used for output of the collective. 2025-08-26T19:56:09.2316763Z Uneven sized tensors are supported. 2025-08-26T19:56:09.2316968Z tensor (Tensor): Tensor to be broadcast from current process. 2025-08-26T19:56:09.2317203Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:56:09.2317345Z the default process group will be used. 2025-08-26T19:56:09.2317540Z async_op (bool, optional): Whether this op should be an async op 2025-08-26T19:56:09.2317621Z 2025-08-26T19:56:09.2317746Z Returns: 2025-08-26T19:56:09.2317888Z Async work handle, if async_op is set to True. 2025-08-26T19:56:09.2318037Z None, if not async_op or if not part of the group 2025-08-26T19:56:09.2318131Z 2025-08-26T19:56:09.2318219Z Examples: 2025-08-26T19:56:09.2318367Z >>> # xdoctest: +SKIP("need process group init") 2025-08-26T19:56:09.2318534Z >>> # All tensors below are of torch.int64 dtype. 2025-08-26T19:56:09.2318659Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:56:09.2318790Z >>> device = torch.device(f"cuda:{rank}") 2025-08-26T19:56:09.2318884Z >>> tensor_list = [ 2025-08-26T19:56:09.2319108Z ... torch.zeros(2, dtype=torch.int64, device=device) for _ in range(2) 2025-08-26T19:56:09.2319191Z ... ] 2025-08-26T19:56:09.2319282Z >>> tensor_list 2025-08-26T19:56:09.2319494Z [tensor([0, 0], device='cuda:0'), tensor([0, 0], device='cuda:0')] # Rank 0 2025-08-26T19:56:09.2319693Z [tensor([0, 0], device='cuda:1'), tensor([0, 0], device='cuda:1')] # Rank 1 2025-08-26T19:56:09.2319933Z >>> tensor = torch.arange(2, dtype=torch.int64, device=device) + 1 + 2 * rank 2025-08-26T19:56:09.2320021Z >>> tensor 2025-08-26T19:56:09.2320142Z tensor([1, 2], device='cuda:0') # Rank 0 2025-08-26T19:56:09.2320270Z tensor([3, 4], device='cuda:1') # Rank 1 2025-08-26T19:56:09.2320391Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T19:56:09.2320494Z >>> tensor_list 2025-08-26T19:56:09.2320688Z [tensor([1, 2], device='cuda:0'), tensor([3, 4], device='cuda:0')] # Rank 0 2025-08-26T19:56:09.2320884Z [tensor([1, 2], device='cuda:1'), tensor([3, 4], device='cuda:1')] # Rank 1 2025-08-26T19:56:09.2320979Z 2025-08-26T19:56:09.2321123Z >>> # All tensors below are of torch.cfloat dtype. 2025-08-26T19:56:09.2321254Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:56:09.2321350Z >>> tensor_list = [ 2025-08-26T19:56:09.2321570Z ... torch.zeros(2, dtype=torch.cfloat, device=device) for _ in range(2) 2025-08-26T19:56:09.2321665Z ... ] 2025-08-26T19:56:09.2321755Z >>> tensor_list 2025-08-26T19:56:09.2322023Z [tensor([0.+0.j, 0.+0.j], device='cuda:0'), tensor([0.+0.j, 0.+0.j], device='cuda:0')] # Rank 0 2025-08-26T19:56:09.2322267Z [tensor([0.+0.j, 0.+0.j], device='cuda:1'), tensor([0.+0.j, 0.+0.j], device='cuda:1')] # Rank 1 2025-08-26T19:56:09.2322401Z >>> tensor = torch.tensor( 2025-08-26T19:56:09.2322559Z ... [1 + 1j, 2 + 2j], dtype=torch.cfloat, device=device 2025-08-26T19:56:09.2322653Z ... ) + 2 * rank * (1 + 1j) 2025-08-26T19:56:09.2322754Z >>> tensor 2025-08-26T19:56:09.2322893Z tensor([1.+1.j, 2.+2.j], device='cuda:0') # Rank 0 2025-08-26T19:56:09.2323033Z tensor([3.+3.j, 4.+4.j], device='cuda:1') # Rank 1 2025-08-26T19:56:09.2323163Z >>> dist.all_gather(tensor_list, tensor) 2025-08-26T19:56:09.2323254Z >>> tensor_list 2025-08-26T19:56:09.2323506Z [tensor([1.+1.j, 2.+2.j], device='cuda:0'), tensor([3.+3.j, 4.+4.j], device='cuda:0')] # Rank 0 2025-08-26T19:56:09.2323743Z [tensor([1.+1.j, 2.+2.j], device='cuda:1'), tensor([3.+3.j, 4.+4.j], device='cuda:1')] # Rank 1 2025-08-26T19:56:09.2323823Z 2025-08-26T19:56:09.2323913Z 2025-08-26T19:56:09.2324176Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2324295Z 2025-08-26T19:56:09.2324391Z warnings.warn(msg) 2025-08-26T19:56:09.2324472Z 2025-08-26T19:56:09.2324675Z --- Parse Warning: 52 / 146 --- 2025-08-26T19:56:09.2325654Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all_single in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4504. 2025-08-26T19:56:09.2325962Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2326042Z 2025-08-26T19:56:09.2326298Z Split input tensor and then scatter the split list to all processes in a group. 2025-08-26T19:56:09.2326394Z 2025-08-26T19:56:09.2326659Z Later the received tensors are concatenated from all the processes in the group 2025-08-26T19:56:09.2326820Z and returned as a single output tensor. 2025-08-26T19:56:09.2326902Z 2025-08-26T19:56:09.2327014Z Complex tensors are supported. 2025-08-26T19:56:09.2327107Z 2025-08-26T19:56:09.2327188Z Args: 2025-08-26T19:56:09.2327362Z output (Tensor): Gathered concatenated output tensor. 2025-08-26T19:56:09.2327501Z input (Tensor): Input tensor to scatter. 2025-08-26T19:56:09.2327727Z output_split_sizes: (list[Int], optional): Output split sizes for dim 0 2025-08-26T19:56:09.2327944Z if specified None or empty, dim 0 of ``output`` tensor must divide 2025-08-26T19:56:09.2328050Z equally by ``world_size``. 2025-08-26T19:56:09.2328283Z input_split_sizes: (list[Int], optional): Input split sizes for dim 0 2025-08-26T19:56:09.2328483Z if specified None or empty, dim 0 of ``input`` tensor must divide 2025-08-26T19:56:09.2328591Z equally by ``world_size``. 2025-08-26T19:56:09.2328921Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:56:09.2329053Z the default process group will be used. 2025-08-26T19:56:09.2329268Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T19:56:09.2329345Z 2025-08-26T19:56:09.2329430Z Returns: 2025-08-26T19:56:09.2329584Z Async work handle, if async_op is set to True. 2025-08-26T19:56:09.2329731Z None, if not async_op or if not part of the group. 2025-08-26T19:56:09.2329811Z 2025-08-26T19:56:09.2329913Z .. warning:: 2025-08-26T19:56:09.2330086Z `all_to_all_single` is experimental and subject to change. 2025-08-26T19:56:09.2330185Z 2025-08-26T19:56:09.2330275Z Examples: 2025-08-26T19:56:09.2330400Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T19:56:09.2330524Z >>> input = torch.arange(4) + rank * 4 2025-08-26T19:56:09.2330610Z >>> input 2025-08-26T19:56:09.2330727Z tensor([0, 1, 2, 3]) # Rank 0 2025-08-26T19:56:09.2330828Z tensor([4, 5, 6, 7]) # Rank 1 2025-08-26T19:56:09.2330965Z tensor([8, 9, 10, 11]) # Rank 2 2025-08-26T19:56:09.2331078Z tensor([12, 13, 14, 15]) # Rank 3 2025-08-26T19:56:09.2331220Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T19:56:09.2331358Z >>> dist.all_to_all_single(output, input) 2025-08-26T19:56:09.2331445Z >>> output 2025-08-26T19:56:09.2331545Z tensor([0, 4, 8, 12]) # Rank 0 2025-08-26T19:56:09.2331651Z tensor([1, 5, 9, 13]) # Rank 1 2025-08-26T19:56:09.2331751Z tensor([2, 6, 10, 14]) # Rank 2 2025-08-26T19:56:09.2331864Z tensor([3, 7, 11, 15]) # Rank 3 2025-08-26T19:56:09.2331945Z 2025-08-26T19:56:09.2332111Z >>> # Essentially, it is similar to following operation: 2025-08-26T19:56:09.2332262Z >>> scatter_list = list(input.chunk(world_size)) 2025-08-26T19:56:09.2332400Z >>> gather_list = list(output.chunk(world_size)) 2025-08-26T19:56:09.2332517Z >>> for i in range(world_size): 2025-08-26T19:56:09.2332755Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src = i) 2025-08-26T19:56:09.2332867Z 2025-08-26T19:56:09.2332998Z >>> # Another example with uneven split 2025-08-26T19:56:09.2333084Z >>> input 2025-08-26T19:56:09.2333243Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T19:56:09.2333418Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T19:56:09.2333575Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T19:56:09.2333769Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T19:56:09.2333865Z >>> input_splits 2025-08-26T19:56:09.2334000Z [2, 2, 1, 1] # Rank 0 2025-08-26T19:56:09.2334121Z [3, 2, 2, 2] # Rank 1 2025-08-26T19:56:09.2334270Z [2, 1, 1, 1] # Rank 2 2025-08-26T19:56:09.2334407Z [2, 2, 2, 1] # Rank 3 2025-08-26T19:56:09.2334504Z >>> output_splits 2025-08-26T19:56:09.2334640Z [2, 3, 2, 2] # Rank 0 2025-08-26T19:56:09.2334762Z [2, 2, 1, 2] # Rank 1 2025-08-26T19:56:09.2334883Z [1, 2, 1, 2] # Rank 2 2025-08-26T19:56:09.2335017Z [1, 2, 1, 1] # Rank 3 2025-08-26T19:56:09.2335110Z >>> output = ... 2025-08-26T19:56:09.2335333Z >>> dist.all_to_all_single(output, input, output_splits, input_splits) 2025-08-26T19:56:09.2335418Z >>> output 2025-08-26T19:56:09.2335575Z tensor([ 0, 1, 10, 11, 12, 20, 21, 30, 31]) # Rank 0 2025-08-26T19:56:09.2335748Z tensor([ 2, 3, 13, 14, 22, 32, 33]) # Rank 1 2025-08-26T19:56:09.2335905Z tensor([ 4, 15, 16, 23, 34, 35]) # Rank 2 2025-08-26T19:56:09.2336068Z tensor([ 5, 17, 18, 24, 36]) # Rank 3 2025-08-26T19:56:09.2336146Z 2025-08-26T19:56:09.2336230Z 2025-08-26T19:56:09.2336404Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T19:56:09.2336507Z >>> input = torch.tensor( 2025-08-26T19:56:09.2336665Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T19:56:09.2336764Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T19:56:09.2336850Z >>> input 2025-08-26T19:56:09.2337037Z tensor([1+1j, 2+2j, 3+3j, 4+4j]) # Rank 0 2025-08-26T19:56:09.2337208Z tensor([5+5j, 6+6j, 7+7j, 8+8j]) # Rank 1 2025-08-26T19:56:09.2337570Z tensor([9+9j, 10+10j, 11+11j, 12+12j]) # Rank 2 2025-08-26T19:56:09.2337825Z tensor([13+13j, 14+14j, 15+15j, 16+16j]) # Rank 3 2025-08-26T19:56:09.2337969Z >>> output = torch.empty([4], dtype=torch.int64) 2025-08-26T19:56:09.2338111Z >>> dist.all_to_all_single(output, input) 2025-08-26T19:56:09.2338200Z >>> output 2025-08-26T19:56:09.2338384Z tensor([1+1j, 5+5j, 9+9j, 13+13j]) # Rank 0 2025-08-26T19:56:09.2338560Z tensor([2+2j, 6+6j, 10+10j, 14+14j]) # Rank 1 2025-08-26T19:56:09.2338738Z tensor([3+3j, 7+7j, 11+11j, 15+15j]) # Rank 2 2025-08-26T19:56:09.2338923Z tensor([4+4j, 8+8j, 12+12j, 16+16j]) # Rank 3 2025-08-26T19:56:09.2339006Z 2025-08-26T19:56:09.2339275Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2339353Z 2025-08-26T19:56:09.2339456Z warnings.warn(msg) 2025-08-26T19:56:09.2339605Z 2025-08-26T19:56:09.2339826Z --- Parse Warning: 53 / 146 --- 2025-08-26T19:56:09.2340793Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=all_to_all in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/distributed_c10d.py line=4646. 2025-08-26T19:56:09.2341061Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2341146Z 2025-08-26T19:56:09.2341570Z Scatters list of input tensors to all processes in a group and return gathered list of tensors in output list. 2025-08-26T19:56:09.2341653Z 2025-08-26T19:56:09.2341775Z Complex tensors are supported. 2025-08-26T19:56:09.2341856Z 2025-08-26T19:56:09.2341940Z Args: 2025-08-26T19:56:09.2342172Z output_tensor_list (list[Tensor]): List of tensors to be gathered one 2025-08-26T19:56:09.2342297Z per rank. 2025-08-26T19:56:09.2342545Z input_tensor_list (list[Tensor]): List of tensors to scatter one per rank. 2025-08-26T19:56:09.2342779Z group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:56:09.2342908Z the default process group will be used. 2025-08-26T19:56:09.2343116Z async_op (bool, optional): Whether this op should be an async op. 2025-08-26T19:56:09.2343199Z 2025-08-26T19:56:09.2343296Z Returns: 2025-08-26T19:56:09.2343435Z Async work handle, if async_op is set to True. 2025-08-26T19:56:09.2343590Z None, if not async_op or if not part of the group. 2025-08-26T19:56:09.2343682Z 2025-08-26T19:56:09.2343774Z .. warning:: 2025-08-26T19:56:09.2343939Z `all_to_all` is experimental and subject to change. 2025-08-26T19:56:09.2344019Z 2025-08-26T19:56:09.2344109Z Examples: 2025-08-26T19:56:09.2344246Z >>> # xdoctest: +SKIP("Undefined rank") 2025-08-26T19:56:09.2344365Z >>> input = torch.arange(4) + rank * 4 2025-08-26T19:56:09.2344481Z >>> input = list(input.chunk(4)) 2025-08-26T19:56:09.2344579Z >>> input 2025-08-26T19:56:09.2344752Z [tensor([0]), tensor([1]), tensor([2]), tensor([3])] # Rank 0 2025-08-26T19:56:09.2344928Z [tensor([4]), tensor([5]), tensor([6]), tensor([7])] # Rank 1 2025-08-26T19:56:09.2345098Z [tensor([8]), tensor([9]), tensor([10]), tensor([11])] # Rank 2 2025-08-26T19:56:09.2345267Z [tensor([12]), tensor([13]), tensor([14]), tensor([15])] # Rank 3 2025-08-26T19:56:09.2345465Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T19:56:09.2345581Z >>> dist.all_to_all(output, input) 2025-08-26T19:56:09.2345682Z >>> output 2025-08-26T19:56:09.2345845Z [tensor([0]), tensor([4]), tensor([8]), tensor([12])] # Rank 0 2025-08-26T19:56:09.2346009Z [tensor([1]), tensor([5]), tensor([9]), tensor([13])] # Rank 1 2025-08-26T19:56:09.2346185Z [tensor([2]), tensor([6]), tensor([10]), tensor([14])] # Rank 2 2025-08-26T19:56:09.2346379Z [tensor([3]), tensor([7]), tensor([11]), tensor([15])] # Rank 3 2025-08-26T19:56:09.2346471Z 2025-08-26T19:56:09.2346635Z >>> # Essentially, it is similar to following operation: 2025-08-26T19:56:09.2346736Z >>> scatter_list = input 2025-08-26T19:56:09.2346839Z >>> gather_list = output 2025-08-26T19:56:09.2346945Z >>> for i in range(world_size): 2025-08-26T19:56:09.2347184Z >>> dist.scatter(gather_list[i], scatter_list if i == rank else [], src=i) 2025-08-26T19:56:09.2347262Z 2025-08-26T19:56:09.2347350Z >>> input 2025-08-26T19:56:09.2347514Z tensor([0, 1, 2, 3, 4, 5]) # Rank 0 2025-08-26T19:56:09.2347671Z tensor([10, 11, 12, 13, 14, 15, 16, 17, 18]) # Rank 1 2025-08-26T19:56:09.2347839Z tensor([20, 21, 22, 23, 24]) # Rank 2 2025-08-26T19:56:09.2348002Z tensor([30, 31, 32, 33, 34, 35, 36]) # Rank 3 2025-08-26T19:56:09.2348124Z >>> input_splits 2025-08-26T19:56:09.2348253Z [2, 2, 1, 1] # Rank 0 2025-08-26T19:56:09.2348374Z [3, 2, 2, 2] # Rank 1 2025-08-26T19:56:09.2348510Z [2, 1, 1, 1] # Rank 2 2025-08-26T19:56:09.2348629Z [2, 2, 2, 1] # Rank 3 2025-08-26T19:56:09.2348756Z >>> output_splits 2025-08-26T19:56:09.2348887Z [2, 3, 2, 2] # Rank 0 2025-08-26T19:56:09.2349007Z [2, 2, 1, 2] # Rank 1 2025-08-26T19:56:09.2349137Z [1, 2, 1, 2] # Rank 2 2025-08-26T19:56:09.2349280Z [1, 2, 1, 1] # Rank 3 2025-08-26T19:56:09.2349416Z >>> input = list(input.split(input_splits)) 2025-08-26T19:56:09.2349510Z >>> input 2025-08-26T19:56:09.2349718Z [tensor([0, 1]), tensor([2, 3]), tensor([4]), tensor([5])] # Rank 0 2025-08-26T19:56:09.2349933Z [tensor([10, 11, 12]), tensor([13, 14]), tensor([15, 16]), tensor([17, 18])] # Rank 1 2025-08-26T19:56:09.2350138Z [tensor([20, 21]), tensor([22]), tensor([23]), tensor([24])] # Rank 2 2025-08-26T19:56:09.2350345Z [tensor([30, 31]), tensor([32, 33]), tensor([34, 35]), tensor([36])] # Rank 3 2025-08-26T19:56:09.2350451Z >>> output = ... 2025-08-26T19:56:09.2350567Z >>> dist.all_to_all(output, input) 2025-08-26T19:56:09.2350666Z >>> output 2025-08-26T19:56:09.2350871Z [tensor([0, 1]), tensor([10, 11, 12]), tensor([20, 21]), tensor([30, 31])] # Rank 0 2025-08-26T19:56:09.2351077Z [tensor([2, 3]), tensor([13, 14]), tensor([22]), tensor([32, 33])] # Rank 1 2025-08-26T19:56:09.2351292Z [tensor([4]), tensor([15, 16]), tensor([23]), tensor([34, 35])] # Rank 2 2025-08-26T19:56:09.2351496Z [tensor([5]), tensor([17, 18]), tensor([24]), tensor([36])] # Rank 3 2025-08-26T19:56:09.2351593Z 2025-08-26T19:56:09.2351757Z >>> # Another example with tensors of torch.cfloat type. 2025-08-26T19:56:09.2351861Z >>> input = torch.tensor( 2025-08-26T19:56:09.2352014Z ... [1 + 1j, 2 + 2j, 3 + 3j, 4 + 4j], dtype=torch.cfloat 2025-08-26T19:56:09.2352113Z ... ) + 4 * rank * (1 + 1j) 2025-08-26T19:56:09.2352238Z >>> input = list(input.chunk(4)) 2025-08-26T19:56:09.2352324Z >>> input 2025-08-26T19:56:09.2352542Z [tensor([1+1j]), tensor([2+2j]), tensor([3+3j]), tensor([4+4j])] # Rank 0 2025-08-26T19:56:09.2352765Z [tensor([5+5j]), tensor([6+6j]), tensor([7+7j]), tensor([8+8j])] # Rank 1 2025-08-26T19:56:09.2353018Z [tensor([9+9j]), tensor([10+10j]), tensor([11+11j]), tensor([12+12j])] # Rank 2 2025-08-26T19:56:09.2353252Z [tensor([13+13j]), tensor([14+14j]), tensor([15+15j]), tensor([16+16j])] # Rank 3 2025-08-26T19:56:09.2353436Z >>> output = list(torch.empty([4], dtype=torch.int64).chunk(4)) 2025-08-26T19:56:09.2353566Z >>> dist.all_to_all(output, input) 2025-08-26T19:56:09.2353652Z >>> output 2025-08-26T19:56:09.2353864Z [tensor([1+1j]), tensor([5+5j]), tensor([9+9j]), tensor([13+13j])] # Rank 0 2025-08-26T19:56:09.2354094Z [tensor([2+2j]), tensor([6+6j]), tensor([10+10j]), tensor([14+14j])] # Rank 1 2025-08-26T19:56:09.2354306Z [tensor([3+3j]), tensor([7+7j]), tensor([11+11j]), tensor([15+15j])] # Rank 2 2025-08-26T19:56:09.2354531Z [tensor([4+4j]), tensor([8+8j]), tensor([12+12j]), tensor([16+16j])] # Rank 3 2025-08-26T19:56:09.2354608Z 2025-08-26T19:56:09.2354689Z 2025-08-26T19:56:09.2354987Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2355066Z 2025-08-26T19:56:09.2355178Z warnings.warn(msg) 2025-08-26T19:56:09.2355260Z 2025-08-26T19:56:09.2355468Z --- Parse Warning: 54 / 146 --- 2025-08-26T19:56:09.2356350Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=__doc__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/launch.py line=2. 2025-08-26T19:56:09.2356645Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2356739Z 2025-08-26T19:56:09.2356861Z Module ``torch.distributed.launch``. 2025-08-26T19:56:09.2356943Z 2025-08-26T19:56:09.2357212Z ``torch.distributed.launch`` is a module that spawns up multiple distributed 2025-08-26T19:56:09.2357407Z training processes on each of the training nodes. 2025-08-26T19:56:09.2357502Z 2025-08-26T19:56:09.2357594Z .. warning:: 2025-08-26T19:56:09.2357677Z 2025-08-26T19:56:09.2357947Z This module is going to be deprecated in favor of :ref:`torchrun `. 2025-08-26T19:56:09.2358028Z 2025-08-26T19:56:09.2358270Z The utility can be used for single-node distributed training, in which one or 2025-08-26T19:56:09.2358524Z more processes per node will be spawned. The utility can be used for either 2025-08-26T19:56:09.2358745Z CPU training or GPU training. If the utility is used for GPU training, 2025-08-26T19:56:09.2359013Z each distributed process will be operating on a single GPU. This can achieve 2025-08-26T19:56:09.2359253Z well-improved single-node training performance. It can also be used in 2025-08-26T19:56:09.2359539Z multi-node distributed training, by spawning up multiple processes on each node 2025-08-26T19:56:09.2359775Z for well-improved multi-node distributed training performance as well. 2025-08-26T19:56:09.2360013Z This will especially be beneficial for systems with multiple Infiniband 2025-08-26T19:56:09.2360288Z interfaces that have direct-GPU support, since all of them can be utilized for 2025-08-26T19:56:09.2360407Z aggregated communication bandwidth. 2025-08-26T19:56:09.2360502Z 2025-08-26T19:56:09.2360740Z In both cases of single-node distributed training or multi-node distributed 2025-08-26T19:56:09.2360979Z training, this utility will launch the given number of processes per node 2025-08-26T19:56:09.2361226Z (``--nproc-per-node``). If used for GPU training, this number needs to be less 2025-08-26T19:56:09.2361451Z or equal to the number of GPUs on the current system (``nproc_per_node``), 2025-08-26T19:56:09.2361673Z and each process will be operating on a single GPU from *GPU 0 to 2025-08-26T19:56:09.2361780Z GPU (nproc_per_node - 1)*. 2025-08-26T19:56:09.2361863Z 2025-08-26T19:56:09.2361982Z **How to use this module:** 2025-08-26T19:56:09.2362093Z 2025-08-26T19:56:09.2362266Z 1. Single-Node multi-process distributed training 2025-08-26T19:56:09.2362349Z 2025-08-26T19:56:09.2362433Z :: 2025-08-26T19:56:09.2362527Z 2025-08-26T19:56:09.2362768Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T19:56:09.2362961Z YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 and all other 2025-08-26T19:56:09.2363100Z arguments of your training script) 2025-08-26T19:56:09.2363179Z 2025-08-26T19:56:09.2363405Z 2. Multi-Node multi-process distributed training: (e.g. two nodes) 2025-08-26T19:56:09.2363487Z 2025-08-26T19:56:09.2363569Z 2025-08-26T19:56:09.2363728Z Node 1: *(IP: 192.168.1.1, and has a free port: 1234)* 2025-08-26T19:56:09.2363806Z 2025-08-26T19:56:09.2363905Z :: 2025-08-26T19:56:09.2363985Z 2025-08-26T19:56:09.2364222Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T19:56:09.2364397Z --nnodes=2 --node-rank=0 --master-addr="192.168.1.1" 2025-08-26T19:56:09.2364641Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T19:56:09.2364810Z and all other arguments of your training script) 2025-08-26T19:56:09.2364889Z 2025-08-26T19:56:09.2364975Z Node 2: 2025-08-26T19:56:09.2365065Z 2025-08-26T19:56:09.2365144Z :: 2025-08-26T19:56:09.2365224Z 2025-08-26T19:56:09.2365473Z python -m torch.distributed.launch --nproc-per-node=NUM_GPUS_YOU_HAVE 2025-08-26T19:56:09.2365658Z --nnodes=2 --node-rank=1 --master-addr="192.168.1.1" 2025-08-26T19:56:09.2365880Z --master-port=1234 YOUR_TRAINING_SCRIPT.py (--arg1 --arg2 --arg3 2025-08-26T19:56:09.2366029Z and all other arguments of your training script) 2025-08-26T19:56:09.2366109Z 2025-08-26T19:56:09.2366285Z 3. To look up what optional arguments this module offers: 2025-08-26T19:56:09.2366399Z 2025-08-26T19:56:09.2366500Z :: 2025-08-26T19:56:09.2366577Z 2025-08-26T19:56:09.2366720Z python -m torch.distributed.launch --help 2025-08-26T19:56:09.2366813Z 2025-08-26T19:56:09.2366892Z 2025-08-26T19:56:09.2367007Z **Important Notices:** 2025-08-26T19:56:09.2367086Z 2025-08-26T19:56:09.2367276Z 1. This utility and multi-process distributed (single-node or 2025-08-26T19:56:09.2367540Z multi-node) GPU training currently only achieves the best performance using 2025-08-26T19:56:09.2367797Z the NCCL distributed backend. Thus NCCL backend is the recommended backend to 2025-08-26T19:56:09.2367909Z use for GPU training. 2025-08-26T19:56:09.2367989Z 2025-08-26T19:56:09.2368208Z 2. In your training program, you must parse the command-line argument: 2025-08-26T19:56:09.2368459Z ``--local-rank=LOCAL_PROCESS_RANK``, which will be provided by this module. 2025-08-26T19:56:09.2368691Z If your training program uses GPUs, you should ensure that your code only 2025-08-26T19:56:09.2368986Z runs on the GPU device of LOCAL_PROCESS_RANK. This can be done by: 2025-08-26T19:56:09.2369065Z 2025-08-26T19:56:09.2369177Z Parsing the local_rank argument 2025-08-26T19:56:09.2369273Z 2025-08-26T19:56:09.2369360Z :: 2025-08-26T19:56:09.2369439Z 2025-08-26T19:56:09.2369547Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2369640Z >>> import argparse 2025-08-26T19:56:09.2369782Z >>> parser = argparse.ArgumentParser() 2025-08-26T19:56:09.2369978Z >>> parser.add_argument("--local-rank", "--local_rank", type=int) 2025-08-26T19:56:09.2370091Z >>> args = parser.parse_args() 2025-08-26T19:56:09.2370182Z 2025-08-26T19:56:09.2370310Z Set your device to local rank using either 2025-08-26T19:56:09.2370404Z 2025-08-26T19:56:09.2370488Z :: 2025-08-26T19:56:09.2370568Z 2025-08-26T19:56:09.2370782Z >>> torch.cuda.set_device(args.local_rank) # before your code runs 2025-08-26T19:56:09.2370915Z 2025-08-26T19:56:09.2370999Z or 2025-08-26T19:56:09.2371091Z 2025-08-26T19:56:09.2371176Z :: 2025-08-26T19:56:09.2371271Z 2025-08-26T19:56:09.2371411Z >>> with torch.cuda.device(args.local_rank): 2025-08-26T19:56:09.2371513Z >>> # your code to run 2025-08-26T19:56:09.2371614Z >>> ... 2025-08-26T19:56:09.2371698Z 2025-08-26T19:56:09.2371819Z .. versionchanged:: 2.0.0 2025-08-26T19:56:09.2371904Z 2025-08-26T19:56:09.2372160Z The launcher will passes the ``--local-rank=`` argument to your script. 2025-08-26T19:56:09.2372423Z From PyTorch 2.0.0 onwards, the dashed ``--local-rank`` is preferred over the 2025-08-26T19:56:09.2372568Z previously used underscored ``--local_rank``. 2025-08-26T19:56:09.2372662Z 2025-08-26T19:56:09.2372903Z For backward compatibility, it may be necessary for users to handle both 2025-08-26T19:56:09.2373179Z cases in their argument parsing code. This means including both ``"--local-rank"`` 2025-08-26T19:56:09.2373442Z and ``"--local_rank"`` in the argument parser. If only ``"--local_rank"`` is 2025-08-26T19:56:09.2373700Z provided, the launcher will trigger an error: "error: unrecognized arguments: 2025-08-26T19:56:09.2373946Z --local-rank=". For training code that only supports PyTorch 2.0.0+, 2025-08-26T19:56:09.2374097Z including ``"--local-rank"`` should be sufficient. 2025-08-26T19:56:09.2374179Z 2025-08-26T19:56:09.2374429Z 3. In your training program, you are supposed to call the following function 2025-08-26T19:56:09.2374701Z at the beginning to start the distributed backend. It is strongly recommended 2025-08-26T19:56:09.2374938Z that ``init_method=env://``. Other init methods (e.g. ``tcp://``) may work, 2025-08-26T19:56:09.2375131Z but ``env://`` is the one that is officially supported by this module. 2025-08-26T19:56:09.2375212Z 2025-08-26T19:56:09.2375307Z :: 2025-08-26T19:56:09.2375415Z 2025-08-26T19:56:09.2375634Z >>> torch.distributed.init_process_group(backend='YOUR BACKEND', 2025-08-26T19:56:09.2375773Z >>> init_method='env://') 2025-08-26T19:56:09.2375852Z 2025-08-26T19:56:09.2376104Z 4. In your training program, you can either use regular distributed functions 2025-08-26T19:56:09.2376343Z or use :func:`torch.nn.parallel.DistributedDataParallel` module. If your 2025-08-26T19:56:09.2376566Z training program uses GPUs for training and you would like to use 2025-08-26T19:56:09.2376760Z :func:`torch.nn.parallel.DistributedDataParallel` module, 2025-08-26T19:56:09.2376865Z here is how to configure it. 2025-08-26T19:56:09.2376957Z 2025-08-26T19:56:09.2377038Z :: 2025-08-26T19:56:09.2377116Z 2025-08-26T19:56:09.2377325Z >>> model = torch.nn.parallel.DistributedDataParallel(model, 2025-08-26T19:56:09.2377465Z >>> device_ids=[args.local_rank], 2025-08-26T19:56:09.2377620Z >>> output_device=args.local_rank) 2025-08-26T19:56:09.2377701Z 2025-08-26T19:56:09.2377962Z Please ensure that ``device_ids`` argument is set to be the only GPU device id 2025-08-26T19:56:09.2378198Z that your code will be operating on. This is generally the local rank of the 2025-08-26T19:56:09.2378444Z process. In other words, the ``device_ids`` needs to be ``[args.local_rank]``, 2025-08-26T19:56:09.2378673Z and ``output_device`` needs to be ``args.local_rank`` in order to use this 2025-08-26T19:56:09.2378762Z utility 2025-08-26T19:56:09.2378855Z 2025-08-26T19:56:09.2379101Z 5. Another way to pass ``local_rank`` to the subprocesses via environment variable 2025-08-26T19:56:09.2379316Z ``LOCAL_RANK``. This behavior is enabled when you launch the script with 2025-08-26T19:56:09.2379553Z ``--use-env=True``. You must adjust the subprocess example above to replace 2025-08-26T19:56:09.2379780Z ``args.local_rank`` with ``os.environ['LOCAL_RANK']``; the launcher 2025-08-26T19:56:09.2379967Z will not pass ``--local-rank`` when you specify this flag. 2025-08-26T19:56:09.2380048Z 2025-08-26T19:56:09.2380138Z .. warning:: 2025-08-26T19:56:09.2380230Z 2025-08-26T19:56:09.2380433Z ``local_rank`` is NOT globally unique: it is only unique per process 2025-08-26T19:56:09.2380623Z on a machine. Thus, don't use it to decide if you should, e.g., 2025-08-26T19:56:09.2380759Z write to a networked filesystem. See 2025-08-26T19:56:09.2380983Z https://github.com/pytorch/pytorch/issues/12042 for an example of 2025-08-26T19:56:09.2381161Z how things can go wrong if you don't do this correctly. 2025-08-26T19:56:09.2381241Z 2025-08-26T19:56:09.2381325Z 2025-08-26T19:56:09.2381417Z 2025-08-26T19:56:09.2381493Z 2025-08-26T19:56:09.2381764Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2381848Z 2025-08-26T19:56:09.2381974Z warnings.warn(msg) 2025-08-26T19:56:09.2382071Z 2025-08-26T19:56:09.2382288Z --- Parse Warning: 55 / 146 --- 2025-08-26T19:56:09.2383373Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=init_from_local_shards in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/__init__.py line=361. 2025-08-26T19:56:09.2383639Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2383755Z 2025-08-26T19:56:09.2384016Z Creates an :class:`ShardedTensor` from local shards and the global metadata. 2025-08-26T19:56:09.2384164Z Needs to be called on all ranks in an SPMD fashion. 2025-08-26T19:56:09.2384260Z 2025-08-26T19:56:09.2384345Z Args: 2025-08-26T19:56:09.2384652Z local_shards (List[:class `torch.distributed._shard.sharded_tensor.Shard`]): A list 2025-08-26T19:56:09.2384850Z of shards that represent the local shards on this rank. 2025-08-26T19:56:09.2385084Z global_size (int...): a list, tuple, or `torch.Size` of integers defining the 2025-08-26T19:56:09.2385222Z shape of the overall sharded tensor. 2025-08-26T19:56:09.2385305Z 2025-08-26T19:56:09.2385393Z Keyword args: 2025-08-26T19:56:09.2385671Z process_group (ProcessGroup, optional): The process group to work on. If None, 2025-08-26T19:56:09.2385799Z the default process group will be used. 2025-08-26T19:56:09.2385991Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T19:56:09.2386201Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T19:56:09.2386401Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T19:56:09.2386510Z Default: ``False``. 2025-08-26T19:56:09.2386591Z 2025-08-26T19:56:09.2386690Z Returns: 2025-08-26T19:56:09.2386845Z A :class:`ShardedTensor` object handle on this rank 2025-08-26T19:56:09.2386928Z 2025-08-26T19:56:09.2387021Z 2025-08-26T19:56:09.2387110Z Examples: 2025-08-26T19:56:09.2387381Z Suppose we want construct a sharded tensor on two ranks, global size = (10, 5), 2025-08-26T19:56:09.2387568Z each shard have a (5, 5) local tensor, we can do it like below: 2025-08-26T19:56:09.2387647Z 2025-08-26T19:56:09.2387750Z on rank 0: 2025-08-26T19:56:09.2387873Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T19:56:09.2388008Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T19:56:09.2388114Z >>> shard_offsets=[0, 0], 2025-08-26T19:56:09.2388217Z >>> shard_lengths=[5, 5], 2025-08-26T19:56:09.2388337Z >>> placement="rank:0/cuda:0" 2025-08-26T19:56:09.2388421Z >>> ) 2025-08-26T19:56:09.2388615Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T19:56:09.2388856Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T19:56:09.2388936Z 2025-08-26T19:56:09.2389034Z on rank 1: 2025-08-26T19:56:09.2389157Z >>> # xdoctest: +SKIP("not distributed") 2025-08-26T19:56:09.2389281Z >>> local_shard_metadata = ShardMetadata( 2025-08-26T19:56:09.2389396Z >>> shard_offsets=[5, 0], 2025-08-26T19:56:09.2389496Z >>> shard_lengths=[5, 5], 2025-08-26T19:56:09.2389616Z >>> placement="rank:1/cuda:1" 2025-08-26T19:56:09.2389701Z >>> ) 2025-08-26T19:56:09.2389897Z >>> local_shards = [Shard(torch.randn(5, 5), local_shard_metadata)] 2025-08-26T19:56:09.2390105Z >>> sharded_tensor = init_from_local_shards(local_shards, [10, 5]) 2025-08-26T19:56:09.2390182Z 2025-08-26T19:56:09.2390450Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2390533Z 2025-08-26T19:56:09.2390629Z warnings.warn(msg) 2025-08-26T19:56:09.2390733Z 2025-08-26T19:56:09.2390950Z --- Parse Warning: 56 / 146 --- 2025-08-26T19:56:09.2392081Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor._init_from_local_tensor in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=835. 2025-08-26T19:56:09.2392349Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2392428Z 2025-08-26T19:56:09.2392732Z Initialize a ShardedTensor given only one local tensor, global sharded tensor 2025-08-26T19:56:09.2392848Z size and sharding spec on each rank. 2025-08-26T19:56:09.2392942Z 2025-08-26T19:56:09.2393029Z Args: 2025-08-26T19:56:09.2393257Z local_tensor (Tensor): Single tensor of local shard stored in each rank. 2025-08-26T19:56:09.2393562Z sharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): 2025-08-26T19:56:09.2393734Z The specification describing how to shard the Tensor. 2025-08-26T19:56:09.2393916Z global_size (Sequence[int]): Size of the sharded tensor. 2025-08-26T19:56:09.2394173Z process_group (ProcessGroup, optional): The process group to aggregate on. 2025-08-26T19:56:09.2394267Z Default: None 2025-08-26T19:56:09.2394451Z init_rrefs (bool, optional): Whether or not to initialize 2025-08-26T19:56:09.2394658Z :class:`torch.distributed.rpc.RRef`s pointing to remote shards. 2025-08-26T19:56:09.2394863Z Need to initialize the RPC Framework if specified as ``True``. 2025-08-26T19:56:09.2394961Z Default: ``False``. 2025-08-26T19:56:09.2395038Z 2025-08-26T19:56:09.2395138Z Returns: 2025-08-26T19:56:09.2395381Z A :class:`ShardedTensor` sharded based on the given sharding_spec with local 2025-08-26T19:56:09.2395515Z tensor stored in the current rank. 2025-08-26T19:56:09.2395598Z 2025-08-26T19:56:09.2395682Z Examples: 2025-08-26T19:56:09.2395799Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2395933Z >>> # All tensors below are of torch.int64 type. 2025-08-26T19:56:09.2396063Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:56:09.2396239Z >>> tensor = torch.arange(2, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T19:56:09.2396439Z >>> local_tensor = torch.unsqueeze(torch.cat([tensor, tensor + 2])) 2025-08-26T19:56:09.2396545Z >>> local_tensor 2025-08-26T19:56:09.2396644Z tensor([[1, 2, 3, 4]]) # Rank 0 2025-08-26T19:56:09.2396754Z tensor([[3, 4, 5, 6]]) # Rank 1 2025-08-26T19:56:09.2396851Z >>> sharding_dim = 0 2025-08-26T19:56:09.2396971Z >>> sharding_spec = ChunkShardingSpec( 2025-08-26T19:56:09.2397083Z dim=sharding_dim, 2025-08-26T19:56:09.2397176Z placements=[ 2025-08-26T19:56:09.2397273Z "rank:0/cuda:0", 2025-08-26T19:56:09.2397413Z "rank:1/cuda:1", 2025-08-26T19:56:09.2397494Z ], 2025-08-26T19:56:09.2397590Z ) 2025-08-26T19:56:09.2397720Z >>> st = ShardedTensor._init_from_local_tensor( 2025-08-26T19:56:09.2397844Z ... local_tensor, sharding_spec, [2, 4] 2025-08-26T19:56:09.2397937Z ... ) 2025-08-26T19:56:09.2398019Z >>> st 2025-08-26T19:56:09.2398126Z ShardedTensor( 2025-08-26T19:56:09.2398232Z ShardedTensorMetadata( 2025-08-26T19:56:09.2398329Z shards_metadata=[ 2025-08-26T19:56:09.2398618Z ShardMetadata(shard_offsets=[0, 0], shard_sizes=[1, 4], placement=rank:0/cuda:0), 2025-08-26T19:56:09.2398884Z ShardMetadata(shard_offsets=[1, 0], shard_sizes=[1, 4], placement=rank:1/cuda:1), 2025-08-26T19:56:09.2398978Z ], 2025-08-26T19:56:09.2399081Z size=torch.Size([2, 4]) 2025-08-26T19:56:09.2399160Z ) 2025-08-26T19:56:09.2399273Z >>> st.local_tensor() 2025-08-26T19:56:09.2399374Z tensor([1, 2, 3, 4]) # Rank 0 2025-08-26T19:56:09.2399513Z tensor([3, 4, 5, 6]) # Rank 1 2025-08-26T19:56:09.2399589Z 2025-08-26T19:56:09.2399861Z Warning: This API is experimental and subject to change. It lacks of a fully across 2025-08-26T19:56:09.2400115Z rank validations, and we only validate the local shard on the current rank. 2025-08-26T19:56:09.2400329Z We fully rely on the user to ensure local tensor is sharded based on the 2025-08-26T19:56:09.2400435Z sharding spec. 2025-08-26T19:56:09.2400512Z 2025-08-26T19:56:09.2400795Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2400891Z 2025-08-26T19:56:09.2400987Z warnings.warn(msg) 2025-08-26T19:56:09.2401068Z 2025-08-26T19:56:09.2401272Z --- Parse Warning: 57 / 146 --- 2025-08-26T19:56:09.2402381Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardedTensor.reshard in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharded_tensor/api.py line=1076. 2025-08-26T19:56:09.2402666Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2402746Z 2025-08-26T19:56:09.2403017Z Reshard a sharded tensor given the ``resharding_spec``. For now, we only support 2025-08-26T19:56:09.2403110Z single local shard. 2025-08-26T19:56:09.2403191Z 2025-08-26T19:56:09.2403431Z If ``resharding_spec`` is same as the original one, this becomes a no-op. 2025-08-26T19:56:09.2403675Z If only ``resharding_spec`` shares the same sharding dim with the original one, 2025-08-26T19:56:09.2403794Z we swap local shards directly. 2025-08-26T19:56:09.2404054Z For more generic cases, we merge different shards across different ranks and split 2025-08-26T19:56:09.2404309Z the local shards based on the ``resharding_spec`` via `all_to_all` collective API. 2025-08-26T19:56:09.2404405Z 2025-08-26T19:56:09.2404490Z Args: 2025-08-26T19:56:09.2404801Z resharding_spec (:class:`torch.distributed._shard.sharding_spec.ShardingSpec`): The 2025-08-26T19:56:09.2404967Z specification describing how the tensor is sharded. 2025-08-26T19:56:09.2405050Z 2025-08-26T19:56:09.2405149Z Returns: 2025-08-26T19:56:09.2405355Z A :class:`ShardedTensor` object whose local shards are resharded. 2025-08-26T19:56:09.2405436Z 2025-08-26T19:56:09.2405532Z Examples: 2025-08-26T19:56:09.2405632Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2405767Z >>> # We have 2 process groups, 2 ranks. 2025-08-26T19:56:09.2405940Z >>> tensor = torch.arange(4, dtype=torch.int64) + 1 + 2 * rank 2025-08-26T19:56:09.2406062Z >>> tensor = torch.stack([tensor, tensor]) 2025-08-26T19:56:09.2406157Z >>> tensor 2025-08-26T19:56:09.2406280Z tensor([[1, 2, 3, 4], [1, 2, 3, 4]]) # Rank 0 2025-08-26T19:56:09.2406443Z tensor([[3, 4, 5, 6], [3, 4, 5, 6]]) # Rank 1 2025-08-26T19:56:09.2406559Z tensor([[5, 6, 7, 8], [5, 6, 7, 8]]) # Rank 2 2025-08-26T19:56:09.2406685Z tensor([[7, 8, 9, 10], [7, 8, 9, 10]]) # Rank 3 2025-08-26T19:56:09.2406792Z >>> sharding_dim = 0 2025-08-26T19:56:09.2406904Z >>> spec = ChunkShardingSpec( 2025-08-26T19:56:09.2407013Z dim=sharding_dim, 2025-08-26T19:56:09.2407107Z placements=[ 2025-08-26T19:56:09.2407208Z "rank:0/cuda:0", 2025-08-26T19:56:09.2407312Z "rank:1/cuda:1", 2025-08-26T19:56:09.2407405Z "rank:2/cuda:2", 2025-08-26T19:56:09.2407508Z "rank:3/cuda:3", 2025-08-26T19:56:09.2407588Z ], 2025-08-26T19:56:09.2407670Z ) 2025-08-26T19:56:09.2407787Z >>> current_offsets = [0] * 2 2025-08-26T19:56:09.2407892Z >>> current_offsets[0] = rank * 2 2025-08-26T19:56:09.2408011Z >>> shard_metadata = ShardMetadata( 2025-08-26T19:56:09.2408207Z shard_offsets=copy.deepcopy(current_offsets), 2025-08-26T19:56:09.2408319Z shard_sizes=tensor.size(), 2025-08-26T19:56:09.2408455Z placement=spec.placements[rank], 2025-08-26T19:56:09.2408537Z ) 2025-08-26T19:56:09.2408633Z >>> local_shards = [ 2025-08-26T19:56:09.2408727Z Shard( 2025-08-26T19:56:09.2408924Z tensor=tensor, 2025-08-26T19:56:09.2409049Z metadata=shard_metadata, 2025-08-26T19:56:09.2409131Z ) 2025-08-26T19:56:09.2409246Z ] 2025-08-26T19:56:09.2409491Z >>> st = ShardedTensor._init_from_local_shards(local_shards, tensor.size()) 2025-08-26T19:56:09.2409589Z >>> sharding_dim = 1 2025-08-26T19:56:09.2409725Z >>> resharding_spec = ChunkShardingSpec( 2025-08-26T19:56:09.2409823Z dim=sharding_dim, 2025-08-26T19:56:09.2409950Z placements=[ 2025-08-26T19:56:09.2410058Z "rank:0/cuda:0", 2025-08-26T19:56:09.2410154Z "rank:1/cuda:1", 2025-08-26T19:56:09.2410259Z "rank:2/cuda:2", 2025-08-26T19:56:09.2410351Z "rank:3/cuda:3", 2025-08-26T19:56:09.2410434Z ], 2025-08-26T19:56:09.2410524Z ) 2025-08-26T19:56:09.2410635Z >>> st.reshard(resharding_spec) 2025-08-26T19:56:09.2410754Z >>> tensor = st.local_shards()[0].tensor 2025-08-26T19:56:09.2410845Z >>> tensor 2025-08-26T19:56:09.2410997Z tensor([[1], [1], [3], [3], [5], [5], [7], [7]]) # Rank 0 2025-08-26T19:56:09.2411144Z tensor([[2], [2], [4], [4], [6], [6], [8], [8]]) # Rank 1 2025-08-26T19:56:09.2411281Z tensor([[3], [3], [5], [5], [7], [7], [9], [9]]) # Rank 2 2025-08-26T19:56:09.2411423Z tensor([[4], [4], [6], [6], [8], [8], [10], [10]]) # Rank 3 2025-08-26T19:56:09.2411512Z 2025-08-26T19:56:09.2411772Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2411862Z 2025-08-26T19:56:09.2411965Z warnings.warn(msg) 2025-08-26T19:56:09.2412046Z 2025-08-26T19:56:09.2412260Z --- Parse Warning: 58 / 146 --- 2025-08-26T19:56:09.2413273Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ShardingPlan in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/_shard/sharding_plan/api.py line=12. 2025-08-26T19:56:09.2413549Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2413635Z 2025-08-26T19:56:09.2413859Z Representation of a sharding plan, describes how to shard a module 2025-08-26T19:56:09.2414146Z across hosts. `plan` is used to shard module parameters according to the spec provided, 2025-08-26T19:56:09.2414439Z `output_plan` and `return_local_tensor` are optional, they are used to specify the output 2025-08-26T19:56:09.2414731Z layout of a module with a spec, and when to convert back to data parallel fashion. 2025-08-26T19:56:09.2414814Z 2025-08-26T19:56:09.2414898Z Args: 2025-08-26T19:56:09.2415180Z plan (Dict[str, Union[:class:`torch.distributed._shard.sharding_spec.ShardingSpec`, 2025-08-26T19:56:09.2415350Z :class:`torch.distributed._shard.sharder.Sharder`]): 2025-08-26T19:56:09.2415635Z a dict describes how to shard a module, there're currently two ways to shard a module: 2025-08-26T19:56:09.2415898Z 1. directly shard a module parameter by a `ShardingSpec`, keyed by the name of 2025-08-26T19:56:09.2416037Z a parameter to a `ShardingSpec`. 2025-08-26T19:56:09.2416301Z 2. shard a submodule by applying a `Sharder` on it, keyed by the name of a module 2025-08-26T19:56:09.2416409Z to a `Sharder` object. 2025-08-26T19:56:09.2416761Z output_plan (Dict[str, :class:`torch.distributed._shard.sharding_spec.ShardingSpec`), optional): 2025-08-26T19:56:09.2417058Z a dict specifies the layout of a module's output which produces a ShardedTensor, 2025-08-26T19:56:09.2417312Z keyed by the name of module to ShardingSpec("" in key means the root module). 2025-08-26T19:56:09.2417410Z Default: `None` 2025-08-26T19:56:09.2417670Z return_local_tensor (List[str], optional): a list of string, each element enables 2025-08-26T19:56:09.2417929Z a module's sharded output to be returned as a Tensor from its local shards to 2025-08-26T19:56:09.2418209Z ensure further processing in a data parallel fashion. ("" in list means the 2025-08-26T19:56:09.2418319Z root module). 2025-08-26T19:56:09.2418414Z Default: None 2025-08-26T19:56:09.2418502Z Example: 2025-08-26T19:56:09.2418808Z Suppose we want to shard a module with two linear layers and then run it with DDP, we also 2025-08-26T19:56:09.2419128Z want to convert the output of the second linear layer back to DDP, we can do it as follows: 2025-08-26T19:56:09.2419229Z 2025-08-26T19:56:09.2419408Z >>> # xdoctest: +REQUIRES(module:torch._C._distributed_c10d) 2025-08-26T19:56:09.2419522Z >>> class MyModule(nn.Module): 2025-08-26T19:56:09.2419652Z >>> def __init__(self) -> None: 2025-08-26T19:56:09.2419756Z >>> super().__init__() 2025-08-26T19:56:09.2419878Z >>> self.fc1 = nn.Linear() 2025-08-26T19:56:09.2419985Z >>> self.gelu = nn.GELU() 2025-08-26T19:56:09.2420091Z >>> self.fc2 = nn.Linear() 2025-08-26T19:56:09.2420218Z >>> self.relu = nn.Linear() 2025-08-26T19:56:09.2420305Z >>> 2025-08-26T19:56:09.2420428Z >>> def forward(self, input): 2025-08-26T19:56:09.2420607Z >>> return self.relu(self.fc2(self.gelu(self.fc1(input)))) 2025-08-26T19:56:09.2420691Z 2025-08-26T19:56:09.2420789Z 2025-08-26T19:56:09.2420930Z >>> # xdoctest: +SKIP("Undefined spec1, spec2) 2025-08-26T19:56:09.2421063Z >>> sharding_plan = ShardingPlan( 2025-08-26T19:56:09.2421151Z >>> plan={ 2025-08-26T19:56:09.2421255Z >>> "fc1.weight": spec1, 2025-08-26T19:56:09.2421374Z >>> "fc2.weight": spec2 2025-08-26T19:56:09.2421458Z >>> }, 2025-08-26T19:56:09.2421559Z >>> output_plan={ 2025-08-26T19:56:09.2421672Z >>> "fc2": output_spec 2025-08-26T19:56:09.2421757Z >>> }, 2025-08-26T19:56:09.2421880Z >>> return_local_tensor=["fc2"] 2025-08-26T19:56:09.2421964Z >>> ) 2025-08-26T19:56:09.2422050Z 2025-08-26T19:56:09.2422322Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2422406Z 2025-08-26T19:56:09.2422518Z warnings.warn(msg) 2025-08-26T19:56:09.2422598Z 2025-08-26T19:56:09.2422792Z --- Parse Warning: 59 / 146 --- 2025-08-26T19:56:09.2423942Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=post_localSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/post_localSGD_hook.py line=72. 2025-08-26T19:56:09.2424247Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2424339Z 2025-08-26T19:56:09.2424450Z Run post-localSGD algorithm. 2025-08-26T19:56:09.2424534Z 2025-08-26T19:56:09.2424787Z This DDP communication hook is used for running post-localSGD algorithm, 2025-08-26T19:56:09.2424951Z by combining with a model averaging component (e.g., 2025-08-26T19:56:09.2425301Z :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager`) 2025-08-26T19:56:09.2425417Z that runs after the optimizer step. 2025-08-26T19:56:09.2425497Z 2025-08-26T19:56:09.2425596Z Args: 2025-08-26T19:56:09.2425826Z state (PostLocalSGDState): State information to run post-localSGD. 2025-08-26T19:56:09.2426153Z Users mainly need to tune ``start_localSGD_iter`` to determine when to start local SGD. 2025-08-26T19:56:09.2426583Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T19:56:09.2426837Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T19:56:09.2427005Z only exactly one tensor is stored in this bucket. 2025-08-26T19:56:09.2427087Z 2025-08-26T19:56:09.2427185Z Returns: 2025-08-26T19:56:09.2427461Z Future handler of the communication, which updates the gradients in place. 2025-08-26T19:56:09.2427543Z 2025-08-26T19:56:09.2427652Z Example:: 2025-08-26T19:56:09.2427752Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2428025Z >>> state = PostLocalSGDState(process_group=process_group, subgroup=subgroup, 2025-08-26T19:56:09.2428219Z start_localSGD_iter=10) 2025-08-26T19:56:09.2428400Z >>> ddp_model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:56:09.2428756Z >>> # Also need to establish a model averaging module and run model averaging after ``optimizer.step()``. 2025-08-26T19:56:09.2429110Z >>> # Please refer to the examples in ``torch.distributed.algorithms.model_averaging.averagers`` module. 2025-08-26T19:56:09.2429210Z 2025-08-26T19:56:09.2429467Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2429549Z 2025-08-26T19:56:09.2429663Z warnings.warn(msg) 2025-08-26T19:56:09.2429744Z 2025-08-26T19:56:09.2429950Z --- Parse Warning: 60 / 146 --- 2025-08-26T19:56:09.2431056Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=powerSGD_hook in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/ddp_comm_hooks/powerSGD_hook.py line=342. 2025-08-26T19:56:09.2431326Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2431420Z 2025-08-26T19:56:09.2431534Z Implement PowerSGD algorithm. 2025-08-26T19:56:09.2431628Z 2025-08-26T19:56:09.2431860Z This DDP communication hook implements PowerSGD gradient compression 2025-08-26T19:56:09.2432099Z algorithm described in the `paper `_. 2025-08-26T19:56:09.2432359Z Once gradient tensors are aggregated across all workers, this hook applies 2025-08-26T19:56:09.2432467Z compression as follows: 2025-08-26T19:56:09.2432558Z 2025-08-26T19:56:09.2433008Z 1. Views the input flattened 1D gradient tensor as a list of per-parameter tensors, and divides all the tensors into two groups: 2025-08-26T19:56:09.2433091Z 2025-08-26T19:56:09.2433538Z 1.1 The tensors that should be compressed before allreduce, because the compression can give enough saving in bandwidth. 2025-08-26T19:56:09.2433649Z 2025-08-26T19:56:09.2434081Z 1.2 Rest of the tensors will be directly allreduced without compression, including all the vector tensors (for biases). 2025-08-26T19:56:09.2434161Z 2025-08-26T19:56:09.2434274Z 2. Handles uncompressed tensors: 2025-08-26T19:56:09.2434370Z 2025-08-26T19:56:09.2434899Z 2.1. Allocate contiguous memory for those uncompressed tensors, and allreduces all the uncompressed tensors as a batch, without compression; 2025-08-26T19:56:09.2434995Z 2025-08-26T19:56:09.2435345Z 2.2. Copies the individual uncompressed tensors from the contiguous memory back to the input tensor. 2025-08-26T19:56:09.2435426Z 2025-08-26T19:56:09.2435679Z 3. Handles the tensors that should be compressed by PowerSGD compression: 2025-08-26T19:56:09.2435763Z 2025-08-26T19:56:09.2436018Z 3.1. For each tensor M, creates two low-rank tensors P and Q for decomposing M, 2025-08-26T19:56:09.2436336Z such that M = PQ^T, where Q is initialized from a standard normal distribution and orthogonalized; 2025-08-26T19:56:09.2436446Z 2025-08-26T19:56:09.2436609Z 3.2. Computes each P in Ps, which is equal to MQ; 2025-08-26T19:56:09.2436690Z 2025-08-26T19:56:09.2436815Z 3.3. Allreduces Ps as a batch; 2025-08-26T19:56:09.2436896Z 2025-08-26T19:56:09.2437012Z 3.4. Orthogonalizes each P in Ps; 2025-08-26T19:56:09.2437108Z 2025-08-26T19:56:09.2437306Z 3.5. Computes each Q in Qs, which is approximately equal to M^TP; 2025-08-26T19:56:09.2437611Z 2025-08-26T19:56:09.2437807Z 3.6. Allreduces Qs as a batch; 2025-08-26T19:56:09.2437892Z 2025-08-26T19:56:09.2438211Z 3.7. Computes each M among all the compressed tensors, which is approximately equal to PQ^T. 2025-08-26T19:56:09.2438295Z 2025-08-26T19:56:09.2438718Z Note that this communication hook enforces vanilla allreduce for the first ``state.start_powerSGD_iter`` iterations. 2025-08-26T19:56:09.2439063Z This not only gives the user more control over the tradeoff between speedup and accuracy, 2025-08-26T19:56:09.2439511Z but also helps abstract away some complexity of the internal optimization of DDP for future communication hook developers. 2025-08-26T19:56:09.2439611Z 2025-08-26T19:56:09.2439699Z Args: 2025-08-26T19:56:09.2440158Z state (PowerSGDState): State information to configure the compression rate and support error feedback, warm start, etc. 2025-08-26T19:56:09.2440522Z To tune the compression configs, mainly need to tune ``matrix_approximation_rank``, ``start_powerSGD_iter`` 2025-08-26T19:56:09.2440637Z and ``min_compression_rate``. 2025-08-26T19:56:09.2441077Z bucket (dist.GradBucket): Bucket that stores a 1D flattened gradient tensor that batches multiple per-variable tensors. 2025-08-26T19:56:09.2441331Z Note that since DDP comm hook only supports single process single device mode, 2025-08-26T19:56:09.2441500Z only exactly one tensor is stored in this bucket. 2025-08-26T19:56:09.2441584Z 2025-08-26T19:56:09.2441671Z Returns: 2025-08-26T19:56:09.2441932Z Future handler of the communication, which updates the gradients in place. 2025-08-26T19:56:09.2442014Z 2025-08-26T19:56:09.2442119Z Example:: 2025-08-26T19:56:09.2442217Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2442497Z >>> state = PowerSGDState(process_group=process_group, matrix_approximation_rank=1, 2025-08-26T19:56:09.2442673Z start_powerSGD_iter=10, min_compression_rate=0.5) 2025-08-26T19:56:09.2442836Z >>> ddp_model.register_comm_hook(state, powerSGD_hook) 2025-08-26T19:56:09.2442931Z 2025-08-26T19:56:09.2443188Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2443269Z 2025-08-26T19:56:09.2443379Z warnings.warn(msg) 2025-08-26T19:56:09.2443461Z 2025-08-26T19:56:09.2443671Z --- Parse Warning: 61 / 146 --- 2025-08-26T19:56:09.2444870Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PeriodicModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/averagers.py line=38. 2025-08-26T19:56:09.2445140Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2445235Z 2025-08-26T19:56:09.2445429Z Averages parameters periodically after the warm-up stage. 2025-08-26T19:56:09.2445522Z 2025-08-26T19:56:09.2445788Z This can be used for running `post-local SGD `_, 2025-08-26T19:56:09.2445986Z by running :class:`~torch.nn.DistributedDataParallel` (DDP) 2025-08-26T19:56:09.2446241Z using the subgroups created by :meth:`~torch.distributed.new_subgroups`. 2025-08-26T19:56:09.2446322Z 2025-08-26T19:56:09.2446419Z Args: 2025-08-26T19:56:09.2446592Z period (int): The number of steps per model averaging. 2025-08-26T19:56:09.2446910Z Usually the period should be greater than ``1`` to reduce the communication cost. 2025-08-26T19:56:09.2447056Z Otherwise, only DDP needs to be used. 2025-08-26T19:56:09.2447267Z warmup_steps (int): The number of warm-up steps. During this stage, 2025-08-26T19:56:09.2447403Z model averaging is skipped. 2025-08-26T19:56:09.2447593Z process_group: The process group to be used for all-reduce. 2025-08-26T19:56:09.2447763Z If ``None``, the default process group, which 2025-08-26T19:56:09.2447971Z is created by :func:`torch.distributed.init_process_group`, 2025-08-26T19:56:09.2448095Z will be used. (default: ``None``) 2025-08-26T19:56:09.2448194Z 2025-08-26T19:56:09.2448288Z Example:: 2025-08-26T19:56:09.2448372Z 2025-08-26T19:56:09.2448544Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2448645Z >>> import torch 2025-08-26T19:56:09.2448843Z >>> import torch.distributed as dist 2025-08-26T19:56:09.2449175Z >>> import torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook as post_localSGD 2025-08-26T19:56:09.2449450Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T19:56:09.2449568Z >>> import torch.nn as nn 2025-08-26T19:56:09.2449655Z >>> 2025-08-26T19:56:09.2449847Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T19:56:09.2449961Z >>> torch.cuda.set_device(rank) 2025-08-26T19:56:09.2450095Z >>> module = nn.Linear(1, 1, bias=False).cuda() 2025-08-26T19:56:09.2450264Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T19:56:09.2450405Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T19:56:09.2450502Z >>> ) 2025-08-26T19:56:09.2450651Z >>> # Register a post-localSGD communication hook. 2025-08-26T19:56:09.2450957Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T19:56:09.2451136Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:56:09.2451221Z >>> 2025-08-26T19:56:09.2451509Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T19:56:09.2451668Z >>> # After 100 steps, run model averaging every 4 steps. 2025-08-26T19:56:09.2451994Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T19:56:09.2452266Z >>> averager = averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T19:56:09.2452375Z >>> for step in range(0, 200): 2025-08-26T19:56:09.2452494Z >>> optimizer.zero_grad() 2025-08-26T19:56:09.2452612Z >>> loss = loss_fn(output, labels) 2025-08-26T19:56:09.2452714Z >>> loss.backward() 2025-08-26T19:56:09.2452864Z >>> optimizer.step() 2025-08-26T19:56:09.2453066Z >>> # Will average model parameters globally every 4 steps. Thus, 2025-08-26T19:56:09.2453287Z >>> # inter-node communication only occurs every 4 iterations after 2025-08-26T19:56:09.2453415Z >>> # the initial ``warmup_steps`` period. 2025-08-26T19:56:09.2453583Z >>> averager.average_parameters(model.parameters()) 2025-08-26T19:56:09.2453677Z 2025-08-26T19:56:09.2453936Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2454034Z 2025-08-26T19:56:09.2454135Z warnings.warn(msg) 2025-08-26T19:56:09.2454218Z 2025-08-26T19:56:09.2454441Z --- Parse Warning: 62 / 146 --- 2025-08-26T19:56:09.2455700Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=HierarchicalModelAverager in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/algorithms/model_averaging/hierarchical_model_averager.py line=19. 2025-08-26T19:56:09.2456012Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2456096Z 2025-08-26T19:56:09.2456443Z Runs hierarchical model averaging (`hierarchical SGD `_). 2025-08-26T19:56:09.2456540Z 2025-08-26T19:56:09.2456859Z Process groups of different sizes are organized in a hierarchy, and they average parameters 2025-08-26T19:56:09.2457083Z by using different periods concurrently after the warm-up stage. 2025-08-26T19:56:09.2457527Z This is an extension of :class:`~torch.distributed.algorithms.model_averaging.averagers.PeriodicModelAverager` 2025-08-26T19:56:09.2457873Z that supports `post-local SGD `_, which essentially only supports 2025-08-26T19:56:09.2458230Z a two-level hierarchy: the intra-machine level and the global level, where the intra-machine 2025-08-26T19:56:09.2458592Z level is usually embedded in :meth:`~torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook`. 2025-08-26T19:56:09.2458916Z Similarly, the process groups within this class do not have such an intra-machine process 2025-08-26T19:56:09.2459197Z subgroup, which should be embedded by the post-local SGD communication hook instead. 2025-08-26T19:56:09.2459297Z 2025-08-26T19:56:09.2459384Z Args: 2025-08-26T19:56:09.2459655Z period_group_size_dict: An ordered dict mapping keys of model averaging period to 2025-08-26T19:56:09.2459876Z process group size, used for initializing process groups of 2025-08-26T19:56:09.2460107Z different sizes in a hierarchy to average parameters concurrently. 2025-08-26T19:56:09.2460335Z Particularly, at each iteration, there will be at most a single 2025-08-26T19:56:09.2460570Z process group that runs averaging -- the period of such group should 2025-08-26T19:56:09.2460792Z have the largest period which the current step can be divided by. 2025-08-26T19:56:09.2460979Z For example, if the dict has three keys: 2, 4, and 8, 2025-08-26T19:56:09.2461192Z then this means totally three process groups will be created to 2025-08-26T19:56:09.2461421Z average parameters every 2, 4, and 8 iterations, respectively. 2025-08-26T19:56:09.2461618Z At the 4th iteration, only the second process group will run 2025-08-26T19:56:09.2461796Z averaging, because the first process group should be a 2025-08-26T19:56:09.2462028Z subset of the second process group, and no need to execute the first 2025-08-26T19:56:09.2462156Z process group redundantly. 2025-08-26T19:56:09.2462397Z On the other hand, the third process group can only be triggered 2025-08-26T19:56:09.2462625Z every 8 iterations, so it will not be triggered at the 4th iteration. 2025-08-26T19:56:09.2462944Z warmup_steps (int): The number of warm-up steps. During this stage, model averaging is skipped. 2025-08-26T19:56:09.2463397Z process_group (ProcessGroup, optional): The overall process group containing all the processes that runs model averaging. 2025-08-26T19:56:09.2463575Z If ``None``, the default process group, which is created 2025-08-26T19:56:09.2463795Z by :func:`torch.distributed.init_process_group`, will be used. 2025-08-26T19:56:09.2463918Z (default: ``None``) 2025-08-26T19:56:09.2464010Z 2025-08-26T19:56:09.2464101Z Example:: 2025-08-26T19:56:09.2464224Z >>> # xdoctest: +SKIP('undefined rank') 2025-08-26T19:56:09.2464388Z >>> from collections import OrderedDict 2025-08-26T19:56:09.2464481Z >>> import torch 2025-08-26T19:56:09.2464612Z >>> import torch.distributed as dist 2025-08-26T19:56:09.2464889Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T19:56:09.2464998Z >>> PostLocalSGDState, 2025-08-26T19:56:09.2465111Z >>> post_localSGD_hook, 2025-08-26T19:56:09.2465196Z >>> ) 2025-08-26T19:56:09.2465618Z >>> import torch.distributed.algorithms.model_averaging.hierarchical_model_averager as hierarchicalSGD 2025-08-26T19:56:09.2465728Z >>> import torch.nn as nn 2025-08-26T19:56:09.2465814Z >>> 2025-08-26T19:56:09.2466007Z >>> dist.init_process_group("nccl", rank=rank, world_size=16) 2025-08-26T19:56:09.2466121Z >>> torch.cuda.set_device(rank) 2025-08-26T19:56:09.2466294Z >>> module = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T19:56:09.2466452Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T19:56:09.2466595Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T19:56:09.2466694Z >>> ) 2025-08-26T19:56:09.2466842Z >>> # Register a post-localSGD communication hook. 2025-08-26T19:56:09.2467141Z >>> # Assume that each machine has 4 GPUs, then each intra-machine subgroup has a size of 4. 2025-08-26T19:56:09.2467262Z >>> subgroup, _ = dist.new_subgroups() 2025-08-26T19:56:09.2467581Z >>> state = PostLocalSGDState(process_group=None, subgroup=subgroup, start_localSGD_iter=100) 2025-08-26T19:56:09.2467757Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:56:09.2467840Z >>> 2025-08-26T19:56:09.2468141Z >>> # Average parameters among each group of 8 processes every 4 iterations, and among all 2025-08-26T19:56:09.2468263Z >>> # the 16 processes every 16 iterations. 2025-08-26T19:56:09.2468456Z >>> averager = hierarchicalSGD.HierarchicalModelAverager( 2025-08-26T19:56:09.2468705Z >>> period_group_size_dict=OrderedDict([(4, 8), (16, 16)]), warmup_steps=100) 2025-08-26T19:56:09.2469025Z >>> # Note that ``warmup_steps`` must be the same as ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T19:56:09.2469308Z >>> # In the first 100 steps, run global gradient averaging like normal DDP at every step. 2025-08-26T19:56:09.2469465Z >>> # After 100 steps, run model averaging at two levels. 2025-08-26T19:56:09.2469571Z >>> for step in range(0, 200): 2025-08-26T19:56:09.2469691Z >>> optimizer.zero_grad() 2025-08-26T19:56:09.2469806Z >>> loss = loss_fn(output, labels) 2025-08-26T19:56:09.2469917Z >>> loss.backward() 2025-08-26T19:56:09.2470019Z >>> optimizer.step() 2025-08-26T19:56:09.2470178Z >>> # Average parameters after ``optimizer.step()``. 2025-08-26T19:56:09.2470484Z >>> # Thus, the inter-node communication only occurs periodically after ``warmup_steps``. 2025-08-26T19:56:09.2470678Z >>> averager.average_parameters(model.parameters()) 2025-08-26T19:56:09.2470774Z 2025-08-26T19:56:09.2470866Z .. warning :: 2025-08-26T19:56:09.2471124Z The last group size in the dict must be the size of the provided ``process_group``, 2025-08-26T19:56:09.2471376Z which indicates model averaging at the highest level of the hierarchy. 2025-08-26T19:56:09.2471685Z If ``process_group`` is not provided, then the last group size should be equal to the world size. 2025-08-26T19:56:09.2471785Z 2025-08-26T19:56:09.2471874Z .. warning :: 2025-08-26T19:56:09.2472114Z `HierarchicalModelAverager` is experimental and subject to change. 2025-08-26T19:56:09.2472208Z 2025-08-26T19:56:09.2472462Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2472557Z 2025-08-26T19:56:09.2472659Z warnings.warn(msg) 2025-08-26T19:56:09.2472739Z 2025-08-26T19:56:09.2472999Z --- Parse Warning: 63 / 146 --- 2025-08-26T19:56:09.2474110Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BroadcastingTorchSaveReader in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=40. 2025-08-26T19:56:09.2474393Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2474475Z 2025-08-26T19:56:09.2474814Z StorageReader for reading a Torch Save file. This reader will read the entire checkpoint 2025-08-26T19:56:09.2475078Z on the coordinator rank, and then broadcast and shard each tensor to all ranks. 2025-08-26T19:56:09.2475158Z 2025-08-26T19:56:09.2475340Z . N.B. Intended to be used with DynamicMetaLoadPlanner 2025-08-26T19:56:09.2475421Z 2025-08-26T19:56:09.2475510Z .. warning:: 2025-08-26T19:56:09.2475727Z Current implementation only supports loading Tensors. 2025-08-26T19:56:09.2475810Z 2025-08-26T19:56:09.2475942Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2476039Z >>> sd = {"mode": model} 2025-08-26T19:56:09.2476128Z >>> dcp.load( 2025-08-26T19:56:09.2476226Z >>> sd, 2025-08-26T19:56:09.2476382Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T19:56:09.2476523Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T19:56:09.2476640Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T19:56:09.2476722Z >>> ) 2025-08-26T19:56:09.2476814Z 2025-08-26T19:56:09.2477077Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2477167Z 2025-08-26T19:56:09.2477263Z warnings.warn(msg) 2025-08-26T19:56:09.2477343Z 2025-08-26T19:56:09.2477544Z --- Parse Warning: 64 / 146 --- 2025-08-26T19:56:09.2478616Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DynamicMetaLoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/format_utils.py line=151. 2025-08-26T19:56:09.2478898Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2478977Z 2025-08-26T19:56:09.2479352Z Extension of DefaultLoadPlanner, which creates a new Metadata object based on the passed in state dict, 2025-08-26T19:56:09.2479693Z avoiding the need to read metadata from disk. This is useful when reading formats which don't have a 2025-08-26T19:56:09.2479808Z metadata file, like Torch Save files. 2025-08-26T19:56:09.2479900Z 2025-08-26T19:56:09.2480081Z . N.B. Intended to be used with BroadcastingTorchSaveReader 2025-08-26T19:56:09.2480161Z 2025-08-26T19:56:09.2480261Z .. warning:: 2025-08-26T19:56:09.2480436Z Current implementation only supports loading Tensors. 2025-08-26T19:56:09.2480527Z 2025-08-26T19:56:09.2480675Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2480774Z >>> sd = {"mode": model} 2025-08-26T19:56:09.2480873Z >>> dcp.load( 2025-08-26T19:56:09.2480957Z >>> sd, 2025-08-26T19:56:09.2481111Z >>> storage_reader=BroadcastingTorchSaveReader(), 2025-08-26T19:56:09.2481248Z >>> planner=DynamicMetaLoadPlanner(), 2025-08-26T19:56:09.2481365Z >>> checkpoint_id="path_to_model.pt" 2025-08-26T19:56:09.2481459Z >>> ) 2025-08-26T19:56:09.2481538Z 2025-08-26T19:56:09.2481795Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2481889Z 2025-08-26T19:56:09.2481984Z warnings.warn(msg) 2025-08-26T19:56:09.2482081Z 2025-08-26T19:56:09.2482267Z --- Parse Warning: 65 / 146 --- 2025-08-26T19:56:09.2483349Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_sharded_optimizer_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/optimizer.py line=221. 2025-08-26T19:56:09.2483661Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2483745Z 2025-08-26T19:56:09.2483974Z Load a state_dict in conjunction with FSDP sharded optimizer state. 2025-08-26T19:56:09.2484053Z 2025-08-26T19:56:09.2484222Z This is the current recommended way to checkpoint FSDP. 2025-08-26T19:56:09.2484336Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2484494Z >>> import torch.distributed.checkpoint as dist_cp 2025-08-26T19:56:09.2484618Z >>> # Save 2025-08-26T19:56:09.2484721Z >>> model: torch.nn.Model 2025-08-26T19:56:09.2484841Z >>> optim_params = model.parameters() 2025-08-26T19:56:09.2484998Z >>> optim = torch.optim.SGD(optim_params, lr=0.01) 2025-08-26T19:56:09.2485082Z >>> # Save 2025-08-26T19:56:09.2485317Z >>> with FSDP.state_dict_type(model, StateDictType.SHARDED_STATE_DICT): 2025-08-26T19:56:09.2485439Z >>> state_dict = { 2025-08-26T19:56:09.2485599Z >>> "optimizer": FSDP.optim_state_dict(model, optim), 2025-08-26T19:56:09.2485723Z >>> "model": model.state_dict() 2025-08-26T19:56:09.2485805Z >>> } 2025-08-26T19:56:09.2485911Z >>> dist_cp.save_state_dict( 2025-08-26T19:56:09.2486028Z >>> state_dict=optim_state, 2025-08-26T19:56:09.2486212Z >>> storage_writer=dist_cp.FileSystemWriter("checkpoint"), 2025-08-26T19:56:09.2486361Z >>> planner=dist_cp.DefaultSavePlanner(), 2025-08-26T19:56:09.2486445Z >>> ) 2025-08-26T19:56:09.2486530Z >>> 2025-08-26T19:56:09.2486626Z >>> # Load 2025-08-26T19:56:09.2486859Z >>> with FSDP.state_dict_type(model_tp, StateDictType.SHARDED_STATE_DICT): 2025-08-26T19:56:09.2487006Z >>> model_state_dict = model_tp.state_dict() 2025-08-26T19:56:09.2487104Z >>> checkpoint = { 2025-08-26T19:56:09.2487212Z >>> "model": model_state_dict 2025-08-26T19:56:09.2487313Z >>> } 2025-08-26T19:56:09.2487420Z >>> dist_cp.load_state_dict( 2025-08-26T19:56:09.2487540Z >>> state_dict=checkpoint, 2025-08-26T19:56:09.2487733Z >>> storage_reader=dist_cp.FileSystemReader(checkpoint_file), 2025-08-26T19:56:09.2487868Z >>> planner=dist_cp.DefaultLoadPlanner(), 2025-08-26T19:56:09.2487964Z >>> ) 2025-08-26T19:56:09.2488118Z >>> model.load_state_dict(checkpoint["model_state"]) 2025-08-26T19:56:09.2488214Z >>> 2025-08-26T19:56:09.2488390Z >>> optim_state = dist_cp.load_sharded_optimizer_state_dict( 2025-08-26T19:56:09.2488493Z >>> model_state_dict, 2025-08-26T19:56:09.2488620Z >>> optimizer_key="optimizer", 2025-08-26T19:56:09.2488883Z >>> storage_reader=dist_cp.FileSystemReader("checkpoint"), 2025-08-26T19:56:09.2488985Z >>> ) 2025-08-26T19:56:09.2489068Z >>> 2025-08-26T19:56:09.2489219Z >>> flattened_osd = FSDP.optim_state_dict_to_load( 2025-08-26T19:56:09.2489394Z >>> model, optim, optim_state["optimizer"] 2025-08-26T19:56:09.2489482Z >>> ) 2025-08-26T19:56:09.2489566Z >>> 2025-08-26T19:56:09.2489706Z >>> optim.load_state_dict(flattened_osd) 2025-08-26T19:56:09.2489789Z 2025-08-26T19:56:09.2490062Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2490147Z 2025-08-26T19:56:09.2490248Z warnings.warn(msg) 2025-08-26T19:56:09.2490345Z 2025-08-26T19:56:09.2490544Z --- Parse Warning: 66 / 146 --- 2025-08-26T19:56:09.2491542Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SavePlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=122. 2025-08-26T19:56:09.2491810Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2491894Z 2025-08-26T19:56:09.2492203Z Abstract class defining the protocol used by save_state_dict to plan the save process. 2025-08-26T19:56:09.2492313Z 2025-08-26T19:56:09.2492624Z SavePlanners are stateful objects that can be used to customize the whole save process. 2025-08-26T19:56:09.2492707Z 2025-08-26T19:56:09.2492990Z SavePlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T19:56:09.2493122Z will be visible to the whole process. 2025-08-26T19:56:09.2493204Z 2025-08-26T19:56:09.2493503Z A planner subclass can expect the following sequence of calls during save_state_dict: 2025-08-26T19:56:09.2493611Z 2025-08-26T19:56:09.2493734Z 1) set_up_planner - called on all ranks. 2025-08-26T19:56:09.2493875Z Signals the start of a checkpoint save. 2025-08-26T19:56:09.2493958Z 2025-08-26T19:56:09.2494095Z 2) create_local_plan - called on all ranks. 2025-08-26T19:56:09.2494413Z Process the state_dict and produces a `SavePlan` that will be sent for global planning. 2025-08-26T19:56:09.2494499Z 2025-08-26T19:56:09.2494692Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T19:56:09.2494893Z Takes the SavePlan from all ranks and make any global decision. 2025-08-26T19:56:09.2494989Z 2025-08-26T19:56:09.2495102Z 4) finish_plan - called on all ranks. 2025-08-26T19:56:09.2495320Z This gives each rank a chance to adjust to global planning decisions. 2025-08-26T19:56:09.2495415Z 2025-08-26T19:56:09.2495570Z 5) resolve_data - called multiple times on each rank 2025-08-26T19:56:09.2495790Z Lookups a value on the `state_dict` for the storage layer to write. 2025-08-26T19:56:09.2495870Z 2025-08-26T19:56:09.2496184Z Users are recommended to extend DefaultSavePlanner instead of this interface directly as 2025-08-26T19:56:09.2496377Z most changes can be expressed by changes in a single method. 2025-08-26T19:56:09.2496457Z 2025-08-26T19:56:09.2496597Z There are 3 usual patterns of extension: 2025-08-26T19:56:09.2496680Z 2025-08-26T19:56:09.2496937Z Rewriting state_dict. This is the simplest way to extend the save process as it 2025-08-26T19:56:09.2497182Z doesn't requite understanding the intrincacies of how SavePlan works: 2025-08-26T19:56:09.2497264Z 2025-08-26T19:56:09.2497382Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2497530Z >>> class RenamePlanner(DefaultSavePlanner): 2025-08-26T19:56:09.2497632Z >>> def set_up_planner( 2025-08-26T19:56:09.2497731Z >>> self, 2025-08-26T19:56:09.2497847Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T19:56:09.2497981Z >>> storage_meta: Optional[StorageMeta], 2025-08-26T19:56:09.2498100Z >>> is_coordinator: bool, 2025-08-26T19:56:09.2498189Z >>> ) -> None: 2025-08-26T19:56:09.2498313Z >>> # prefix all keys with `foo_`` 2025-08-26T19:56:09.2498615Z >>> super().set_up_planner({"foo_" + k: v for k, v in state_dict.items()}, storage_meta, is_coordinator) 2025-08-26T19:56:09.2498721Z 2025-08-26T19:56:09.2499072Z Modifying local plan and lookup in tandem. This is useful when fine control of how data is persisted 2025-08-26T19:56:09.2499154Z 2025-08-26T19:56:09.2499291Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2499423Z >>> class FP16Planner(DefaultSavePlanner): 2025-08-26T19:56:09.2499534Z >>> def create_local_plan(self): 2025-08-26T19:56:09.2499666Z >>> plan = super().create_local_plan() 2025-08-26T19:56:09.2499765Z >>> for p in plan: 2025-08-26T19:56:09.2499897Z >>> if p.tensor_data is not None: 2025-08-26T19:56:09.2500058Z >>> p.tensor_data.properties.dtype = torch.float16 2025-08-26T19:56:09.2500152Z >>> return plan 2025-08-26T19:56:09.2500249Z >>> 2025-08-26T19:56:09.2500368Z >>> def resolve_data(self, write_item): 2025-08-26T19:56:09.2500511Z >>> item = super().resolve_data(write_item) 2025-08-26T19:56:09.2500792Z >>> return item if write_item.type == WriteItemType.BYTE_IO else item.to(torch.float16) 2025-08-26T19:56:09.2500903Z 2025-08-26T19:56:09.2501263Z Using the global planning step to make central decisions that can't be made individually by each rank 2025-08-26T19:56:09.2501348Z 2025-08-26T19:56:09.2501473Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2501589Z >>> from itertools import zip_longest 2025-08-26T19:56:09.2501702Z >>> from dataclasses import replace 2025-08-26T19:56:09.2501909Z >>> class DDPLoadBalancingPlanner(DefaultSavePlanner): 2025-08-26T19:56:09.2502193Z >>> # This uses the default local plan behavior of having all non-sharded writes in rank 0 2025-08-26T19:56:09.2502337Z >>> # This sample doesn't handle ShardedTensors 2025-08-26T19:56:09.2502468Z >>> def create_global_plan(self, all_plans): 2025-08-26T19:56:09.2502674Z >>> iters = [iter(all_plans[0].items)] * len(all_plans) 2025-08-26T19:56:09.2502791Z >>> items_per_rank = [ 2025-08-26T19:56:09.2502934Z >>> [item for item in items if item is not None] 2025-08-26T19:56:09.2503106Z >>> for items in zip(*zip_longest(*iters), strict=True) 2025-08-26T19:56:09.2503189Z >>> ] 2025-08-26T19:56:09.2503285Z >>> all_plans = [ 2025-08-26T19:56:09.2503411Z >>> replace(plan, items=items) 2025-08-26T19:56:09.2503604Z >>> for plan, items in zip(all_plans, items_per_rank, strict=True) 2025-08-26T19:56:09.2503700Z >>> ] 2025-08-26T19:56:09.2503845Z >>> return super().create_global_plan(all_plans) 2025-08-26T19:56:09.2503928Z 2025-08-26T19:56:09.2504209Z Finally, some planners need to save additional metadata in the checkpoint, this is 2025-08-26T19:56:09.2504485Z accomplished by having each rank contribute their data items in the local plan and 2025-08-26T19:56:09.2504616Z the global planner aggregate them: 2025-08-26T19:56:09.2504700Z 2025-08-26T19:56:09.2504818Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2504987Z >>> class SaveExtraDataPlanner(DefaultSavePlanner): 2025-08-26T19:56:09.2505119Z >>> def create_local_plan(self) -> SavePlan: 2025-08-26T19:56:09.2505244Z >>> plan = super().create_local_plan() 2025-08-26T19:56:09.2505421Z >>> return replace(plan, planner_data="per-rank-data") 2025-08-26T19:56:09.2505504Z >>> 2025-08-26T19:56:09.2505815Z >>> def create_global_plan(self, all_plans: List[SavePlan]) -> Tuple[List[SavePlan], Metadata]: 2025-08-26T19:56:09.2506014Z >>> global_plan, metadata = super().create_global_plan(all_plans) 2025-08-26T19:56:09.2506173Z >>> merged_data = [p.planner_data for p in global_plan] 2025-08-26T19:56:09.2506357Z >>> metadata = replace(metadata, planner_data=merged_data) 2025-08-26T19:56:09.2506471Z >>> return global_plan, metadata 2025-08-26T19:56:09.2506604Z 2025-08-26T19:56:09.2506863Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2506947Z 2025-08-26T19:56:09.2507059Z warnings.warn(msg) 2025-08-26T19:56:09.2507138Z 2025-08-26T19:56:09.2507344Z --- Parse Warning: 67 / 146 --- 2025-08-26T19:56:09.2508327Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LoadPlanner in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/planner.py line=305. 2025-08-26T19:56:09.2508612Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2508693Z 2025-08-26T19:56:09.2508984Z Abstract class defining the protocol used by load_state_dict to plan the load process. 2025-08-26T19:56:09.2509076Z 2025-08-26T19:56:09.2509368Z LoadPlanner are stateful objects that can be used to customize the whole load process. 2025-08-26T19:56:09.2509452Z 2025-08-26T19:56:09.2509747Z LoadPlanner acts as an access proxy to the state_dict, so any transformation done to it 2025-08-26T19:56:09.2509893Z will be visible to the whole process. 2025-08-26T19:56:09.2509983Z 2025-08-26T19:56:09.2510266Z A planner subclass can expect the following sequence of calls during load_state_dict: 2025-08-26T19:56:09.2510348Z 2025-08-26T19:56:09.2510479Z 1) set_up_planner - called on all ranks. 2025-08-26T19:56:09.2510611Z Signals the start of loading a checkpoint. 2025-08-26T19:56:09.2510702Z 2025-08-26T19:56:09.2510853Z 2) create_local_plan - called on all ranks. 2025-08-26T19:56:09.2511144Z Process the state_dict and produces a `LoadPlan` that will be sent for global planning. 2025-08-26T19:56:09.2511237Z 2025-08-26T19:56:09.2511420Z 3) create_global_plan - called on the coordinator rank only. 2025-08-26T19:56:09.2511634Z Takes the LoadPlan from all ranks and make any global decision. 2025-08-26T19:56:09.2511751Z 2025-08-26T19:56:09.2511902Z 4) load_bytes - called multiple times on each rank 2025-08-26T19:56:09.2512086Z This is called once per non-tensor value in state_dict. 2025-08-26T19:56:09.2512167Z 2025-08-26T19:56:09.2512406Z 5) resolve_tensor and commit_tensor - called multiple times on each rank 2025-08-26T19:56:09.2512592Z They are called in pair for each Tensor value in state_dict. 2025-08-26T19:56:09.2512673Z 2025-08-26T19:56:09.2512994Z Users are recommended to extend DefaultLoadPlanner instead of this interface directly as 2025-08-26T19:56:09.2513185Z most changes can be expressed by changes in a single method. 2025-08-26T19:56:09.2513280Z 2025-08-26T19:56:09.2513412Z There are two usual patterns of extension: 2025-08-26T19:56:09.2513497Z 2025-08-26T19:56:09.2513771Z Rewriting state_dict. This is the simplest way to extend the load process as it 2025-08-26T19:56:09.2514032Z doesn't requite understanding the intrincacies of how LoadPlan works. We need 2025-08-26T19:56:09.2514280Z to keep a reference to the original state_dict as load happens in place so 2025-08-26T19:56:09.2514413Z we need to be able to perform it in place 2025-08-26T19:56:09.2514495Z 2025-08-26T19:56:09.2514624Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2514762Z >>> class RenamePlanner(DefaultLoadPlanner): 2025-08-26T19:56:09.2514875Z >>> def set_up_planner( 2025-08-26T19:56:09.2514962Z >>> self, 2025-08-26T19:56:09.2515075Z >>> state_dict: STATE_DICT_TYPE, 2025-08-26T19:56:09.2515191Z >>> metadata: Metadata, 2025-08-26T19:56:09.2515298Z >>> is_coordinator: bool, 2025-08-26T19:56:09.2515387Z >>> ) -> None: 2025-08-26T19:56:09.2515524Z >>> self.original_state_dict = state_dict 2025-08-26T19:56:09.2515703Z >>> state_dict = {"foo_" + k: v for k, v in state_dict.items()} 2025-08-26T19:56:09.2515797Z >>> 2025-08-26T19:56:09.2515947Z >>> if self.flatten_sharded_tensors: 2025-08-26T19:56:09.2516104Z >>> state_dict = _flatten_sharded_tensors(state_dict) 2025-08-26T19:56:09.2516198Z >>> 2025-08-26T19:56:09.2516310Z >>> if self.flatten_state_dict: 2025-08-26T19:56:09.2516506Z >>> state_dict, self.mappings = flatten_state_dict(state_dict) 2025-08-26T19:56:09.2516595Z >>> 2025-08-26T19:56:09.2516709Z >>> self.state_dict = state_dict 2025-08-26T19:56:09.2516830Z >>> self.metadata = metadata 2025-08-26T19:56:09.2516960Z >>> self.is_coordinator = is_coordinator 2025-08-26T19:56:09.2517059Z >>> 2025-08-26T19:56:09.2517186Z >>> def load_bytes(self, read_item, value): 2025-08-26T19:56:09.2517292Z >>> # Remove the "foo_" prefix 2025-08-26T19:56:09.2517632Z >>> self.original_state_dict[read_item.dest_index.fqn[4:]] = torch.load(value, weights_only=False) 2025-08-26T19:56:09.2517715Z 2025-08-26T19:56:09.2517815Z 2025-08-26T19:56:09.2518083Z Modifying resolve_tensor and commit_tensor to handle load time transformation. 2025-08-26T19:56:09.2518195Z 2025-08-26T19:56:09.2518328Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2518488Z >>> class MetaModelMaterialize(DefaultSavePlanner): 2025-08-26T19:56:09.2518625Z >>> def resolve_tensor(self, read_item): 2025-08-26T19:56:09.2518767Z >>> tensor = super().resolve_tensor(read_item) 2025-08-26T19:56:09.2518917Z >>> return torch.empty_like(tensor, device="cpu") 2025-08-26T19:56:09.2519016Z >>> 2025-08-26T19:56:09.2519178Z >>> def commit_tensor(self, read_item, tensor): 2025-08-26T19:56:09.2519354Z >>> self.state_dict[read_item.dest_index.fqn] = tensor 2025-08-26T19:56:09.2519439Z 2025-08-26T19:56:09.2519698Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2519795Z 2025-08-26T19:56:09.2519897Z warnings.warn(msg) 2025-08-26T19:56:09.2520010Z 2025-08-26T19:56:09.2520217Z --- Parse Warning: 68 / 146 --- 2025-08-26T19:56:09.2521226Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict.py line=1118. 2025-08-26T19:56:09.2521508Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2521593Z 2025-08-26T19:56:09.2521776Z Return the model state_dict and optimizers state_dict. 2025-08-26T19:56:09.2521860Z 2025-08-26T19:56:09.2522091Z ``get_state_dict`` can process any module that is parallelized by PyTorch 2025-08-26T19:56:09.2522361Z FSDP/fully_shard, DDP/replicate, tensor_parallel/parallelize_module, and any 2025-08-26T19:56:09.2522614Z combination of these parallelisms. The main functions of ``get_state_dict`` 2025-08-26T19:56:09.2522849Z are: 1.) returning a model and optimizer state_dict that can be resharded 2025-08-26T19:56:09.2523064Z with a different number of trainers and/or different parallelisms. 2025-08-26T19:56:09.2523319Z 2.) hiding the parallelism-specific state_dict APIs. Users don't have to call 2025-08-26T19:56:09.2523423Z these APIs. 2025-08-26T19:56:09.2523549Z 3.) sanity checking the result state_dict. 2025-08-26T19:56:09.2523644Z 2025-08-26T19:56:09.2523856Z The keys of the result state dictionary are the canonical FQNs (Fully 2025-08-26T19:56:09.2524097Z Qualified Names). A canonical FQN refers to the FQN based on a parameter's 2025-08-26T19:56:09.2524353Z position in an nn.Module hierarchy. More specifically, a canonical FQN to a 2025-08-26T19:56:09.2524567Z parameter is the FQN returned by ``module.named_parameters()`` or 2025-08-26T19:56:09.2524791Z ``module.named_buffers()`` when the module is not distributed by any 2025-08-26T19:56:09.2525050Z parallelisms. Since the optimizer internally uses parameter IDs to represent 2025-08-26T19:56:09.2525300Z a parameter, there will be a conversion from the parameter IDs to the 2025-08-26T19:56:09.2525429Z canonical FQNs when calling this API. 2025-08-26T19:56:09.2525511Z 2025-08-26T19:56:09.2525745Z ``get_state_dict`` can also process a module that is not parallelized. In 2025-08-26T19:56:09.2525970Z such a case, ``get_state_dict`` only performs one function -- converting the 2025-08-26T19:56:09.2526115Z optimizer parameter IDs to the canonical FQNs. 2025-08-26T19:56:09.2526209Z 2025-08-26T19:56:09.2526295Z Example: 2025-08-26T19:56:09.2526407Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2526501Z >>> import torch 2025-08-26T19:56:09.2526745Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:56:09.2526964Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T19:56:09.2527195Z >>> from torch.distributed.checkpoint.state_dict import get_state_dict 2025-08-26T19:56:09.2527290Z 2025-08-26T19:56:09.2527452Z >>> fsdp_model = FSDP(copy.deepcopy(model)) 2025-08-26T19:56:09.2527641Z >>> fsdp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T19:56:09.2527779Z >>> ddp_model = DDP(copy.deepcopy(model)) 2025-08-26T19:56:09.2527960Z >>> ddp_optim = torch.optim.Adam(model.parameters(), lr=1e-3) 2025-08-26T19:56:09.2528043Z 2025-08-26T19:56:09.2528143Z 2025-08-26T19:56:09.2528386Z >>> ddp_state_dict, ddp_optim_state_dict = get_state_dict(ddp_model, ddp_optim) 2025-08-26T19:56:09.2528596Z >>> fsdp_state_dict, fsdp_optim_state_dict = get_state_dict( 2025-08-26T19:56:09.2528709Z ... fsdp_model, fsdp_optim 2025-08-26T19:56:09.2528862Z ... ) 2025-08-26T19:56:09.2528960Z 2025-08-26T19:56:09.2529180Z >>> # if we simply call ddp_model.state_dict() and fsdp_model.state_dict(), 2025-08-26T19:56:09.2529299Z >>> # the asserts will fail. 2025-08-26T19:56:09.2529466Z >>> assert ddp_state_dict == fsdp_state_dict 2025-08-26T19:56:09.2529623Z >>> assert ddp_optim_state == fsdp_optim_state_dict 2025-08-26T19:56:09.2529719Z 2025-08-26T19:56:09.2529801Z 2025-08-26T19:56:09.2529899Z Args: 2025-08-26T19:56:09.2530042Z model (nn.Module): the nn.Module to the model. 2025-08-26T19:56:09.2530234Z optimizers (Union[None, Optimizer, Iterable[Optimizer]]): 2025-08-26T19:56:09.2530407Z The optimizers that are used to optimize ``model``. 2025-08-26T19:56:09.2530697Z submodules (deprecated): Optional[set[nn.Module]]: only return the model parameters 2025-08-26T19:56:09.2530828Z that belong to the submodules. 2025-08-26T19:56:09.2531013Z options (StateDictOptions): the options to control how 2025-08-26T19:56:09.2531227Z model state_dict and optimizer state_dict should be returned. See 2025-08-26T19:56:09.2531364Z `StateDictOptions` for the details. 2025-08-26T19:56:09.2531450Z 2025-08-26T19:56:09.2531548Z Returns: 2025-08-26T19:56:09.2531749Z ``Tuple`` that contain model state_dict and optimizer state_dict. 2025-08-26T19:56:09.2531833Z 2025-08-26T19:56:09.2532081Z :rtype: typing.Tuple[typing.Dict[str, ValueType], OptimizerStateType] 2025-08-26T19:56:09.2532164Z 2025-08-26T19:56:09.2532437Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2532519Z 2025-08-26T19:56:09.2532620Z warnings.warn(msg) 2025-08-26T19:56:09.2532715Z 2025-08-26T19:56:09.2532922Z --- Parse Warning: 69 / 146 --- 2025-08-26T19:56:09.2533915Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_loader.py line=69. 2025-08-26T19:56:09.2534203Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2534321Z 2025-08-26T19:56:09.2534542Z Load a checkpoint into a distributed state dict in SPMD style. 2025-08-26T19:56:09.2534625Z 2025-08-26T19:56:09.2534866Z Each rank must have the same keys in their ``state_dict`` provided to this 2025-08-26T19:56:09.2535101Z API. Mismatched keys may result in hangs or errors. If unsure, you can use 2025-08-26T19:56:09.2535323Z the ``utils._assert_same_keys`` API to check (but may incur communication 2025-08-26T19:56:09.2535422Z costs). 2025-08-26T19:56:09.2535504Z 2025-08-26T19:56:09.2535702Z Each rank will try to read the least amount of data necessary 2025-08-26T19:56:09.2535940Z to fulfill the requested `state_dict`. When loading :class:`ShardedTensor` 2025-08-26T19:56:09.2536194Z or :class:`DTensor` instances, each rank only reads data for their local shards. 2025-08-26T19:56:09.2536287Z 2025-08-26T19:56:09.2536552Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T19:56:09.2536822Z load will first call ``state_dict`` before attempting deserialization, followed by 2025-08-26T19:56:09.2537023Z ``load_state_dict`` once the deserialization is complete. 2025-08-26T19:56:09.2537285Z For each non-``Stateful`` object, load will deserialize the object, and then replace 2025-08-26T19:56:09.2537607Z it in the ``state_dict`` with the deserialized object. 2025-08-26T19:56:09.2537691Z 2025-08-26T19:56:09.2537801Z .. warning:: 2025-08-26T19:56:09.2537972Z All tensors in ``state_dict`` must be allocated on their 2025-08-26T19:56:09.2538202Z destination device *prior to* calling this function. 2025-08-26T19:56:09.2538301Z 2025-08-26T19:56:09.2538537Z All non-tensor data is loaded using `torch.load()` and modified in place 2025-08-26T19:56:09.2538647Z on state_dict. 2025-08-26T19:56:09.2538728Z 2025-08-26T19:56:09.2538818Z .. warning:: 2025-08-26T19:56:09.2539091Z Users must call `load_state_dict` on the root module to ensure load 2025-08-26T19:56:09.2539284Z pos-processing and non-tensor data properly propagates. 2025-08-26T19:56:09.2539364Z 2025-08-26T19:56:09.2539465Z .. note: 2025-08-26T19:56:09.2539693Z If no process group is initialized, this function will assume the intent 2025-08-26T19:56:09.2539932Z is to load a checkpoint into the local process. This can be useful in the 2025-08-26T19:56:09.2540184Z case of local inference, and when using regular Tensors (as opposed to DTensor 2025-08-26T19:56:09.2540287Z or ShardedTensor) 2025-08-26T19:56:09.2540385Z 2025-08-26T19:56:09.2540471Z .. note: 2025-08-26T19:56:09.2540628Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T19:56:09.2540708Z 2025-08-26T19:56:09.2540791Z Args: 2025-08-26T19:56:09.2541019Z state_dict (Dict[str, Any]): The state_dict to load the checkpoint into. 2025-08-26T19:56:09.2541169Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T19:56:09.2541396Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T19:56:09.2541603Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T19:56:09.2541772Z It can also be a key if the storage is a key-value store. 2025-08-26T19:56:09.2541884Z (Default: ``None``) 2025-08-26T19:56:09.2542017Z storage_reader (Optional[StorageReader]): 2025-08-26T19:56:09.2542237Z Instance of StorageWriter used to perform reads. If this is not 2025-08-26T19:56:09.2542444Z specified, DCP will automatically infer the reader based on the 2025-08-26T19:56:09.2542648Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T19:56:09.2542773Z be raised. (Default: ``None``) 2025-08-26T19:56:09.2542892Z planner (Optional[LoadPlanner]): 2025-08-26T19:56:09.2543109Z Instance of LoadPlanner. If this is not specified, the default 2025-08-26T19:56:09.2543283Z planner will be used. (Default: ``None``) 2025-08-26T19:56:09.2543416Z process_group (Optional[ProcessGroup]): 2025-08-26T19:56:09.2543613Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T19:56:09.2543712Z (Default: ``None``) 2025-08-26T19:56:09.2543940Z no_dist (bool): If ``True``, this function will assume the intent is to load 2025-08-26T19:56:09.2544197Z a checkpoint without using cross-rank synchronization. (Default: ``False``) 2025-08-26T19:56:09.2544284Z Returns: 2025-08-26T19:56:09.2544382Z None. 2025-08-26T19:56:09.2544466Z 2025-08-26T19:56:09.2544569Z Examples 2025-08-26T19:56:09.2544670Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2544772Z >>> my_model = MyModule() 2025-08-26T19:56:09.2544926Z >>> optimizer = Adagrad(my_model.parameters()) 2025-08-26T19:56:09.2545058Z >>> model_state_dict = my_model.state_dict() 2025-08-26T19:56:09.2545312Z >>> fs_storage_reader = torch.distributed.checkpoint.FileSystemReader( 2025-08-26T19:56:09.2545450Z ... "/checkpoint/1" 2025-08-26T19:56:09.2545535Z ... ) 2025-08-26T19:56:09.2545629Z 2025-08-26T19:56:09.2545787Z >>> torch.distributed.checkpoint.load_state_dict( 2025-08-26T19:56:09.2545901Z >>> state_dict=model_state_dict, 2025-08-26T19:56:09.2546034Z >>> storage_reader=fs_storage_reader, 2025-08-26T19:56:09.2546118Z >>> ) 2025-08-26T19:56:09.2546209Z 2025-08-26T19:56:09.2546435Z >>> # module.load_state_dict() function might have customized steps 2025-08-26T19:56:09.2546565Z >>> # to flush the state_dict, must call it to 2025-08-26T19:56:09.2546684Z >>> # ensure correct behavior. 2025-08-26T19:56:09.2546817Z >>> my_model.load_state_dict(model_state_dict) 2025-08-26T19:56:09.2546913Z 2025-08-26T19:56:09.2568001Z .. note:: 2025-08-26T19:56:09.2568412Z load_state_dict uses collectives to coordinate reads across ranks. 2025-08-26T19:56:09.2568667Z For NCCL-based process groups, internal tensor representations of 2025-08-26T19:56:09.2569001Z objects must be moved to the GPU device before communication takes place. 2025-08-26T19:56:09.2569263Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T19:56:09.2569535Z and it is the user's responsibility to ensure that this is set so that each 2025-08-26T19:56:09.2569724Z rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T19:56:09.2569823Z 2025-08-26T19:56:09.2570086Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2570185Z 2025-08-26T19:56:09.2570285Z warnings.warn(msg) 2025-08-26T19:56:09.2570368Z 2025-08-26T19:56:09.2570633Z --- Parse Warning: 70 / 146 --- 2025-08-26T19:56:09.2571628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=97. 2025-08-26T19:56:09.2571915Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2571999Z 2025-08-26T19:56:09.2572123Z Save a distributed model in SPMD style. 2025-08-26T19:56:09.2572220Z 2025-08-26T19:56:09.2572416Z This function is different from ``torch.save()`` as it handles 2025-08-26T19:56:09.2572693Z ``ShardedTensor`` , and ``DTensor`` by having each rank only save their local shards. 2025-08-26T19:56:09.2572777Z 2025-08-26T19:56:09.2573038Z For each ``Stateful`` object (having both a ``state_dict`` and a ``load_state_dict``), 2025-08-26T19:56:09.2573205Z save will call ``state_dict`` before serialization. 2025-08-26T19:56:09.2573283Z 2025-08-26T19:56:09.2573391Z .. warning:: 2025-08-26T19:56:09.2573637Z There is no guarantees of Backwards Compatibility across PyTorch versions 2025-08-26T19:56:09.2573791Z for saved state_dicts. 2025-08-26T19:56:09.2573887Z 2025-08-26T19:56:09.2573977Z .. warning:: 2025-08-26T19:56:09.2574199Z If using the `process_group` argument, make sure that only its ranks 2025-08-26T19:56:09.2574407Z call `save_state_dict` and that all data in state_dict belong to it. 2025-08-26T19:56:09.2574489Z 2025-08-26T19:56:09.2574586Z .. note:: 2025-08-26T19:56:09.2574850Z When saving checkpoint for FSDP's `ShardingStrategy.HYBRID_SHARD`, only one of 2025-08-26T19:56:09.2575133Z the shard_group should be calling `save_state_dict` and the corresponding process 2025-08-26T19:56:09.2575246Z group needs to be passed in. 2025-08-26T19:56:09.2575328Z 2025-08-26T19:56:09.2575430Z .. note:: 2025-08-26T19:56:09.2575703Z If no process group is available, this function assumes the intention is to save the 2025-08-26T19:56:09.2575836Z state_dict in the local process. 2025-08-26T19:56:09.2575916Z 2025-08-26T19:56:09.2576033Z .. note: 2025-08-26T19:56:09.2576193Z Rank 0 is assumed to be the coordinator rank. 2025-08-26T19:56:09.2576274Z 2025-08-26T19:56:09.2576357Z 2025-08-26T19:56:09.2576449Z Args: 2025-08-26T19:56:09.2576606Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T19:56:09.2576766Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T19:56:09.2576981Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T19:56:09.2577216Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T19:56:09.2577400Z It can also be a key if the storage is a key-value store. 2025-08-26T19:56:09.2577499Z (Default: ``None``) 2025-08-26T19:56:09.2577647Z storage_writer (Optional[StorageWriter]): 2025-08-26T19:56:09.2577886Z Instance of StorageWriter used to perform writes. If this is not 2025-08-26T19:56:09.2578100Z specified, DCP will automatically infer the writer based on the 2025-08-26T19:56:09.2578318Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T19:56:09.2578431Z be raised. (Default: ``None``) 2025-08-26T19:56:09.2578564Z planner (Optional[SavePlanner]): 2025-08-26T19:56:09.2578763Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T19:56:09.2578908Z planner will be used. (Default: ``None``) 2025-08-26T19:56:09.2579040Z process_group (Optional[ProcessGroup]): 2025-08-26T19:56:09.2579226Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T19:56:09.2579337Z (Default: ``None``) 2025-08-26T19:56:09.2579431Z no_dist (bool): 2025-08-26T19:56:09.2579602Z If ``True``, this function will assume the intent is to load 2025-08-26T19:56:09.2579741Z a checkpoint on a single rank/process. 2025-08-26T19:56:09.2579845Z (Default: ``False``) 2025-08-26T19:56:09.2580121Z use_collectives (bool): If ``False``, this function will assume the intent is to save 2025-08-26T19:56:09.2580298Z a checkpoint without using cross-rank synchronization. 2025-08-26T19:56:09.2580398Z (Default: ``True``) 2025-08-26T19:56:09.2580639Z This configuration is experimental and should be used with caution. 2025-08-26T19:56:09.2580915Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T19:56:09.2581010Z 2025-08-26T19:56:09.2581097Z Returns: 2025-08-26T19:56:09.2581261Z Metadata: Metadata object for the saved checkpoint. 2025-08-26T19:56:09.2581355Z 2025-08-26T19:56:09.2581442Z Example: 2025-08-26T19:56:09.2581553Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2581655Z >>> my_model = MyModule() 2025-08-26T19:56:09.2581737Z 2025-08-26T19:56:09.2581868Z >>> state_dict = {"model": my_model} 2025-08-26T19:56:09.2581977Z 2025-08-26T19:56:09.2582232Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T19:56:09.2582333Z ... "/checkpoint/1" 2025-08-26T19:56:09.2582416Z ... ) 2025-08-26T19:56:09.2582560Z >>> torch.distributed.checkpoint.save( 2025-08-26T19:56:09.2582666Z >>> state_dict=state_dict, 2025-08-26T19:56:09.2582799Z >>> storage_writer=fs_storage_writer, 2025-08-26T19:56:09.2582882Z >>> ) 2025-08-26T19:56:09.2582962Z 2025-08-26T19:56:09.2583057Z .. note:: 2025-08-26T19:56:09.2583277Z save_state_dict uses collectives to coordinate writes across ranks. 2025-08-26T19:56:09.2583495Z For NCCL-based process groups, internal tensor representations of 2025-08-26T19:56:09.2583739Z objects must be moved to the GPU device before communication takes place. 2025-08-26T19:56:09.2583966Z In this case, the device used is given by ``torch.cuda.current_device()`` 2025-08-26T19:56:09.2584189Z and it is the user's responsibility to ensure that this is set so that 2025-08-26T19:56:09.2584417Z each rank has an individual GPU, via ``torch.cuda.set_device()``. 2025-08-26T19:56:09.2584505Z 2025-08-26T19:56:09.2584762Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2584841Z 2025-08-26T19:56:09.2584952Z warnings.warn(msg) 2025-08-26T19:56:09.2585035Z 2025-08-26T19:56:09.2585240Z --- Parse Warning: 71 / 146 --- 2025-08-26T19:56:09.2586308Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_save in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/checkpoint/state_dict_saver.py line=230. 2025-08-26T19:56:09.2586579Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2586886Z Asynchronous version of ``save``. This code first de-stages the state_dict on to the 2025-08-26T19:56:09.2587186Z staging storage (defaults to CPU memory), and then calls the `save` in a separate thread. 2025-08-26T19:56:09.2587279Z 2025-08-26T19:56:09.2587370Z .. warning:: 2025-08-26T19:56:09.2587535Z This feature is experimental and subject to change. 2025-08-26T19:56:09.2587691Z MUST CALL CLOSE AFTER LAST CHECKPOINT IS SAVED 2025-08-26T19:56:09.2587773Z 2025-08-26T19:56:09.2587868Z Args: 2025-08-26T19:56:09.2588024Z state_dict (Dict[str, Any]): The state_dict to save. 2025-08-26T19:56:09.2588172Z checkpoint_id (Union[str, os.PathLike, None]): 2025-08-26T19:56:09.2588402Z The ID of this checkpoint instance. The meaning of the checkpoint_id 2025-08-26T19:56:09.2588612Z depends on the storage. It can be a path to a folder or to a file. 2025-08-26T19:56:09.2588792Z It can also be a key if the storage is a key-value store. 2025-08-26T19:56:09.2588896Z (Default: ``None``) 2025-08-26T19:56:09.2589034Z storage_writer (Optional[StorageWriter]): 2025-08-26T19:56:09.2589258Z Instance of StorageWriter used to perform 'stage' and 'save'. If 2025-08-26T19:56:09.2589501Z this is not specified, DCP will automatically infer the writer based on the 2025-08-26T19:56:09.2589719Z checkpoint_id. If checkpoint_id is also None, an exception will 2025-08-26T19:56:09.2589834Z be raised. (Default: ``None``) 2025-08-26T19:56:09.2589957Z planner (Optional[SavePlanner]): 2025-08-26T19:56:09.2590175Z Instance of SavePlanner. If this is not specified, the default 2025-08-26T19:56:09.2590308Z planner will be used. (Default: ``None``) 2025-08-26T19:56:09.2590453Z process_group (Optional[ProcessGroup]): 2025-08-26T19:56:09.2590641Z ProcessGroup to be used for cross-rank synchronization. 2025-08-26T19:56:09.2590772Z (Default: ``None``) 2025-08-26T19:56:09.2590945Z async_checkpointer_type (AsyncCheckpointerType): 2025-08-26T19:56:09.2591118Z whether to do checkpoint in separate thread or process 2025-08-26T19:56:09.2591277Z (Default: ``AsyncCheckpointerType.THREAD``) 2025-08-26T19:56:09.2591388Z async_stager (AsyncStager): 2025-08-26T19:56:09.2591651Z provides staging implementation. If storage_writer implements AsyncStager 2025-08-26T19:56:09.2591876Z and async_stager is provided, async_stager will be used for staging 2025-08-26T19:56:09.2591974Z no_dist (bool): 2025-08-26T19:56:09.2592157Z If ``True``, this function will assume the intent is to save 2025-08-26T19:56:09.2592286Z a checkpoint on a single rank/process. 2025-08-26T19:56:09.2592385Z (Default: ``False``) 2025-08-26T19:56:09.2592713Z use_collectives: If False, Save the checkpoint without rank coordination. (Default: ``True``) 2025-08-26T19:56:09.2592984Z This configuration is experimental and should be used with caution. 2025-08-26T19:56:09.2593264Z It will change the format of the saved checkpoint and may not be backward compatible. 2025-08-26T19:56:09.2593346Z 2025-08-26T19:56:09.2593432Z Returns: 2025-08-26T19:56:09.2593660Z Future: A future holding the resultant Metadata object from `save`. 2025-08-26T19:56:09.2593745Z 2025-08-26T19:56:09.2593838Z Example: 2025-08-26T19:56:09.2593939Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2594068Z >>> my_model = MyModule() 2025-08-26T19:56:09.2594163Z 2025-08-26T19:56:09.2594280Z >>> state_dict = {"model": my_model} 2025-08-26T19:56:09.2594370Z 2025-08-26T19:56:09.2594606Z >>> fs_storage_writer = torch.distributed.checkpoint.FileSystemWriter( 2025-08-26T19:56:09.2594734Z ... "/checkpoint/1" 2025-08-26T19:56:09.2594836Z ... ) 2025-08-26T19:56:09.2595051Z >>> checkpoint_future = torch.distributed.checkpoint.async_save( 2025-08-26T19:56:09.2595158Z >>> state_dict=state_dict, 2025-08-26T19:56:09.2595293Z >>> storage_writer=fs_storage_writer, 2025-08-26T19:56:09.2595378Z >>> ) 2025-08-26T19:56:09.2595477Z >>> 2025-08-26T19:56:09.2595578Z >>> # ... do some work ... 2025-08-26T19:56:09.2595664Z >>> 2025-08-26T19:56:09.2595787Z >>> checkpoint_future.result() 2025-08-26T19:56:09.2595866Z 2025-08-26T19:56:09.2595958Z 2025-08-26T19:56:09.2596215Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2596298Z 2025-08-26T19:56:09.2596407Z warnings.warn(msg) 2025-08-26T19:56:09.2596486Z 2025-08-26T19:56:09.2596690Z --- Parse Warning: 72 / 146 --- 2025-08-26T19:56:09.2597773Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=construct_and_record_rdzv_event in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/elastic/events/__init__.py line=94. 2025-08-26T19:56:09.2598045Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2598138Z 2025-08-26T19:56:09.2598346Z Initialize rendezvous event object and record its operations. 2025-08-26T19:56:09.2598439Z 2025-08-26T19:56:09.2598525Z Args: 2025-08-26T19:56:09.2598657Z run_id (str): The run id of the rendezvous. 2025-08-26T19:56:09.2598818Z message (str): The message describing the event. 2025-08-26T19:56:09.2599077Z node_state (NodeState): The state of the node (INIT, RUNNING, SUCCEEDED, FAILED). 2025-08-26T19:56:09.2599271Z name (str): Event name. (E.g. Current action being performed). 2025-08-26T19:56:09.2599393Z hostname (str): Hostname of the node. 2025-08-26T19:56:09.2599567Z pid (Optional[int]): The process id of the node. 2025-08-26T19:56:09.2599830Z master_endpoint (str): The master endpoint for the rendezvous store, if known. 2025-08-26T19:56:09.2600105Z local_id (Optional[int]): The local_id of the node, if defined in dynamic_rendezvous.py 2025-08-26T19:56:09.2600274Z rank (Optional[int]): The rank of the node, if known. 2025-08-26T19:56:09.2600361Z Returns: 2025-08-26T19:56:09.2600449Z None 2025-08-26T19:56:09.2600545Z Example: 2025-08-26T19:56:09.2600673Z >>> # See DynamicRendezvousHandler class 2025-08-26T19:56:09.2600778Z >>> def _record( 2025-08-26T19:56:09.2600865Z ... self, 2025-08-26T19:56:09.2600958Z ... message: str, 2025-08-26T19:56:09.2601113Z ... node_state: NodeState = NodeState.RUNNING, 2025-08-26T19:56:09.2601228Z ... rank: Optional[int] = None, 2025-08-26T19:56:09.2601326Z ... ) -> None: 2025-08-26T19:56:09.2601451Z ... construct_and_record_rdzv_event( 2025-08-26T19:56:09.2601646Z ... name=f"{self.__class__.__name__}.{get_method_name()}", 2025-08-26T19:56:09.2601779Z ... run_id=self._settings.run_id, 2025-08-26T19:56:09.2601879Z ... message=message, 2025-08-26T19:56:09.2601987Z ... node_state=node_state, 2025-08-26T19:56:09.2602118Z ... hostname=self._this_node.addr, 2025-08-26T19:56:09.2602227Z ... pid=self._this_node.pid, 2025-08-26T19:56:09.2602365Z ... local_id=self._this_node.local_id, 2025-08-26T19:56:09.2602486Z ... rank=rank, 2025-08-26T19:56:09.2602571Z ... ) 2025-08-26T19:56:09.2602664Z 2025-08-26T19:56:09.2602925Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2603014Z 2025-08-26T19:56:09.2603112Z warnings.warn(msg) 2025-08-26T19:56:09.2603193Z 2025-08-26T19:56:09.2603425Z --- Parse Warning: 73 / 146 --- 2025-08-26T19:56:09.2604378Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixedPrecision in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=114. 2025-08-26T19:56:09.2604655Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2604735Z 2025-08-26T19:56:09.2604904Z This configures FSDP-native mixed precision training. 2025-08-26T19:56:09.2604996Z 2025-08-26T19:56:09.2605085Z Attributes: 2025-08-26T19:56:09.2605338Z param_dtype (Optional[torch.dtype]): This specifies the dtype for model 2025-08-26T19:56:09.2605540Z parameters during forward and backward and thus the dtype for 2025-08-26T19:56:09.2605764Z forward and backward computation. Outside forward and backward, the 2025-08-26T19:56:09.2605970Z *sharded* parameters are kept in full precision (e.g. for the 2025-08-26T19:56:09.2606182Z optimizer step), and for model checkpointing, the parameters are 2025-08-26T19:56:09.2606354Z always saved in full precision. (Default: ``None``) 2025-08-26T19:56:09.2606571Z reduce_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T19:56:09.2606784Z gradient reduction (i.e. reduce-scatter or all-reduce). If this is 2025-08-26T19:56:09.2606974Z ``None`` but ``param_dtype`` is not ``None``, then this takes on 2025-08-26T19:56:09.2607175Z the ``param_dtype`` value, still running gradient reduction in low 2025-08-26T19:56:09.2607398Z precision. This is permitted to differ from ``param_dtype``, e.g. 2025-08-26T19:56:09.2607600Z to force gradient reduction to run in full precision. (Default: 2025-08-26T19:56:09.2607701Z ``None``) 2025-08-26T19:56:09.2607915Z buffer_dtype (Optional[torch.dtype]): This specifies the dtype for 2025-08-26T19:56:09.2608146Z buffers. FSDP does not shard buffers. Rather, FSDP casts them to 2025-08-26T19:56:09.2608355Z ``buffer_dtype`` in the first forward pass and keeps them in that 2025-08-26T19:56:09.2608569Z dtype thereafter. For model checkpointing, the buffers are saved 2025-08-26T19:56:09.2608763Z in full precision except for ``LOCAL_STATE_DICT``. (Default: 2025-08-26T19:56:09.2608935Z ``None``) 2025-08-26T19:56:09.2609136Z keep_low_precision_grads (bool): If ``False``, then FSDP upcasts 2025-08-26T19:56:09.2609362Z gradients to full precision after the backward pass in preparation 2025-08-26T19:56:09.2609566Z for the optimizer step. If ``True``, then FSDP keeps the gradients 2025-08-26T19:56:09.2609776Z in the dtype used for gradient reduction, which can save memory if 2025-08-26T19:56:09.2609982Z using a custom optimizer that supports running in low precision. 2025-08-26T19:56:09.2610087Z (Default: ``False``) 2025-08-26T19:56:09.2610312Z cast_forward_inputs (bool): If ``True``, then this FSDP module casts 2025-08-26T19:56:09.2610549Z its forward args and kwargs to ``param_dtype``. This is to ensure 2025-08-26T19:56:09.2610779Z that parameter and input dtypes match for forward computation, as 2025-08-26T19:56:09.2610988Z required by many ops. This may need to be set to ``True`` when only 2025-08-26T19:56:09.2611212Z applying mixed precision to some but not all FSDP modules, in which 2025-08-26T19:56:09.2611457Z case a mixed-precision FSDP submodule needs to recast its inputs. 2025-08-26T19:56:09.2611558Z (Default: ``False``) 2025-08-26T19:56:09.2611791Z cast_root_forward_inputs (bool): If ``True``, then the root FSDP module 2025-08-26T19:56:09.2611993Z casts its forward args and kwargs to ``param_dtype``, overriding 2025-08-26T19:56:09.2612210Z the value of ``cast_forward_inputs``. For non-root FSDP modules, 2025-08-26T19:56:09.2612366Z this does not do anything. (Default: ``True``) 2025-08-26T19:56:09.2612586Z _module_classes_to_ignore: (Sequence[Type[nn.Module]]): This specifies 2025-08-26T19:56:09.2612781Z module classes to ignore for mixed precision when using an 2025-08-26T19:56:09.2612959Z ``auto_wrap_policy``: Modules of these classes will have FSDP 2025-08-26T19:56:09.2613184Z applied to them separately with mixed precision disabled (meaning 2025-08-26T19:56:09.2613388Z that the final FSDP construction would deviate from the specified 2025-08-26T19:56:09.2613582Z policy). If ``auto_wrap_policy`` is not specified, then this does 2025-08-26T19:56:09.2613792Z not do anything. This API is experimental and subject to change. 2025-08-26T19:56:09.2613902Z (Default: ``(_BatchNorm,)``) 2025-08-26T19:56:09.2613994Z 2025-08-26T19:56:09.2614167Z .. note:: This API is experimental and subject to change. 2025-08-26T19:56:09.2614249Z 2025-08-26T19:56:09.2614483Z .. note:: Only floating point tensors are cast to their specified dtypes. 2025-08-26T19:56:09.2614565Z 2025-08-26T19:56:09.2614761Z .. note:: In ``summon_full_params``, parameters are forced to full 2025-08-26T19:56:09.2614874Z precision, but buffers are not. 2025-08-26T19:56:09.2614955Z 2025-08-26T19:56:09.2615173Z .. note:: Layer norm and batch norm accumulate in ``float32`` even when 2025-08-26T19:56:09.2615382Z their inputs are in a low precision like ``float16`` or ``bfloat16``. 2025-08-26T19:56:09.2615630Z Disabling FSDP's mixed precision for those norm modules only means that 2025-08-26T19:56:09.2615844Z the affine parameters are kept in ``float32``. However, this incurs 2025-08-26T19:56:09.2616083Z separate all-gathers and reduce-scatters for those norm modules, which 2025-08-26T19:56:09.2616318Z may be inefficient, so if the workload permits, the user should prefer 2025-08-26T19:56:09.2616497Z to still apply mixed precision to those modules. 2025-08-26T19:56:09.2616592Z 2025-08-26T19:56:09.2616797Z .. note:: By default, if the user passes a model with any ``_BatchNorm`` 2025-08-26T19:56:09.2617004Z modules and specifies an ``auto_wrap_policy``, then the batch norm 2025-08-26T19:56:09.2617246Z modules will have FSDP applied to them separately with mixed precision 2025-08-26T19:56:09.2617424Z disabled. See the ``_module_classes_to_ignore`` argument. 2025-08-26T19:56:09.2617516Z 2025-08-26T19:56:09.2617724Z .. note:: ``MixedPrecision`` has ``cast_root_forward_inputs=True`` and 2025-08-26T19:56:09.2617941Z ``cast_forward_inputs=False`` by default. For the root FSDP instance, 2025-08-26T19:56:09.2618127Z its ``cast_root_forward_inputs`` takes precedence over its 2025-08-26T19:56:09.2618309Z ``cast_forward_inputs``. For non-root FSDP instances, their 2025-08-26T19:56:09.2618542Z ``cast_root_forward_inputs`` values are ignored. The default setting is 2025-08-26T19:56:09.2618795Z sufficient for the typical case where each FSDP instance has the same 2025-08-26T19:56:09.2619025Z ``MixedPrecision`` configuration and only needs to cast inputs to the 2025-08-26T19:56:09.2619220Z ``param_dtype`` at the beginning of the model's forward pass. 2025-08-26T19:56:09.2619300Z 2025-08-26T19:56:09.2619521Z .. note:: For nested FSDP instances with different ``MixedPrecision`` 2025-08-26T19:56:09.2619766Z configurations, we recommend setting individual ``cast_forward_inputs`` 2025-08-26T19:56:09.2620010Z values to configure casting inputs or not before each instance's 2025-08-26T19:56:09.2620208Z forward. In such a case, since the casts happen before each FSDP 2025-08-26T19:56:09.2620423Z instance's forward, a parent FSDP instance should have its non-FSDP 2025-08-26T19:56:09.2620698Z submodules run before its FSDP submodules to avoid the activation dtype 2025-08-26T19:56:09.2620908Z being changed due to a different ``MixedPrecision`` configuration. 2025-08-26T19:56:09.2621001Z 2025-08-26T19:56:09.2621090Z Example:: 2025-08-26T19:56:09.2621168Z 2025-08-26T19:56:09.2621315Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2621484Z >>> model = nn.Sequential(nn.Linear(3, 3), nn.Linear(3, 3)) 2025-08-26T19:56:09.2621580Z >>> model[1] = FSDP( 2025-08-26T19:56:09.2621682Z >>> model[1], 2025-08-26T19:56:09.2621995Z >>> mixed_precision=MixedPrecision(param_dtype=torch.float16, cast_forward_inputs=True), 2025-08-26T19:56:09.2622092Z >>> ) 2025-08-26T19:56:09.2622187Z >>> model = FSDP( 2025-08-26T19:56:09.2622277Z >>> model, 2025-08-26T19:56:09.2622603Z >>> mixed_precision=MixedPrecision(param_dtype=torch.bfloat16, cast_forward_inputs=True), 2025-08-26T19:56:09.2622689Z >>> ) 2025-08-26T19:56:09.2622781Z 2025-08-26T19:56:09.2622995Z The above shows a working example. On the other hand, if ``model[1]`` 2025-08-26T19:56:09.2623196Z were replaced with ``model[0]``, meaning that the submodule using 2025-08-26T19:56:09.2623432Z different ``MixedPrecision`` ran its forward first, then ``model[1]`` 2025-08-26T19:56:09.2623651Z would incorrectly see ``float16`` activations instead of ``bfloat16`` 2025-08-26T19:56:09.2623746Z ones. 2025-08-26T19:56:09.2623828Z 2025-08-26T19:56:09.2623909Z 2025-08-26T19:56:09.2624180Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2624257Z 2025-08-26T19:56:09.2624365Z warnings.warn(msg) 2025-08-26T19:56:09.2624444Z 2025-08-26T19:56:09.2624657Z --- Parse Warning: 74 / 146 --- 2025-08-26T19:56:09.2625646Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullStateDictConfig in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/api.py line=295. 2025-08-26T19:56:09.2625960Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2626058Z 2025-08-26T19:56:09.2626267Z ``FullStateDictConfig`` is a config class meant to be used with 2025-08-26T19:56:09.2626470Z ``StateDictType.FULL_STATE_DICT``. We recommend enabling both 2025-08-26T19:56:09.2626686Z ``offload_to_cpu=True`` and ``rank0_only=True`` when saving full state 2025-08-26T19:56:09.2626914Z dicts to save GPU memory and CPU memory, respectively. This config class 2025-08-26T19:56:09.2627129Z is meant to be used via the :func:`state_dict_type` context manager as 2025-08-26T19:56:09.2627214Z follows: 2025-08-26T19:56:09.2627293Z 2025-08-26T19:56:09.2627442Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2627682Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:56:09.2627828Z >>> fsdp = FSDP(model, auto_wrap_policy=...) 2025-08-26T19:56:09.2628061Z >>> cfg = FullStateDictConfig(offload_to_cpu=True, rank0_only=True) 2025-08-26T19:56:09.2628284Z >>> with FSDP.state_dict_type(fsdp, StateDictType.FULL_STATE_DICT, cfg): 2025-08-26T19:56:09.2628406Z >>> state = fsdp.state_dict() 2025-08-26T19:56:09.2628618Z >>> # `state` will be empty on non rank 0 and contain CPU tensors on rank 0. 2025-08-26T19:56:09.2628872Z >>> # To reload checkpoint for inference, finetuning, transfer learning, etc: 2025-08-26T19:56:09.2629135Z >>> model = model_fn() # Initialize model in preparation for wrapping with FSDP 2025-08-26T19:56:09.2629241Z >>> if dist.get_rank() == 0: 2025-08-26T19:56:09.2629440Z >>> # Load checkpoint only on rank 0 to avoid memory redundancy 2025-08-26T19:56:09.2629581Z >>> state_dict = torch.load("my_checkpoint.pt") 2025-08-26T19:56:09.2629741Z >>> model.load_state_dict(state_dict) 2025-08-26T19:56:09.2629980Z >>> # All ranks initialize FSDP module as usual. `sync_module_states` argument 2025-08-26T19:56:09.2630231Z >>> # communicates loaded checkpoint states from rank 0 to rest of the world. 2025-08-26T19:56:09.2630324Z >>> fsdp = FSDP( 2025-08-26T19:56:09.2630408Z ... model, 2025-08-26T19:56:09.2630556Z ... device_id=torch.cuda.current_device(), 2025-08-26T19:56:09.2630659Z ... auto_wrap_policy=..., 2025-08-26T19:56:09.2630765Z ... sync_module_states=True, 2025-08-26T19:56:09.2630860Z ... ) 2025-08-26T19:56:09.2631073Z >>> # After this point, all ranks have FSDP model with loaded checkpoint. 2025-08-26T19:56:09.2631164Z 2025-08-26T19:56:09.2631253Z Attributes: 2025-08-26T19:56:09.2631453Z rank0_only (bool): If ``True``, then only rank 0 saves the full state 2025-08-26T19:56:09.2631673Z dict, and nonzero ranks save an empty dict. If ``False``, then all 2025-08-26T19:56:09.2631833Z ranks save the full state dict. (Default: ``False``) 2025-08-26T19:56:09.2631928Z 2025-08-26T19:56:09.2632184Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2632271Z 2025-08-26T19:56:09.2632378Z warnings.warn(msg) 2025-08-26T19:56:09.2632454Z 2025-08-26T19:56:09.2632663Z --- Parse Warning: 75 / 146 --- 2025-08-26T19:56:09.2633878Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.set_state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=634. 2025-08-26T19:56:09.2634152Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2634403Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T19:56:09.2634512Z 2025-08-26T19:56:09.2634792Z Also takes (optional) configuration for the model's and optimizer's state dict. 2025-08-26T19:56:09.2634998Z The target module does not have to be a FSDP module. If the target 2025-08-26T19:56:09.2635217Z module is a FSDP module, its ``state_dict_type`` will also be changed. 2025-08-26T19:56:09.2635297Z 2025-08-26T19:56:09.2635491Z .. note:: This API should be called for only the top-level (root) 2025-08-26T19:56:09.2635589Z module. 2025-08-26T19:56:09.2635666Z 2025-08-26T19:56:09.2635888Z .. note:: This API enables users to transparently use the conventional 2025-08-26T19:56:09.2636082Z ``state_dict`` API to take model checkpoints in cases where the 2025-08-26T19:56:09.2636287Z root FSDP module is wrapped by another ``nn.Module``. For example, 2025-08-26T19:56:09.2636508Z the following will ensure ``state_dict`` is called on all non-FSDP 2025-08-26T19:56:09.2636744Z instances, while dispatching into `sharded_state_dict` implementation 2025-08-26T19:56:09.2636871Z for FSDP: 2025-08-26T19:56:09.2636951Z 2025-08-26T19:56:09.2637039Z Example:: 2025-08-26T19:56:09.2637129Z 2025-08-26T19:56:09.2637261Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2637575Z >>> model = DDP(FSDP(...)) 2025-08-26T19:56:09.2637690Z >>> FSDP.set_state_dict_type( 2025-08-26T19:56:09.2637780Z >>> model, 2025-08-26T19:56:09.2637997Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T19:56:09.2638214Z >>> state_dict_config = ShardedStateDictConfig(offload_to_cpu=True), 2025-08-26T19:56:09.2638451Z >>> optim_state_dict_config = OptimStateDictConfig(offload_to_cpu=True), 2025-08-26T19:56:09.2638539Z >>> ) 2025-08-26T19:56:09.2638704Z >>> param_state_dict = model.state_dict() 2025-08-26T19:56:09.2638895Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T19:56:09.2638970Z 2025-08-26T19:56:09.2639067Z Args: 2025-08-26T19:56:09.2639194Z module (torch.nn.Module): Root module. 2025-08-26T19:56:09.2639425Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T19:56:09.2639676Z state_dict_config (Optional[StateDictConfig]): the configuration for the 2025-08-26T19:56:09.2639787Z target ``state_dict_type``. 2025-08-26T19:56:09.2640055Z optim_state_dict_config (Optional[OptimStateDictConfig]): the configuration 2025-08-26T19:56:09.2640173Z for the optimizer state dict. 2025-08-26T19:56:09.2640248Z 2025-08-26T19:56:09.2640350Z Returns: 2025-08-26T19:56:09.2640571Z A StateDictSettings that include the previous state_dict type and 2025-08-26T19:56:09.2640699Z configuration for the module. 2025-08-26T19:56:09.2640783Z 2025-08-26T19:56:09.2641038Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2641135Z 2025-08-26T19:56:09.2641230Z warnings.warn(msg) 2025-08-26T19:56:09.2641307Z 2025-08-26T19:56:09.2641521Z --- Parse Warning: 76 / 146 --- 2025-08-26T19:56:09.2642722Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.state_dict_type in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=792. 2025-08-26T19:56:09.2642997Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2643246Z Set the ``state_dict_type`` of all the descendant FSDP modules of the target module. 2025-08-26T19:56:09.2643336Z 2025-08-26T19:56:09.2643706Z This context manager has the same functions as :meth:`set_state_dict_type`. Read the document of 2025-08-26T19:56:09.2643838Z :meth:`set_state_dict_type` for the detail. 2025-08-26T19:56:09.2643930Z 2025-08-26T19:56:09.2644017Z Example:: 2025-08-26T19:56:09.2644103Z 2025-08-26T19:56:09.2644238Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2644342Z >>> model = DDP(FSDP(...)) 2025-08-26T19:56:09.2644467Z >>> with FSDP.state_dict_type( 2025-08-26T19:56:09.2644554Z >>> model, 2025-08-26T19:56:09.2644689Z >>> StateDictType.SHARDED_STATE_DICT, 2025-08-26T19:56:09.2644790Z >>> ): 2025-08-26T19:56:09.2644909Z >>> checkpoint = model.state_dict() 2025-08-26T19:56:09.2644995Z 2025-08-26T19:56:09.2645078Z Args: 2025-08-26T19:56:09.2645203Z module (torch.nn.Module): Root module. 2025-08-26T19:56:09.2645453Z state_dict_type (StateDictType): the desired ``state_dict_type`` to set. 2025-08-26T19:56:09.2645718Z state_dict_config (Optional[StateDictConfig]): the model ``state_dict`` 2025-08-26T19:56:09.2645888Z configuration for the target ``state_dict_type``. 2025-08-26T19:56:09.2646123Z optim_state_dict_config (Optional[OptimStateDictConfig]): the optimizer 2025-08-26T19:56:09.2646320Z ``state_dict`` configuration for the target ``state_dict_type``. 2025-08-26T19:56:09.2646415Z 2025-08-26T19:56:09.2646693Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2646784Z 2025-08-26T19:56:09.2646879Z warnings.warn(msg) 2025-08-26T19:56:09.2646954Z 2025-08-26T19:56:09.2647152Z --- Parse Warning: 77 / 146 --- 2025-08-26T19:56:09.2648389Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1805. 2025-08-26T19:56:09.2648667Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2648745Z 2025-08-26T19:56:09.2649070Z Transform the state-dict of an optimizer corresponding to a sharded model. 2025-08-26T19:56:09.2649153Z 2025-08-26T19:56:09.2649345Z The given state-dict can be transformed to one of three types: 2025-08-26T19:56:09.2649663Z 1) full optimizer state_dict, 2) sharded optimizer state_dict, 3) local optimizer state_dict. 2025-08-26T19:56:09.2649746Z 2025-08-26T19:56:09.2649992Z For full optimizer state_dict, all states are unflattened and not sharded. 2025-08-26T19:56:09.2650210Z Rank0 only and CPU only can be specified via :meth:`state_dict_type` to 2025-08-26T19:56:09.2650295Z avoid OOM. 2025-08-26T19:56:09.2650389Z 2025-08-26T19:56:09.2650630Z For sharded optimizer state_dict, all states are unflattened but sharded. 2025-08-26T19:56:09.2650848Z CPU only can be specified via :meth:`state_dict_type` to further save 2025-08-26T19:56:09.2650933Z memory. 2025-08-26T19:56:09.2651009Z 2025-08-26T19:56:09.2651236Z For local state_dict, no transformation will be performed. But a state 2025-08-26T19:56:09.2651476Z will be converted from nn.Tensor to ShardedTensor to represent its sharding 2025-08-26T19:56:09.2651589Z nature (this is not supported yet). 2025-08-26T19:56:09.2651677Z 2025-08-26T19:56:09.2651765Z Example:: 2025-08-26T19:56:09.2651855Z 2025-08-26T19:56:09.2651986Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2652221Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:56:09.2652389Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T19:56:09.2652568Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T19:56:09.2652817Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T19:56:09.2652916Z >>> # Save a checkpoint 2025-08-26T19:56:09.2653015Z >>> model, optim = ... 2025-08-26T19:56:09.2653134Z >>> FSDP.set_state_dict_type( 2025-08-26T19:56:09.2653214Z >>> model, 2025-08-26T19:56:09.2653344Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:56:09.2653472Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2653616Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2653710Z >>> ) 2025-08-26T19:56:09.2653820Z >>> state_dict = model.state_dict() 2025-08-26T19:56:09.2653999Z >>> optim_state_dict = FSDP.optim_state_dict(model, optim) 2025-08-26T19:56:09.2654145Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T19:56:09.2654240Z >>> # Load a checkpoint 2025-08-26T19:56:09.2654348Z >>> model, optim = ... 2025-08-26T19:56:09.2654500Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T19:56:09.2654643Z >>> FSDP.set_state_dict_type( 2025-08-26T19:56:09.2654730Z >>> model, 2025-08-26T19:56:09.2654844Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:56:09.2654982Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2655124Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2655216Z >>> ) 2025-08-26T19:56:09.2655332Z >>> model.load_state_dict(state_dict) 2025-08-26T19:56:09.2655504Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T19:56:09.2655632Z >>> model, optim, optim_state_dict 2025-08-26T19:56:09.2655711Z >>> ) 2025-08-26T19:56:09.2655836Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T19:56:09.2655927Z 2025-08-26T19:56:09.2656006Z Args: 2025-08-26T19:56:09.2656248Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T19:56:09.2656455Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T19:56:09.2656585Z were passed into the optimizer ``optim``. 2025-08-26T19:56:09.2656776Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T19:56:09.2656864Z parameters. 2025-08-26T19:56:09.2657091Z optim_state_dict (Dict[str, Any]): the target optimizer state_dict to 2025-08-26T19:56:09.2657302Z transform. If the value is None, optim.state_dict() will be used. ( 2025-08-26T19:56:09.2657396Z Default: ``None``) 2025-08-26T19:56:09.2657649Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T19:56:09.2657828Z are sharded or ``None`` if using the default process group. ( 2025-08-26T19:56:09.2657938Z Default: ``None``) 2025-08-26T19:56:09.2658016Z 2025-08-26T19:56:09.2658099Z Returns: 2025-08-26T19:56:09.2658308Z Dict[str, Any]: A :class:`dict` containing the optimizer state for 2025-08-26T19:56:09.2658475Z ``model``. The sharding of the optimizer state is based on 2025-08-26T19:56:09.2658582Z ``state_dict_type``. 2025-08-26T19:56:09.2658661Z 2025-08-26T19:56:09.2658914Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2659005Z 2025-08-26T19:56:09.2659100Z warnings.warn(msg) 2025-08-26T19:56:09.2659192Z 2025-08-26T19:56:09.2659392Z --- Parse Warning: 78 / 146 --- 2025-08-26T19:56:09.2660628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FullyShardedDataParallel.optim_state_dict_to_load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/fsdp/fully_sharded_data_parallel.py line=1903. 2025-08-26T19:56:09.2660909Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2661021Z 2025-08-26T19:56:09.2661390Z Convert an optimizer state-dict so that it can be loaded into the optimizer associated with the FSDP model. 2025-08-26T19:56:09.2661474Z 2025-08-26T19:56:09.2661643Z Given a ``optim_state_dict`` that is transformed through 2025-08-26T19:56:09.2661869Z :meth:`optim_state_dict`, it gets converted to the flattened optimizer 2025-08-26T19:56:09.2662077Z state_dict that can be loaded to ``optim`` which is the optimizer for 2025-08-26T19:56:09.2662277Z ``model``. ``model`` must be sharded by FullyShardedDataParallel. 2025-08-26T19:56:09.2662357Z 2025-08-26T19:56:09.2662488Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2662738Z >>> from torch.distributed.fsdp import FullyShardedDataParallel as FSDP 2025-08-26T19:56:09.2662892Z >>> from torch.distributed.fsdp import StateDictType 2025-08-26T19:56:09.2663080Z >>> from torch.distributed.fsdp import FullStateDictConfig 2025-08-26T19:56:09.2663289Z >>> from torch.distributed.fsdp import FullOptimStateDictConfig 2025-08-26T19:56:09.2663411Z >>> # Save a checkpoint 2025-08-26T19:56:09.2663517Z >>> model, optim = ... 2025-08-26T19:56:09.2663622Z >>> FSDP.set_state_dict_type( 2025-08-26T19:56:09.2663711Z >>> model, 2025-08-26T19:56:09.2663832Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:56:09.2663960Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2664120Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2664203Z >>> ) 2025-08-26T19:56:09.2664355Z >>> state_dict = model.state_dict() 2025-08-26T19:56:09.2664474Z >>> original_osd = optim.state_dict() 2025-08-26T19:56:09.2664609Z >>> optim_state_dict = FSDP.optim_state_dict( 2025-08-26T19:56:09.2664709Z >>> model, 2025-08-26T19:56:09.2664796Z >>> optim, 2025-08-26T19:56:09.2664925Z >>> optim_state_dict=original_osd 2025-08-26T19:56:09.2665052Z >>> ) 2025-08-26T19:56:09.2665207Z >>> save_a_checkpoint(state_dict, optim_state_dict) 2025-08-26T19:56:09.2665322Z >>> # Load a checkpoint 2025-08-26T19:56:09.2665422Z >>> model, optim = ... 2025-08-26T19:56:09.2665593Z >>> state_dict, optim_state_dict = load_a_checkpoint() 2025-08-26T19:56:09.2665704Z >>> FSDP.set_state_dict_type( 2025-08-26T19:56:09.2665793Z >>> model, 2025-08-26T19:56:09.2665928Z >>> StateDictType.FULL_STATE_DICT, 2025-08-26T19:56:09.2666061Z >>> FullStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2666211Z >>> FullOptimStateDictConfig(rank0_only=False), 2025-08-26T19:56:09.2666311Z >>> ) 2025-08-26T19:56:09.2666433Z >>> model.load_state_dict(state_dict) 2025-08-26T19:56:09.2666599Z >>> optim_state_dict = FSDP.optim_state_dict_to_load( 2025-08-26T19:56:09.2666718Z >>> model, optim, optim_state_dict 2025-08-26T19:56:09.2666805Z >>> ) 2025-08-26T19:56:09.2666952Z >>> optim.load_state_dict(optim_state_dict) 2025-08-26T19:56:09.2667038Z 2025-08-26T19:56:09.2667140Z Args: 2025-08-26T19:56:09.2667338Z model (torch.nn.Module): Root module (which may or may not be a 2025-08-26T19:56:09.2667545Z :class:`FullyShardedDataParallel` instance) whose parameters 2025-08-26T19:56:09.2667696Z were passed into the optimizer ``optim``. 2025-08-26T19:56:09.2667880Z optim (torch.optim.Optimizer): Optimizer for ``model`` 's 2025-08-26T19:56:09.2667990Z parameters. 2025-08-26T19:56:09.2668210Z optim_state_dict (Dict[str, Any]): The optimizer states to be loaded. 2025-08-26T19:56:09.2668413Z is_named_optimizer (bool): Is this optimizer a NamedOptimizer or 2025-08-26T19:56:09.2668620Z KeyedOptimizer. Only set to True if ``optim`` is TorchRec's 2025-08-26T19:56:09.2668802Z KeyedOptimizer or torch.distributed's NamedOptimizer. 2025-08-26T19:56:09.2669040Z load_directly (bool): If this is set to True, this API will also 2025-08-26T19:56:09.2669245Z call optim.load_state_dict(result) before returning the result. 2025-08-26T19:56:09.2669472Z Otherwise, users are responsible to call ``optim.load_state_dict()`` 2025-08-26T19:56:09.2669589Z (Default: ``False``) 2025-08-26T19:56:09.2669830Z group (dist.ProcessGroup): Model's process group across which parameters 2025-08-26T19:56:09.2670034Z are sharded or ``None`` if using the default process group. ( 2025-08-26T19:56:09.2670135Z Default: ``None``) 2025-08-26T19:56:09.2670222Z 2025-08-26T19:56:09.2670492Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2670575Z 2025-08-26T19:56:09.2670687Z warnings.warn(msg) 2025-08-26T19:56:09.2670767Z 2025-08-26T19:56:09.2670960Z --- Parse Warning: 79 / 146 --- 2025-08-26T19:56:09.2672003Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.__init__ in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=129. 2025-08-26T19:56:09.2672299Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2672398Z 2025-08-26T19:56:09.2672625Z RemoteModule instance can only be created after RPC initialization. 2025-08-26T19:56:09.2672705Z 2025-08-26T19:56:09.2672917Z It creates a user-specified module on a specified remote node. 2025-08-26T19:56:09.2673176Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T19:56:09.2673295Z executed on the remote node. 2025-08-26T19:56:09.2673533Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T19:56:09.2673694Z gradients back to the corresponding remote module. 2025-08-26T19:56:09.2674091Z It can be shared across processors using `RPC framework `__, 2025-08-26T19:56:09.2674295Z without incurring any overheads of copying the actual module, 2025-08-26T19:56:09.2674510Z which is equivalent to an :class:`~torch.distributed.rpc.RRef` 2025-08-26T19:56:09.2674619Z pointing to the remote module. 2025-08-26T19:56:09.2674701Z 2025-08-26T19:56:09.2674915Z The arguments of ``forward_async`` and ``forward`` are the same as 2025-08-26T19:56:09.2675118Z the ``forward`` method of the module returned by the ``module_cls``. 2025-08-26T19:56:09.2675216Z 2025-08-26T19:56:09.2675535Z Apart from ``forward_async`` and ``forward``, no other methods are supported from nn.Module for now. 2025-08-26T19:56:09.2675618Z 2025-08-26T19:56:09.2675884Z Particularly, to create a hybrid model, typically the local modules should be 2025-08-26T19:56:09.2676270Z created outside of remote modules, rather than as submodules of any remote module (by calling ``add_module``). 2025-08-26T19:56:09.2676380Z Hybrid Example: 2025-08-26T19:56:09.2676501Z >>> class HybridModel(nn.Module): 2025-08-26T19:56:09.2676617Z >>> def __init__(self) -> None: 2025-08-26T19:56:09.2676745Z >>> nn.Module.__init__(self) 2025-08-26T19:56:09.2676892Z >>> self.remote_embedding = RemoteModule(...) 2025-08-26T19:56:09.2677037Z >>> self.local_linear = nn.Linear(...) 2025-08-26T19:56:09.2677121Z 2025-08-26T19:56:09.2677322Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T19:56:09.2677590Z that has ``forward`` method signature, ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T19:56:09.2677801Z the generated ``RemoteModule`` will have 2 methods in signature of 2025-08-26T19:56:09.2677947Z ``def forward(input: Tensor) -> Tensor:`` and 2025-08-26T19:56:09.2678115Z ``def forward_async(input: Tensor) -> Future[Tensor]:``. 2025-08-26T19:56:09.2678195Z 2025-08-26T19:56:09.2678325Z .. note:: 2025-08-26T19:56:09.2678473Z If the remote module is placed on a cuda device, 2025-08-26T19:56:09.2678724Z any input CPU tensors will be automatically moved to the same cuda device, 2025-08-26T19:56:09.2679133Z and GPU tensors are returned over the wire according to the device map of the remote worker on TensorPipe RPC backend. 2025-08-26T19:56:09.2679217Z 2025-08-26T19:56:09.2679313Z Args: 2025-08-26T19:56:09.2679614Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T19:56:09.2679924Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T19:56:09.2680013Z formats: 2025-08-26T19:56:09.2680094Z 2025-08-26T19:56:09.2680251Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T19:56:09.2680406Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T19:56:09.2680510Z 2025-08-26T19:56:09.2680767Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T19:56:09.2680919Z module_cls (nn.Module): For example, 2025-08-26T19:56:09.2681044Z >>> class MyModule(nn.Module): 2025-08-26T19:56:09.2681149Z >>> def forward(input): 2025-08-26T19:56:09.2681267Z >>> return input + 1 2025-08-26T19:56:09.2681351Z >>> 2025-08-26T19:56:09.2681456Z >>> module_cls = MyModule 2025-08-26T19:56:09.2681671Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T19:56:09.2681893Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T19:56:09.2682192Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T19:56:09.2682430Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T19:56:09.2682678Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T19:56:09.2682933Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T19:56:09.2683016Z 2025-08-26T19:56:09.2683114Z Returns: 2025-08-26T19:56:09.2683360Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T19:56:09.2683593Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T19:56:09.2683883Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T19:56:09.2684032Z on the user-provided module on the remote side. 2025-08-26T19:56:09.2684127Z 2025-08-26T19:56:09.2684218Z Example:: 2025-08-26T19:56:09.2684372Z Run the following code in two different processes: 2025-08-26T19:56:09.2684465Z 2025-08-26T19:56:09.2684583Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2684691Z >>> # On worker 0: 2025-08-26T19:56:09.2684787Z >>> import torch 2025-08-26T19:56:09.2684917Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2685043Z >>> from torch import nn, Tensor 2025-08-26T19:56:09.2685266Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T19:56:09.2685363Z >>> 2025-08-26T19:56:09.2685505Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:56:09.2685628Z >>> remote_linear_module = RemoteModule( 2025-08-26T19:56:09.2685769Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T19:56:09.2685856Z >>> ) 2025-08-26T19:56:09.2685980Z >>> input = torch.randn(128, 20) 2025-08-26T19:56:09.2686136Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T19:56:09.2686237Z >>> ret = ret_fut.wait() 2025-08-26T19:56:09.2686347Z >>> rpc.shutdown() 2025-08-26T19:56:09.2686428Z 2025-08-26T19:56:09.2686521Z >>> # On worker 1: 2025-08-26T19:56:09.2686658Z >>> import torch 2025-08-26T19:56:09.2686787Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2686883Z >>> 2025-08-26T19:56:09.2687024Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:56:09.2687119Z >>> rpc.shutdown() 2025-08-26T19:56:09.2687213Z 2025-08-26T19:56:09.2687473Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2687568Z 2025-08-26T19:56:09.2687665Z warnings.warn(msg) 2025-08-26T19:56:09.2687745Z 2025-08-26T19:56:09.2687956Z --- Parse Warning: 80 / 146 --- 2025-08-26T19:56:09.2689121Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_RemoteModule.init_from_module_rref in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=506. 2025-08-26T19:56:09.2689405Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2689488Z 2025-08-26T19:56:09.2689853Z Besides the constructor, a RemoteModule instance can also be initialized given a module RRef. 2025-08-26T19:56:09.2689947Z 2025-08-26T19:56:09.2690278Z This alternate initialization method can be particularly useful if we want to create multiple 2025-08-26T19:56:09.2690613Z RemoteModule instances that share the same underlying module and reduce memory consumption. 2025-08-26T19:56:09.2690693Z 2025-08-26T19:56:09.2690974Z Moreover, this also provides a workaround for passing script RemoteModule over RPC, 2025-08-26T19:56:09.2691212Z which is not supported. The recommended way is as follows: 2025-08-26T19:56:09.2691296Z 2025-08-26T19:56:09.2691429Z 1. the sender creates a RemoteModule; 2025-08-26T19:56:09.2691576Z 2. the sender sends its ``module_rref`` over RPC; 2025-08-26T19:56:09.2691947Z 3. the receiver calls this method to initialize another RemoteModule using the same ``module_rref``. 2025-08-26T19:56:09.2692046Z 2025-08-26T19:56:09.2692142Z Example:: 2025-08-26T19:56:09.2692314Z Run the following code in two different processes: 2025-08-26T19:56:09.2692394Z 2025-08-26T19:56:09.2692516Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2692624Z >>> # On worker 0: 2025-08-26T19:56:09.2692717Z >>> import torch 2025-08-26T19:56:09.2692859Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2692969Z >>> from torch import nn, Tensor 2025-08-26T19:56:09.2693197Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T19:56:09.2693294Z >>> 2025-08-26T19:56:09.2693434Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:56:09.2693558Z >>> remote_module = RemoteModule( 2025-08-26T19:56:09.2693686Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T19:56:09.2693770Z >>> ) 2025-08-26T19:56:09.2693869Z >>> 2025-08-26T19:56:09.2693984Z >>> remote_module1 = rpc.rpc_sync( 2025-08-26T19:56:09.2694085Z >>> "worker1/cpu", 2025-08-26T19:56:09.2694225Z >>> RemoteModule.init_from_module_rref, 2025-08-26T19:56:09.2694382Z >>> ("worker1/cpu", remote_module1.get_module_rref()), 2025-08-26T19:56:09.2694478Z >>> ) 2025-08-26T19:56:09.2694574Z >>> rpc.shutdown() 2025-08-26T19:56:09.2694655Z 2025-08-26T19:56:09.2694761Z >>> # On worker 1: 2025-08-26T19:56:09.2694853Z >>> import torch 2025-08-26T19:56:09.2694996Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2695080Z >>> 2025-08-26T19:56:09.2695218Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:56:09.2695328Z >>> rpc.shutdown() 2025-08-26T19:56:09.2695410Z 2025-08-26T19:56:09.2695505Z Args: 2025-08-26T19:56:09.2695806Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T19:56:09.2696135Z The device can be a local device or a remote device specified by one of the following remote 2025-08-26T19:56:09.2696236Z formats: 2025-08-26T19:56:09.2696318Z 2025-08-26T19:56:09.2696474Z 1. "rank:/" (ex: "rank:0/cuda:0"). 2025-08-26T19:56:09.2696629Z 2. "/" (ex: "trainer0/cuda:0"). 2025-08-26T19:56:09.2696707Z 2025-08-26T19:56:09.2696974Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T19:56:09.2697230Z module_rref (RRef[nn.Module]): The module reference shared by both the caller and 2025-08-26T19:56:09.2697353Z the created remote module. 2025-08-26T19:56:09.2697636Z _module_interface_cls (type, optional): The TorchScript interface type for the module 2025-08-26T19:56:09.2697870Z to be created. The type object should be decorated by @torch.jit.interface. 2025-08-26T19:56:09.2698110Z If not provided, the generated RemoteModule is not torchscript-able. 2025-08-26T19:56:09.2698377Z Warning, this is an experimental API and susceptible to frequent changes. 2025-08-26T19:56:09.2698467Z 2025-08-26T19:56:09.2698554Z Returns: 2025-08-26T19:56:09.2698800Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T19:56:09.2699048Z user-provided ``module_rref``, it has a blocking ``forward`` method and an 2025-08-26T19:56:09.2699319Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T19:56:09.2699501Z on the user-provided module on the remote side. 2025-08-26T19:56:09.2699584Z 2025-08-26T19:56:09.2699841Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2699938Z 2025-08-26T19:56:09.2700035Z warnings.warn(msg) 2025-08-26T19:56:09.2700129Z 2025-08-26T19:56:09.2700359Z --- Parse Warning: 81 / 146 --- 2025-08-26T19:56:09.2701363Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RemoteModule in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/nn/api/remote_module.py line=598. 2025-08-26T19:56:09.2701645Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2701728Z 2025-08-26T19:56:09.2701973Z A RemoteModule instance can only be created after RPC initialization. 2025-08-26T19:56:09.2702057Z 2025-08-26T19:56:09.2702258Z It creates a user-specified module on a specified remote node. 2025-08-26T19:56:09.2702507Z It behaves like a regular ``nn.Module`` except that the ``forward`` method is 2025-08-26T19:56:09.2702610Z executed on the remote node. 2025-08-26T19:56:09.2702862Z It takes care of autograd recording to ensure the backward pass propagates 2025-08-26T19:56:09.2703020Z gradients back to the corresponding remote module. 2025-08-26T19:56:09.2703104Z 2025-08-26T19:56:09.2703337Z It generates two methods ``forward_async`` and ``forward`` based on the 2025-08-26T19:56:09.2703549Z signature of the ``forward`` method of ``module_cls``. ``forward_async`` 2025-08-26T19:56:09.2703818Z runs asynchronously and returns a Future. The arguments of ``forward_async`` 2025-08-26T19:56:09.2704016Z and ``forward`` are the same as the ``forward`` method of the module 2025-08-26T19:56:09.2704125Z returned by the ``module_cls``. 2025-08-26T19:56:09.2704218Z 2025-08-26T19:56:09.2704419Z For example, if ``module_cls`` returns an instance of ``nn.Linear``, 2025-08-26T19:56:09.2704682Z that has ``forward`` method signature: ``def forward(input: Tensor) -> Tensor:``, 2025-08-26T19:56:09.2704907Z the generated ``RemoteModule`` will have 2 methods with the signatures: 2025-08-26T19:56:09.2704987Z 2025-08-26T19:56:09.2705127Z | ``def forward(input: Tensor) -> Tensor:`` 2025-08-26T19:56:09.2705356Z | ``def forward_async(input: Tensor) -> Future[Tensor]:`` 2025-08-26T19:56:09.2705450Z 2025-08-26T19:56:09.2705534Z Args: 2025-08-26T19:56:09.2705833Z remote_device (str): Device on the destination worker where we'd like to place this module. 2025-08-26T19:56:09.2706192Z The format should be "/", where the device field can be parsed as torch.device type. 2025-08-26T19:56:09.2706331Z E.g., "trainer0/cpu", "trainer0", "ps0/cuda:0". 2025-08-26T19:56:09.2706593Z In addition, the device field can be optional and the default value is "cpu". 2025-08-26T19:56:09.2706841Z module_cls (nn.Module): Class for the module to be created remotely. For example, 2025-08-26T19:56:09.2706921Z 2025-08-26T19:56:09.2707047Z >>> class MyModule(nn.Module): 2025-08-26T19:56:09.2707146Z >>> def forward(input): 2025-08-26T19:56:09.2707261Z >>> return input + 1 2025-08-26T19:56:09.2707342Z >>> 2025-08-26T19:56:09.2707470Z >>> module_cls = MyModule 2025-08-26T19:56:09.2707561Z 2025-08-26T19:56:09.2707764Z args (Sequence, optional): args to be passed to ``module_cls``. 2025-08-26T19:56:09.2707970Z kwargs (Dict, optional): kwargs to be passed to ``module_cls``. 2025-08-26T19:56:09.2708048Z 2025-08-26T19:56:09.2708132Z Returns: 2025-08-26T19:56:09.2708389Z A remote module instance which wraps the :class:`~nn.Module` created by the 2025-08-26T19:56:09.2708647Z user-provided ``module_cls``, it has a blocking ``forward`` method and an 2025-08-26T19:56:09.2708934Z asynchronous ``forward_async`` method that returns a future of the ``forward`` call 2025-08-26T19:56:09.2709076Z on the user-provided module on the remote side. 2025-08-26T19:56:09.2709154Z 2025-08-26T19:56:09.2709254Z Example:: 2025-08-26T19:56:09.2709430Z Run the following code in two different processes: 2025-08-26T19:56:09.2709511Z 2025-08-26T19:56:09.2709637Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2709730Z >>> # On worker 0: 2025-08-26T19:56:09.2709831Z >>> import torch 2025-08-26T19:56:09.2709955Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2710062Z >>> from torch import nn, Tensor 2025-08-26T19:56:09.2710293Z >>> from torch.distributed.nn.api.remote_module import RemoteModule 2025-08-26T19:56:09.2710373Z >>> 2025-08-26T19:56:09.2710524Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:56:09.2710646Z >>> remote_linear_module = RemoteModule( 2025-08-26T19:56:09.2710775Z >>> "worker1/cpu", nn.Linear, args=(20, 30), 2025-08-26T19:56:09.2710867Z >>> ) 2025-08-26T19:56:09.2710977Z >>> input = torch.randn(128, 20) 2025-08-26T19:56:09.2711143Z >>> ret_fut = remote_linear_module.forward_async(input) 2025-08-26T19:56:09.2711246Z >>> ret = ret_fut.wait() 2025-08-26T19:56:09.2711346Z >>> rpc.shutdown() 2025-08-26T19:56:09.2711440Z 2025-08-26T19:56:09.2711529Z >>> # On worker 1: 2025-08-26T19:56:09.2711631Z >>> import torch 2025-08-26T19:56:09.2711756Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2711840Z >>> 2025-08-26T19:56:09.2711991Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:56:09.2712088Z >>> rpc.shutdown() 2025-08-26T19:56:09.2712168Z 2025-08-26T19:56:09.2712372Z Furthermore, a more practical example that is combined with 2025-08-26T19:56:09.2712862Z `DistributedDataParallel `__ (DDP) 2025-08-26T19:56:09.2713209Z can be found in this `tutorial `__. 2025-08-26T19:56:09.2713287Z 2025-08-26T19:56:09.2713551Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2713659Z 2025-08-26T19:56:09.2713758Z warnings.warn(msg) 2025-08-26T19:56:09.2713847Z 2025-08-26T19:56:09.2714042Z --- Parse Warning: 82 / 146 --- 2025-08-26T19:56:09.2715064Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/optimizer.py line=129. 2025-08-26T19:56:09.2715340Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2715420Z 2025-08-26T19:56:09.2715680Z DistributedOptimizer takes remote references to parameters scattered 2025-08-26T19:56:09.2715924Z across workers and applies the given optimizer locally for each parameter. 2025-08-26T19:56:09.2716018Z 2025-08-26T19:56:09.2716255Z This class uses :meth:`~torch.distributed.autograd.get_gradients` in order 2025-08-26T19:56:09.2716414Z to retrieve the gradients for specific parameters. 2025-08-26T19:56:09.2716537Z 2025-08-26T19:56:09.2716634Z Concurrent calls to 2025-08-26T19:56:09.2716842Z :meth:`~torch.distributed.optim.DistributedOptimizer.step`, 2025-08-26T19:56:09.2716994Z either from the same or different clients, will 2025-08-26T19:56:09.2717224Z be serialized on each worker -- as each worker's optimizer can only work 2025-08-26T19:56:09.2717444Z on one set of gradients at a time. However, there is no guarantee that 2025-08-26T19:56:09.2717690Z the full forward-backward-optimizer sequence will execute for one client 2025-08-26T19:56:09.2717948Z at a time. This means that the gradients being applied may not correspond 2025-08-26T19:56:09.2718174Z to the latest forward pass executed on a given worker. Also, there is no 2025-08-26T19:56:09.2718288Z guaranteed ordering across workers. 2025-08-26T19:56:09.2718377Z 2025-08-26T19:56:09.2718665Z `DistributedOptimizer` creates the local optimizer with TorchScript enabled 2025-08-26T19:56:09.2718914Z by default, so that optimizer updates are not blocked by the Python Global 2025-08-26T19:56:09.2719161Z Interpreter Lock (GIL) in the case of multithreaded training (e.g. Distributed 2025-08-26T19:56:09.2719401Z Model Parallel). This feature is currently enabled for most optimizers. You 2025-08-26T19:56:09.2719665Z can also follow `the recipe`__ in PyTorch tutorials to enable TorchScript support 2025-08-26T19:56:09.2719773Z for your own custom optimizers. 2025-08-26T19:56:09.2719866Z 2025-08-26T19:56:09.2719948Z Args: 2025-08-26T19:56:09.2720149Z optimizer_class (optim.Optimizer): the class of optimizer to 2025-08-26T19:56:09.2720264Z instantiate on each worker. 2025-08-26T19:56:09.2720476Z params_rref (list[RRef]): list of RRefs to local or remote parameters 2025-08-26T19:56:09.2720581Z to optimize. 2025-08-26T19:56:09.2720795Z args: arguments to pass to the optimizer constructor on each worker. 2025-08-26T19:56:09.2721023Z kwargs: arguments to pass to the optimizer constructor on each worker. 2025-08-26T19:56:09.2721113Z 2025-08-26T19:56:09.2721202Z Example:: 2025-08-26T19:56:09.2721323Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2721495Z >>> import torch.distributed.autograd as dist_autograd 2025-08-26T19:56:09.2721622Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2721739Z >>> from torch import optim 2025-08-26T19:56:09.2721926Z >>> from torch.distributed.optim import DistributedOptimizer 2025-08-26T19:56:09.2722006Z >>> 2025-08-26T19:56:09.2722151Z >>> with dist_autograd.context() as context_id: 2025-08-26T19:56:09.2722250Z >>> # Forward pass. 2025-08-26T19:56:09.2722458Z >>> rref1 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 3)) 2025-08-26T19:56:09.2722649Z >>> rref2 = rpc.remote("worker1", torch.add, args=(torch.ones(2), 1)) 2025-08-26T19:56:09.2722810Z >>> loss = rref1.to_here() + rref2.to_here() 2025-08-26T19:56:09.2722902Z >>> 2025-08-26T19:56:09.2722998Z >>> # Backward pass. 2025-08-26T19:56:09.2723161Z >>> dist_autograd.backward(context_id, [loss.sum()]) 2025-08-26T19:56:09.2723241Z >>> 2025-08-26T19:56:09.2723336Z >>> # Optimizer. 2025-08-26T19:56:09.2723472Z >>> dist_optim = DistributedOptimizer( 2025-08-26T19:56:09.2723563Z >>> optim.SGD, 2025-08-26T19:56:09.2723671Z >>> [rref1, rref2], 2025-08-26T19:56:09.2723759Z >>> lr=0.05, 2025-08-26T19:56:09.2723845Z >>> ) 2025-08-26T19:56:09.2723966Z >>> dist_optim.step(context_id) 2025-08-26T19:56:09.2724043Z 2025-08-26T19:56:09.2724208Z __ https://github.com/pytorch/tutorials/pull/1465 2025-08-26T19:56:09.2724286Z 2025-08-26T19:56:09.2724543Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2724635Z 2025-08-26T19:56:09.2724729Z warnings.warn(msg) 2025-08-26T19:56:09.2724848Z 2025-08-26T19:56:09.2725049Z --- Parse Warning: 83 / 146 --- 2025-08-26T19:56:09.2726139Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PostLocalSGDOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/post_localSGD_optimizer.py line=9. 2025-08-26T19:56:09.2726415Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2726496Z 2025-08-26T19:56:09.2726934Z Wraps an arbitrary :class:`torch.optim.Optimizer` and runs `post-local SGD `_, 2025-08-26T19:56:09.2727092Z This optimizer runs local optimizer at every step. 2025-08-26T19:56:09.2727433Z After the warm-up stage, it averages parameters periodically after the local optimizer is applied. 2025-08-26T19:56:09.2727528Z 2025-08-26T19:56:09.2727639Z Args: 2025-08-26T19:56:09.2727764Z optim: The local optimizer. 2025-08-26T19:56:09.2727989Z averager: A model averager instance to run post-localSGD algorithm. 2025-08-26T19:56:09.2728071Z 2025-08-26T19:56:09.2728174Z Example:: 2025-08-26T19:56:09.2728253Z 2025-08-26T19:56:09.2728389Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.2728489Z >>> import torch 2025-08-26T19:56:09.2728610Z >>> import torch.distributed as dist 2025-08-26T19:56:09.2728994Z >>> import torch.distributed.algorithms.model_averaging.averagers as averagers 2025-08-26T19:56:09.2729099Z >>> import torch.nn as nn 2025-08-26T19:56:09.2729292Z >>> from torch.distributed.optim import PostLocalSGDOptimizer 2025-08-26T19:56:09.2729589Z >>> from torch.distributed.algorithms.ddp_comm_hooks.post_localSGD_hook import ( 2025-08-26T19:56:09.2729697Z >>> PostLocalSGDState, 2025-08-26T19:56:09.2729814Z >>> post_localSGD_hook, 2025-08-26T19:56:09.2729896Z >>> ) 2025-08-26T19:56:09.2729982Z >>> 2025-08-26T19:56:09.2730150Z >>> model = nn.parallel.DistributedDataParallel( 2025-08-26T19:56:09.2730294Z >>> module, device_ids=[rank], output_device=rank 2025-08-26T19:56:09.2730389Z >>> ) 2025-08-26T19:56:09.2730470Z >>> 2025-08-26T19:56:09.2730621Z >>> # Register a post-localSGD communication hook. 2025-08-26T19:56:09.2730936Z >>> state = PostLocalSGDState(process_group=None, subgroup=None, start_localSGD_iter=100) 2025-08-26T19:56:09.2731103Z >>> model.register_comm_hook(state, post_localSGD_hook) 2025-08-26T19:56:09.2731199Z >>> 2025-08-26T19:56:09.2731402Z >>> # Create a post-localSGD optimizer that wraps a local optimizer. 2025-08-26T19:56:09.2731656Z >>> # Note that ``warmup_steps`` used in ``PostLocalSGDOptimizer`` must be the same as 2025-08-26T19:56:09.2731835Z >>> # ``start_localSGD_iter`` used in ``PostLocalSGDState``. 2025-08-26T19:56:09.2732082Z >>> local_optim = torch.optim.SGD(params=model.parameters(), lr=0.01) 2025-08-26T19:56:09.2732218Z >>> opt = PostLocalSGDOptimizer( 2025-08-26T19:56:09.2732318Z >>> optim=local_optim, 2025-08-26T19:56:09.2732568Z >>> averager=averagers.PeriodicModelAverager(period=4, warmup_steps=100) 2025-08-26T19:56:09.2732659Z >>> ) 2025-08-26T19:56:09.2732737Z >>> 2025-08-26T19:56:09.2732975Z >>> # In the first 100 steps, DDP runs global gradient averaging at every step. 2025-08-26T19:56:09.2733285Z >>> # After 100 steps, DDP runs gradient averaging within each subgroup (intra-node by default), 2025-08-26T19:56:09.2733671Z >>> # and post-localSGD optimizer runs global model averaging every 4 steps after applying the local optimizer. 2025-08-26T19:56:09.2733789Z >>> for step in range(0, 200): 2025-08-26T19:56:09.2733892Z >>> opt.zero_grad() 2025-08-26T19:56:09.2734022Z >>> loss = loss_fn(output, labels) 2025-08-26T19:56:09.2734125Z >>> loss.backward() 2025-08-26T19:56:09.2734241Z >>> opt.step() 2025-08-26T19:56:09.2734332Z 2025-08-26T19:56:09.2734594Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2734688Z 2025-08-26T19:56:09.2734784Z warnings.warn(msg) 2025-08-26T19:56:09.2734865Z 2025-08-26T19:56:09.2735075Z --- Parse Warning: 84 / 146 --- 2025-08-26T19:56:09.2736224Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZeroRedundancyOptimizer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/optim/zero_redundancy_optimizer.py line=284. 2025-08-26T19:56:09.2736503Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2736584Z 2025-08-26T19:56:09.2737023Z Wrap an arbitrary :class:`optim.Optimizer ` and shards its states across ranks in the group. 2025-08-26T19:56:09.2737121Z 2025-08-26T19:56:09.2737527Z The sharing is done as described by `ZeRO `_. 2025-08-26T19:56:09.2737621Z 2025-08-26T19:56:09.2737774Z The local optimizer instance in each rank is only 2025-08-26T19:56:09.2738022Z responsible for updating approximately ``1 / world_size`` parameters and 2025-08-26T19:56:09.2738239Z hence only needs to keep ``1 / world_size`` optimizer states. After 2025-08-26T19:56:09.2738485Z parameters are updated locally, each rank will broadcast its parameters to 2025-08-26T19:56:09.2738687Z all other peers to keep all model replicas in the same state. 2025-08-26T19:56:09.2738881Z ``ZeroRedundancyOptimizer`` can be used in conjunction with 2025-08-26T19:56:09.2739142Z :class:`torch.nn.parallel.DistributedDataParallel` to reduce per-rank peak 2025-08-26T19:56:09.2739258Z memory consumption. 2025-08-26T19:56:09.2739343Z 2025-08-26T19:56:09.2739623Z ``ZeroRedundancyOptimizer`` uses a sorted-greedy algorithm to pack a number 2025-08-26T19:56:09.2739856Z of parameters at each rank. Each parameter belongs to a single rank and is 2025-08-26T19:56:09.2740095Z not divided among ranks. The partition is arbitrary and might not match the 2025-08-26T19:56:09.2740243Z the parameter registration or usage order. 2025-08-26T19:56:09.2740322Z 2025-08-26T19:56:09.2740421Z Arguments: 2025-08-26T19:56:09.2740612Z params (``Iterable``): an ``Iterable`` of :class:`torch.Tensor` s 2025-08-26T19:56:09.2740802Z or :class:`dict` s giving all parameters, which will be sharded 2025-08-26T19:56:09.2740908Z across ranks. 2025-08-26T19:56:09.2740985Z 2025-08-26T19:56:09.2741084Z Keyword Args: 2025-08-26T19:56:09.2741310Z optimizer_class (:class:`torch.nn.Optimizer`): the class of the local 2025-08-26T19:56:09.2741399Z optimizer. 2025-08-26T19:56:09.2741622Z process_group (``ProcessGroup``, optional): ``torch.distributed`` 2025-08-26T19:56:09.2741888Z ``ProcessGroup`` (default: ``dist.group.WORLD`` initialized by 2025-08-26T19:56:09.2742050Z :meth:`torch.distributed.init_process_group`). 2025-08-26T19:56:09.2742281Z parameters_as_bucket_view (bool, optional): if ``True``, parameters are 2025-08-26T19:56:09.2742498Z packed into buckets to speed up communication, and ``param.data`` 2025-08-26T19:56:09.2742711Z fields point to bucket views at different offsets; if ``False``, 2025-08-26T19:56:09.2742918Z each individual parameter is communicated separately, and each 2025-08-26T19:56:09.2743081Z ``params.data`` stays intact (default: ``False``). 2025-08-26T19:56:09.2743279Z overlap_with_ddp (bool, optional): if ``True``, :meth:`step` is 2025-08-26T19:56:09.2743478Z overlapped with :class:`DistributedDataParallel` 's gradient 2025-08-26T19:56:09.2743711Z synchronization; this requires (1) either a functional optimizer 2025-08-26T19:56:09.2743931Z for the ``optimizer_class`` argument or one with a functional 2025-08-26T19:56:09.2744122Z equivalent and (2) registering a DDP communication hook 2025-08-26T19:56:09.2744326Z constructed from one of the functions in ``ddp_zero_hook.py``; 2025-08-26T19:56:09.2744494Z parameters are packed into buckets matching those in 2025-08-26T19:56:09.2744666Z :class:`DistributedDataParallel`, meaning that the 2025-08-26T19:56:09.2744818Z ``parameters_as_bucket_view`` argument is ignored. 2025-08-26T19:56:09.2745062Z If ``False``, :meth:`step` runs disjointly after the backward pass 2025-08-26T19:56:09.2745162Z (per normal). 2025-08-26T19:56:09.2745260Z (default: ``False``) 2025-08-26T19:56:09.2745489Z **defaults: any trailing arguments, which are forwarded to the local 2025-08-26T19:56:09.2745579Z optimizer. 2025-08-26T19:56:09.2745710Z 2025-08-26T19:56:09.2745804Z Example:: 2025-08-26T19:56:09.2745883Z 2025-08-26T19:56:09.2745995Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2746094Z >>> import torch.nn as nn 2025-08-26T19:56:09.2746311Z >>> from torch.distributed.optim import ZeroRedundancyOptimizer 2025-08-26T19:56:09.2746514Z >>> from torch.nn.parallel import DistributedDataParallel as DDP 2025-08-26T19:56:09.2746741Z >>> model = nn.Sequential(*[nn.Linear(2000, 2000).to(rank) for _ in range(20)]) 2025-08-26T19:56:09.2746874Z >>> ddp = DDP(model, device_ids=[rank]) 2025-08-26T19:56:09.2746994Z >>> opt = ZeroRedundancyOptimizer( 2025-08-26T19:56:09.2747110Z >>> ddp.parameters(), 2025-08-26T19:56:09.2747235Z >>> optimizer_class=torch.optim.Adam, 2025-08-26T19:56:09.2747320Z >>> lr=0.01 2025-08-26T19:56:09.2747416Z >>> ) 2025-08-26T19:56:09.2747521Z >>> ddp(inputs).sum().backward() 2025-08-26T19:56:09.2747625Z >>> opt.step() 2025-08-26T19:56:09.2747705Z 2025-08-26T19:56:09.2747792Z .. warning:: 2025-08-26T19:56:09.2748018Z Currently, ``ZeroRedundancyOptimizer`` requires that all of the 2025-08-26T19:56:09.2748165Z passed-in parameters are the same dense type. 2025-08-26T19:56:09.2748245Z 2025-08-26T19:56:09.2748347Z .. warning:: 2025-08-26T19:56:09.2748560Z If you pass ``overlap_with_ddp=True``, be wary of the following: Given 2025-08-26T19:56:09.2748777Z the way that overlapping :class:`DistributedDataParallel` with 2025-08-26T19:56:09.2749014Z :class:`ZeroRedundancyOptimizer` is currently implemented, the first 2025-08-26T19:56:09.2749235Z two or three training iterations do not perform parameter updates in 2025-08-26T19:56:09.2749439Z the optimizer step, depending on if ``static_graph=False`` or 2025-08-26T19:56:09.2749620Z ``static_graph=True``, respectively. This is because it needs 2025-08-26T19:56:09.2749819Z information about the gradient bucketing strategy used by 2025-08-26T19:56:09.2750070Z :class:`DistributedDataParallel`, which is not finalized until the 2025-08-26T19:56:09.2750285Z second forward pass if ``static_graph=False`` or until the third 2025-08-26T19:56:09.2750496Z forward pass if ``static_graph=True``. To adjust for this, one option 2025-08-26T19:56:09.2750603Z is to prepend dummy inputs. 2025-08-26T19:56:09.2750695Z 2025-08-26T19:56:09.2750950Z .. warning:: ZeroRedundancyOptimizer is experimental and subject to change. 2025-08-26T19:56:09.2751041Z 2025-08-26T19:56:09.2751297Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2751373Z 2025-08-26T19:56:09.2751484Z warnings.warn(msg) 2025-08-26T19:56:09.2751560Z 2025-08-26T19:56:09.2751766Z --- Parse Warning: 85 / 146 --- 2025-08-26T19:56:09.2752792Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_CustomReducer in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/pipelining/microbatch.py line=29. 2025-08-26T19:56:09.2753091Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2753183Z 2025-08-26T19:56:09.2753417Z Custom reducer class that can be used to specify a custom operation that 2025-08-26T19:56:09.2753606Z reduces losses of multiple microbatches into one value. 2025-08-26T19:56:09.2753685Z 2025-08-26T19:56:09.2753767Z Example: 2025-08-26T19:56:09.2753876Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2754012Z >>> sum_reducer = _CustomReducer( 2025-08-26T19:56:09.2754117Z >>> torch.tensor(0.0), 2025-08-26T19:56:09.2754224Z >>> lambda a, b: a + b 2025-08-26T19:56:09.2754303Z >>> ) 2025-08-26T19:56:09.2754393Z 2025-08-26T19:56:09.2754647Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2754754Z 2025-08-26T19:56:09.2754866Z warnings.warn(msg) 2025-08-26T19:56:09.2754943Z 2025-08-26T19:56:09.2755144Z --- Parse Warning: 86 / 146 --- 2025-08-26T19:56:09.2756095Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=async_execution in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/functions.py line=6. 2025-08-26T19:56:09.2756360Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2756456Z 2025-08-26T19:56:09.2756700Z A decorator for a function indicating that the return value of the function 2025-08-26T19:56:09.2756924Z is guaranteed to be a :class:`~torch.futures.Future` object and this 2025-08-26T19:56:09.2757170Z function can run asynchronously on the RPC callee. More specifically, the 2025-08-26T19:56:09.2757409Z callee extracts the :class:`~torch.futures.Future` returned by the wrapped 2025-08-26T19:56:09.2757662Z function and installs subsequent processing steps as a callback to that 2025-08-26T19:56:09.2757896Z :class:`~torch.futures.Future`. The installed callback will read the value 2025-08-26T19:56:09.2758110Z from the :class:`~torch.futures.Future` when completed and send the 2025-08-26T19:56:09.2758293Z value back as the RPC response. That also means the returned 2025-08-26T19:56:09.2758536Z :class:`~torch.futures.Future` only exists on the callee side and is never 2025-08-26T19:56:09.2758761Z sent through RPC. This decorator is useful when the wrapped function's 2025-08-26T19:56:09.2758959Z (``fn``) execution needs to pause and resume due to, e.g., containing 2025-08-26T19:56:09.2759196Z :meth:`~torch.distributed.rpc.rpc_async` or waiting for other signals. 2025-08-26T19:56:09.2759277Z 2025-08-26T19:56:09.2759500Z .. note:: To enable asynchronous execution, applications must pass the 2025-08-26T19:56:09.2759738Z function object returned by this decorator to RPC APIs. If RPC detected 2025-08-26T19:56:09.2760000Z attributes installed by this decorator, it knows that this function 2025-08-26T19:56:09.2760197Z returns a ``Future`` object and will handle that accordingly. 2025-08-26T19:56:09.2760414Z However, this does not mean this decorator has to be outmost one when 2025-08-26T19:56:09.2760655Z defining a function. For example, when combined with ``@staticmethod`` 2025-08-26T19:56:09.2760869Z or ``@classmethod``, ``@rpc.functions.async_execution`` needs to be the 2025-08-26T19:56:09.2761095Z inner decorator to allow the target function be recognized as a static 2025-08-26T19:56:09.2761341Z or class function. This target function can still execute asynchronously 2025-08-26T19:56:09.2761571Z because, when accessed, the static or class method preserves attributes 2025-08-26T19:56:09.2761744Z installed by ``@rpc.functions.async_execution``. 2025-08-26T19:56:09.2761827Z 2025-08-26T19:56:09.2761912Z 2025-08-26T19:56:09.2762041Z Example:: 2025-08-26T19:56:09.2762245Z The returned :class:`~torch.futures.Future` object can come from 2025-08-26T19:56:09.2762397Z :meth:`~torch.distributed.rpc.rpc_async`, 2025-08-26T19:56:09.2762625Z :meth:`~torch.futures.Future.then`, or :class:`~torch.futures.Future` 2025-08-26T19:56:09.2762806Z constructor. The example below shows directly using the 2025-08-26T19:56:09.2762953Z :class:`~torch.futures.Future` returned by 2025-08-26T19:56:09.2763080Z :meth:`~torch.futures.Future.then`. 2025-08-26T19:56:09.2763179Z 2025-08-26T19:56:09.2763331Z >>> from torch.distributed import rpc 2025-08-26T19:56:09.2763417Z >>> 2025-08-26T19:56:09.2763546Z >>> # omitting setup and shutdown RPC 2025-08-26T19:56:09.2763630Z >>> 2025-08-26T19:56:09.2763743Z >>> # On all workers 2025-08-26T19:56:09.2763864Z >>> @rpc.functions.async_execution 2025-08-26T19:56:09.2764010Z >>> def async_add_chained(to, x, y, z): 2025-08-26T19:56:09.2764225Z >>> # This function runs on "worker1" and returns immediately when 2025-08-26T19:56:09.2764418Z >>> # the callback is installed through the `then(cb)` API. In the 2025-08-26T19:56:09.2764619Z >>> # mean time, the `rpc_async` to "worker2" can run concurrently. 2025-08-26T19:56:09.2764782Z >>> # When the return value of that `rpc_async` arrives at 2025-08-26T19:56:09.2764973Z >>> # "worker1", "worker1" will run the lambda function accordingly 2025-08-26T19:56:09.2765180Z >>> # and set the value for the previously returned `Future`, which 2025-08-26T19:56:09.2765367Z >>> # will then trigger RPC to send the result back to "worker0". 2025-08-26T19:56:09.2765553Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:56:09.2765671Z >>> lambda fut: fut.wait() + z 2025-08-26T19:56:09.2765758Z >>> ) 2025-08-26T19:56:09.2765859Z >>> 2025-08-26T19:56:09.2765953Z >>> # On worker0 2025-08-26T19:56:09.2766063Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2766162Z >>> ret = rpc.rpc_sync( 2025-08-26T19:56:09.2766254Z >>> "worker1", 2025-08-26T19:56:09.2766369Z >>> async_add_chained, 2025-08-26T19:56:09.2766501Z >>> args=("worker2", torch.ones(2), 1, 1) 2025-08-26T19:56:09.2766585Z >>> ) 2025-08-26T19:56:09.2766718Z >>> print(ret) # prints tensor([3., 3.]) 2025-08-26T19:56:09.2766799Z 2025-08-26T19:56:09.2767042Z When combined with TorchScript decorators, this decorator must be the 2025-08-26T19:56:09.2767131Z outmost one. 2025-08-26T19:56:09.2767211Z 2025-08-26T19:56:09.2767325Z >>> from torch import Tensor 2025-08-26T19:56:09.2767442Z >>> from torch.futures import Future 2025-08-26T19:56:09.2767574Z >>> from torch.distributed import rpc 2025-08-26T19:56:09.2767658Z >>> 2025-08-26T19:56:09.2767803Z >>> # omitting setup and shutdown RPC 2025-08-26T19:56:09.2767898Z >>> 2025-08-26T19:56:09.2767994Z >>> # On all workers 2025-08-26T19:56:09.2768105Z >>> @torch.jit.script 2025-08-26T19:56:09.2768253Z >>> def script_add(x: Tensor, y: Tensor) -> Tensor: 2025-08-26T19:56:09.2768347Z >>> return x + y 2025-08-26T19:56:09.2768438Z >>> 2025-08-26T19:56:09.2768556Z >>> @rpc.functions.async_execution 2025-08-26T19:56:09.2768656Z >>> @torch.jit.script 2025-08-26T19:56:09.2768941Z >>> def async_add(to: str, x: Tensor, y: Tensor) -> Future[Tensor]: 2025-08-26T19:56:09.2769088Z >>> return rpc.rpc_async(to, script_add, (x, y)) 2025-08-26T19:56:09.2769180Z >>> 2025-08-26T19:56:09.2769270Z >>> # On worker0 2025-08-26T19:56:09.2769371Z >>> ret = rpc.rpc_sync( 2025-08-26T19:56:09.2769471Z >>> "worker1", 2025-08-26T19:56:09.2769561Z >>> async_add, 2025-08-26T19:56:09.2769699Z >>> args=("worker2", torch.ones(2), 1) 2025-08-26T19:56:09.2769814Z >>> ) 2025-08-26T19:56:09.2769935Z >>> print(ret) # prints tensor([2., 2.]) 2025-08-26T19:56:09.2770030Z 2025-08-26T19:56:09.2770251Z When combined with static or class method, this decorator must be the 2025-08-26T19:56:09.2770350Z inner one. 2025-08-26T19:56:09.2770430Z 2025-08-26T19:56:09.2770549Z >>> from torch.distributed import rpc 2025-08-26T19:56:09.2770644Z >>> 2025-08-26T19:56:09.2770760Z >>> # omitting setup and shutdown RPC 2025-08-26T19:56:09.2770867Z >>> 2025-08-26T19:56:09.2770974Z >>> # On all workers 2025-08-26T19:56:09.2771089Z >>> class AsyncExecutionClass: 2025-08-26T19:56:09.2771183Z >>> 2025-08-26T19:56:09.2771278Z >>> @staticmethod 2025-08-26T19:56:09.2771398Z >>> @rpc.functions.async_execution 2025-08-26T19:56:09.2771551Z >>> def static_async_add(to, x, y, z): 2025-08-26T19:56:09.2771728Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:56:09.2771854Z >>> lambda fut: fut.wait() + z 2025-08-26T19:56:09.2771938Z >>> ) 2025-08-26T19:56:09.2772020Z >>> 2025-08-26T19:56:09.2772127Z >>> @classmethod 2025-08-26T19:56:09.2772247Z >>> @rpc.functions.async_execution 2025-08-26T19:56:09.2772381Z >>> def class_async_add(cls, to, x, y, z): 2025-08-26T19:56:09.2772509Z >>> ret_fut = torch.futures.Future() 2025-08-26T19:56:09.2772660Z >>> rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:56:09.2772823Z >>> lambda fut: ret_fut.set_result(fut.wait() + z) 2025-08-26T19:56:09.2772911Z >>> ) 2025-08-26T19:56:09.2773021Z >>> return ret_fut 2025-08-26T19:56:09.2773104Z >>> 2025-08-26T19:56:09.2773224Z >>> @rpc.functions.async_execution 2025-08-26T19:56:09.2773366Z >>> def bound_async_add(self, to, x, y, z): 2025-08-26T19:56:09.2773538Z >>> return rpc.rpc_async(to, torch.add, args=(x, y)).then( 2025-08-26T19:56:09.2773668Z >>> lambda fut: fut.wait() + z 2025-08-26T19:56:09.2773755Z >>> ) 2025-08-26T19:56:09.2773839Z >>> 2025-08-26T19:56:09.2773941Z >>> # On worker0 2025-08-26T19:56:09.2774041Z >>> ret = rpc.rpc_sync( 2025-08-26T19:56:09.2774133Z >>> "worker1", 2025-08-26T19:56:09.2774282Z >>> AsyncExecutionClass.static_async_add, 2025-08-26T19:56:09.2774406Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T19:56:09.2774501Z >>> ) 2025-08-26T19:56:09.2774621Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:56:09.2774702Z >>> 2025-08-26T19:56:09.2774811Z >>> ret = rpc.rpc_sync( 2025-08-26T19:56:09.2774902Z >>> "worker1", 2025-08-26T19:56:09.2775050Z >>> AsyncExecutionClass.class_async_add, 2025-08-26T19:56:09.2775196Z >>> args=("worker2", torch.ones(2), 1, 2) 2025-08-26T19:56:09.2775279Z >>> ) 2025-08-26T19:56:09.2775408Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:56:09.2775489Z 2025-08-26T19:56:09.2775662Z This decorator also works with RRef helpers, i.e., . 2025-08-26T19:56:09.2775808Z :meth:`torch.distributed.rpc.RRef.rpc_sync`, 2025-08-26T19:56:09.2775965Z :meth:`torch.distributed.rpc.RRef.rpc_async`, and 2025-08-26T19:56:09.2776118Z :meth:`torch.distributed.rpc.RRef.remote`. 2025-08-26T19:56:09.2776202Z 2025-08-26T19:56:09.2776338Z >>> from torch.distributed import rpc 2025-08-26T19:56:09.2776422Z >>> 2025-08-26T19:56:09.2776559Z >>> # reuse the AsyncExecutionClass class above 2025-08-26T19:56:09.2776727Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T19:56:09.2776943Z >>> ret = rref.rpc_sync().static_async_add("worker2", torch.ones(2), 1, 2) 2025-08-26T19:56:09.2777075Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:56:09.2777188Z >>> 2025-08-26T19:56:09.2777344Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T19:56:09.2777591Z >>> ret = rref.rpc_async().static_async_add("worker2", torch.ones(2), 1, 2).wait() 2025-08-26T19:56:09.2777711Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:56:09.2777793Z >>> 2025-08-26T19:56:09.2777957Z >>> rref = rpc.remote("worker1", AsyncExecutionClass) 2025-08-26T19:56:09.2778218Z >>> ret = rref.remote().static_async_add("worker2", torch.ones(2), 1, 2).to_here() 2025-08-26T19:56:09.2778351Z >>> print(ret) # prints tensor([4., 4.]) 2025-08-26T19:56:09.2778431Z 2025-08-26T19:56:09.2778688Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2778781Z 2025-08-26T19:56:09.2778879Z warnings.warn(msg) 2025-08-26T19:56:09.2778971Z 2025-08-26T19:56:09.2779211Z --- Parse Warning: 87 / 146 --- 2025-08-26T19:56:09.2780318Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TensorPipeRpcBackendOptions.set_device_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/options.py line=113. 2025-08-26T19:56:09.2780601Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2780683Z 2025-08-26T19:56:09.2780905Z Set device mapping between each RPC caller and callee pair. This 2025-08-26T19:56:09.2781098Z function can be called multiple times to incrementally add 2025-08-26T19:56:09.2781226Z device placement configurations. 2025-08-26T19:56:09.2781307Z 2025-08-26T19:56:09.2781392Z Args: 2025-08-26T19:56:09.2781501Z to (str): Callee name. 2025-08-26T19:56:09.2781702Z device_map (Dict of int, str, or torch.device): Device placement 2025-08-26T19:56:09.2781891Z mappings from this worker to the callee. This map must be 2025-08-26T19:56:09.2781999Z invertible. 2025-08-26T19:56:09.2782083Z 2025-08-26T19:56:09.2782179Z Example: 2025-08-26T19:56:09.2782298Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2782392Z >>> # both workers 2025-08-26T19:56:09.2782498Z >>> def add(x, y): 2025-08-26T19:56:09.2782640Z >>> print(x) # tensor([1., 1.], device='cuda:1') 2025-08-26T19:56:09.2782762Z >>> return x + y, (x + y).to(2) 2025-08-26T19:56:09.2782846Z >>> 2025-08-26T19:56:09.2782942Z >>> # on worker 0 2025-08-26T19:56:09.2783092Z >>> options = TensorPipeRpcBackendOptions( 2025-08-26T19:56:09.2783198Z >>> num_worker_threads=8, 2025-08-26T19:56:09.2783325Z >>> device_maps={"worker1": {0: 1}} 2025-08-26T19:56:09.2783458Z >>> # maps worker0's cuda:0 to worker1's cuda:1 2025-08-26T19:56:09.2783541Z >>> ) 2025-08-26T19:56:09.2783717Z >>> options.set_device_map("worker1", {1: 2}) 2025-08-26T19:56:09.2783849Z >>> # maps worker0's cuda:1 to worker1's cuda:2 2025-08-26T19:56:09.2783932Z >>> 2025-08-26T19:56:09.2784037Z >>> rpc.init_rpc( 2025-08-26T19:56:09.2784129Z >>> "worker0", 2025-08-26T19:56:09.2784227Z >>> rank=0, 2025-08-26T19:56:09.2784321Z >>> world_size=2, 2025-08-26T19:56:09.2784452Z >>> backend=rpc.BackendType.TENSORPIPE, 2025-08-26T19:56:09.2784574Z >>> rpc_backend_options=options 2025-08-26T19:56:09.2784658Z >>> ) 2025-08-26T19:56:09.2784754Z >>> 2025-08-26T19:56:09.2784851Z >>> x = torch.ones(2) 2025-08-26T19:56:09.2785016Z >>> rets = rpc.rpc_sync("worker1", add, args=(x.to(0), 1)) 2025-08-26T19:56:09.2785216Z >>> # The first argument will be moved to cuda:1 on worker1. When 2025-08-26T19:56:09.2785401Z >>> # sending the return value back, it will follow the invert of 2025-08-26T19:56:09.2785595Z >>> # the device map, and hence will be moved back to cuda:0 and 2025-08-26T19:56:09.2785718Z >>> # cuda:1 on worker0 2025-08-26T19:56:09.2785868Z >>> print(rets[0]) # tensor([2., 2.], device='cuda:0') 2025-08-26T19:56:09.2786029Z >>> print(rets[1]) # tensor([2., 2.], device='cuda:1') 2025-08-26T19:56:09.2786110Z 2025-08-26T19:56:09.2786386Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2786469Z 2025-08-26T19:56:09.2786572Z warnings.warn(msg) 2025-08-26T19:56:09.2786669Z 2025-08-26T19:56:09.2786890Z --- Parse Warning: 88 / 146 --- 2025-08-26T19:56:09.2788041Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=_server_process_global_profile in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/rpc/server_process_global_profiler.py line=19. 2025-08-26T19:56:09.2788357Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2788444Z 2025-08-26T19:56:09.2788658Z It has the same API as ``torch.autograd.profiler.profile`` class, 2025-08-26T19:56:09.2788943Z except that it enables profiling on all threads running RPC server request callbacks. 2025-08-26T19:56:09.2789038Z 2025-08-26T19:56:09.2789324Z Context manager that manages autograd profiler state and holds a summary of results. 2025-08-26T19:56:09.2789562Z Under the hood it just records events of functions being executed in C++ and 2025-08-26T19:56:09.2789817Z exposes those events to Python. You can wrap any code into it and it will 2025-08-26T19:56:09.2789949Z only report runtime of PyTorch functions. 2025-08-26T19:56:09.2790236Z Note: profiler is thread local and is automatically propagated into the async tasks 2025-08-26T19:56:09.2790319Z 2025-08-26T19:56:09.2790404Z Args: 2025-08-26T19:56:09.2790692Z enabled (bool, optional): Setting this to False makes this context manager a no-op. 2025-08-26T19:56:09.2790797Z Default: ``True``. 2025-08-26T19:56:09.2790895Z 2025-08-26T19:56:09.2791187Z use_cuda (bool, optional): Enables timing of CUDA events as well using the cudaEvent API. 2025-08-26T19:56:09.2791392Z Adds approximately 4us of overhead to each tensor operation. 2025-08-26T19:56:09.2791506Z Default: ``False`` 2025-08-26T19:56:09.2791589Z 2025-08-26T19:56:09.2791832Z record_shapes (bool, optional): If shapes recording is set, information 2025-08-26T19:56:09.2792066Z about input dimensions will be collected. This allows one to see which 2025-08-26T19:56:09.2792282Z dimensions have been used under the hood and further group by them 2025-08-26T19:56:09.2792518Z using prof.key_averages(group_by_input_shape=True). Please note that 2025-08-26T19:56:09.2792751Z shape recording might skew your profiling data. It is recommended to 2025-08-26T19:56:09.2793035Z use separate runs with and without shape recording to validate the timing. 2025-08-26T19:56:09.2793267Z Most likely the skew will be negligible for bottom most events (in a case 2025-08-26T19:56:09.2793484Z of nested function calls). But for higher level functions the total 2025-08-26T19:56:09.2793703Z self cpu time might be artificially increased because of the shape 2025-08-26T19:56:09.2793795Z collection. 2025-08-26T19:56:09.2793888Z 2025-08-26T19:56:09.2794162Z profile_memory (bool, optional): Whether to report memory usage, default: ``False`` 2025-08-26T19:56:09.2794243Z 2025-08-26T19:56:09.2794349Z .. warning:: 2025-08-26T19:56:09.2794555Z Enabling memory profiling incurs additional profiler overhead 2025-08-26T19:56:09.2794647Z 2025-08-26T19:56:09.2794736Z .. warning:: 2025-08-26T19:56:09.2795031Z Due to some CUDA multiprocessing limitations (see :ref:`multiprocessing-cuda-note`), 2025-08-26T19:56:09.2795244Z one cannot use the profiler with ``use_cuda = True`` to benchmark 2025-08-26T19:56:09.2795516Z DataLoaders with ``num_workers > 0``. If you wish to benchmark data loading, 2025-08-26T19:56:09.2795693Z please use ``use_cuda = False`` or ``num_workers = 0``. 2025-08-26T19:56:09.2795774Z 2025-08-26T19:56:09.2795859Z Example: 2025-08-26T19:56:09.2795969Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2796061Z >>> # On worker 0: 2025-08-26T19:56:09.2796165Z >>> import torch 2025-08-26T19:56:09.2796293Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2796458Z >>> rpc.init_rpc("worker0", rank=0, world_size=2) 2025-08-26T19:56:09.2796596Z >>> x, y = torch.tensor(1), torch.tensor(2) 2025-08-26T19:56:09.2796713Z >>> outer_profile_rref = rpc.remote( 2025-08-26T19:56:09.2796892Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T19:56:09.2797001Z ... ) 2025-08-26T19:56:09.2797137Z >>> outer_profile_rref.rpc_sync().__enter__() 2025-08-26T19:56:09.2797304Z >>> rpc.rpc_sync(dst_worker_name, torch.add, (x, y)) 2025-08-26T19:56:09.2797421Z >>> inner_profile_rref = rpc.remote( 2025-08-26T19:56:09.2797601Z ... dst_worker_name, rpc._server_process_global_profile 2025-08-26T19:56:09.2797686Z ... ) 2025-08-26T19:56:09.2797818Z >>> inner_profile_rref.rpc_sync().__enter__() 2025-08-26T19:56:09.2797979Z >>> rpc.rpc_sync(dst_worker_name, torch.sub, (x, y)) 2025-08-26T19:56:09.2798161Z >>> inner_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T19:56:09.2798350Z >>> outer_profile_rref.rpc_sync().__exit__(None, None, None) 2025-08-26T19:56:09.2798515Z >>> print(inner_profile_rref.rpc_sync().key_averages()) 2025-08-26T19:56:09.2798758Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2799090Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T19:56:09.2799324Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2799528Z sub 85.06% 76.275us 100.00% 89.667us 89.667us 1 2025-08-26T19:56:09.2799724Z empty 14.94% 13.392us 14.94% 13.392us 13.392us 1 2025-08-26T19:56:09.2799956Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2800080Z Self CPU time total: 89.667us 2025-08-26T19:56:09.2800242Z >>> print(outer_profile_rref.rpc_sync().key_averages()) 2025-08-26T19:56:09.2800479Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2800821Z Name Self CPU total % Self CPU total CPU total % CPU total CPU time avg Number of Calls 2025-08-26T19:56:09.2801058Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2801239Z sub 35.65% 76.275us 41.91% 89.667us 89.667us 1 2025-08-26T19:56:09.2801426Z empty 12.67% 27.101us 12.67% 27.101us 13.551us 2 2025-08-26T19:56:09.2801622Z add 51.68% 110.550us 58.09% 124.259us 124.259us 1 2025-08-26T19:56:09.2801849Z --------- --------------- --------------- --------------- --------------- --------------- --------------- 2025-08-26T19:56:09.2801969Z Self CPU time total: 213.926us 2025-08-26T19:56:09.2802068Z >>> rpc.shutdown() 2025-08-26T19:56:09.2802150Z 2025-08-26T19:56:09.2802257Z >>> # On worker 1: 2025-08-26T19:56:09.2802387Z >>> import torch.distributed.rpc as rpc 2025-08-26T19:56:09.2802574Z >>> rpc.init_rpc("worker1", rank=1, world_size=2) 2025-08-26T19:56:09.2802738Z >>> # wait for worker 0 to finish work, and then shutdown. 2025-08-26T19:56:09.2802835Z >>> rpc.shutdown() 2025-08-26T19:56:09.2802930Z 2025-08-26T19:56:09.2803188Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2803281Z 2025-08-26T19:56:09.2803379Z warnings.warn(msg) 2025-08-26T19:56:09.2803459Z 2025-08-26T19:56:09.2803696Z --- Parse Warning: 89 / 146 --- 2025-08-26T19:56:09.2804725Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=local_map in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_func_map.py line=35. 2025-08-26T19:56:09.2805052Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2805139Z 2025-08-26T19:56:09.2805412Z :meth:`local_map` is an experimental API that allows users to pass :class:`DTensor` s 2025-08-26T19:56:09.2805710Z to a function that is written to be applied on ``torch.Tensor`` s. It is done by extracting 2025-08-26T19:56:09.2805984Z the local components of :class:`DTensor`, call the function, and wrap the outputs to 2025-08-26T19:56:09.2806160Z :class:`DTensor` according to the ``out_placements``. 2025-08-26T19:56:09.2806241Z 2025-08-26T19:56:09.2806325Z Args: 2025-08-26T19:56:09.2806547Z func (Callable): the function to be applied on each local shard of 2025-08-26T19:56:09.2806646Z :class:`DTensor` s. 2025-08-26T19:56:09.2806888Z out_placements (Union[`PlacementType`, Tuple[`PlacementType`, ...]]): 2025-08-26T19:56:09.2807148Z the desired placements of the :class:`DTensor` s in ``func``'s flattened output. 2025-08-26T19:56:09.2807401Z If the flattened ``output`` is a single value, the ``out_placements`` should be 2025-08-26T19:56:09.2807661Z of type `PlacementType`. Otherwise if the flattened ``output`` has multiple 2025-08-26T19:56:09.2807912Z values, the ``out_placements`` should be a tuple of `PlacementType` values 1:1 2025-08-26T19:56:09.2808050Z mapping to the flattened ``output``. 2025-08-26T19:56:09.2808258Z Besides, for :class:`Tensor` output, we use `PlacementType` as its 2025-08-26T19:56:09.2808546Z placements (a `Tuple[Placement]` value). For non-Tensor output, the `PlacementType` 2025-08-26T19:56:09.2808646Z should be `None`. 2025-08-26T19:56:09.2808987Z Note that the only exception is when no :class:`DTensor` argument is passed 2025-08-26T19:56:09.2809228Z in. In this case, even if `out_placements` is not `None`, the result function 2025-08-26T19:56:09.2809495Z should ignore the desired placements because the function is not running with 2025-08-26T19:56:09.2809646Z :class:`DTensor` s. 2025-08-26T19:56:09.2809817Z in_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T19:56:09.2810103Z the required placements of the :class:`DTensor` s in the flattened inputs of ``func``. 2025-08-26T19:56:09.2810354Z If ``in_placements`` is specified, :meth:`local_map` would examine whether the 2025-08-26T19:56:09.2810585Z placements of each :class:`DTensor` argument is the same as the required 2025-08-26T19:56:09.2810790Z placements or not. If the placements are not the same and 2025-08-26T19:56:09.2811039Z ``redistribute_inputs`` is ``False``, an exception will be raised. Otherwise if 2025-08-26T19:56:09.2811287Z ``redistribute_inputs`` is ``True``, the argument will be first redistributed to 2025-08-26T19:56:09.2811562Z the required sharding placements before passing its local tensor to ``func``. 2025-08-26T19:56:09.2811793Z The only exception is when required placements are not ``None`` and the 2025-08-26T19:56:09.2812101Z argument is a :class:`torch.Tensor`. In this case, the placements examination 2025-08-26T19:56:09.2812321Z will be skipped and the argument will be directly passed to ``func``. 2025-08-26T19:56:09.2812562Z If ``in_placements`` is ``None``, no placements examination will be performed. 2025-08-26T19:56:09.2812657Z Default: None 2025-08-26T19:56:09.2812844Z in_grad_placements (Tuple[`PlacementType`, ...], optional): 2025-08-26T19:56:09.2813095Z the placements hint of the :class:`DTensor` s gradient corresponds 2025-08-26T19:56:09.2813311Z to the flattened input DTensor. This argument is the hint that user 2025-08-26T19:56:09.2813510Z can give to :meth:`to_local` in case the gradient layout of the 2025-08-26T19:56:09.2814007Z local tensor input does not match its :class:`DTensor` input layout. 2025-08-26T19:56:09.2814212Z If not specified, we will assume the gradient layout of the local 2025-08-26T19:56:09.2814447Z tensor input remains the same as the original :class:`DTensor` input 2025-08-26T19:56:09.2814616Z and use that for gradient computation. Default: None. 2025-08-26T19:56:09.2814772Z device_mesh (:class:`DeviceMesh`, optional): 2025-08-26T19:56:09.2814997Z the device mesh that the output :class:`DTensor` s are placed on. If not 2025-08-26T19:56:09.2815254Z specified, this will be inferred from the first input :class:`DTensor`'s device 2025-08-26T19:56:09.2815372Z mesh. Default: None. 2025-08-26T19:56:09.2815452Z 2025-08-26T19:56:09.2815555Z Keyword Args: 2025-08-26T19:56:09.2815679Z redistribute_inputs (bool, optional): 2025-08-26T19:56:09.2815941Z the bool value indicating whether to reshard the input :class:`DTensor` s when 2025-08-26T19:56:09.2816207Z their placements are different from the required input placements. If this 2025-08-26T19:56:09.2816441Z value is ``False`` and some :class:`DTensor` input has a different placement, 2025-08-26T19:56:09.2816594Z an exception will be raised. Default: False. 2025-08-26T19:56:09.2816677Z 2025-08-26T19:56:09.2816763Z Returns: 2025-08-26T19:56:09.2817038Z A ``Callable`` that applies ``func`` to each local shard of the input :class:`DTensor` 2025-08-26T19:56:09.2817284Z and returns a :class:`DTensor` constructed from the return value of ``func``. 2025-08-26T19:56:09.2817382Z 2025-08-26T19:56:09.2817470Z Raises: 2025-08-26T19:56:09.2817716Z AssertionError: For any non-DTensor output, we require its corresponding 2025-08-26T19:56:09.2817992Z output placement in ``out_placements`` be None. An AssertionError will be raised 2025-08-26T19:56:09.2818096Z if this is not the case. 2025-08-26T19:56:09.2818192Z 2025-08-26T19:56:09.2818491Z ValueError: If ``redistribute_inputs=False`` but the input :class:`DTensor` needs 2025-08-26T19:56:09.2818651Z a redistribution according to ``in_placements``. 2025-08-26T19:56:09.2818744Z 2025-08-26T19:56:09.2818831Z Example: 2025-08-26T19:56:09.2818961Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2819100Z >>> def mm_allreduce_forward(device_mesh, W, X): 2025-08-26T19:56:09.2819225Z >>> partial_sum_tensor = torch.mm(W, X) 2025-08-26T19:56:09.2819483Z >>> reduced_tensor = funcol.all_reduce(partial_sum_tensor, "sum", device_mesh) 2025-08-26T19:56:09.2819592Z >>> return reduced_tensor 2025-08-26T19:56:09.2819685Z >>> 2025-08-26T19:56:09.2819816Z >>> W = torch.randn(12, 8, requires_grad=False) 2025-08-26T19:56:09.2819947Z >>> X = torch.randn(8, 16, requires_grad=False) 2025-08-26T19:56:09.2820054Z >>> Y = torch.mm(W, X) 2025-08-26T19:56:09.2820247Z >>> row_wise = [Shard(0)] # row-wise sharding placements on 1-d mesh 2025-08-26T19:56:09.2820476Z >>> col_wise = [Shard(1)] # col-wise sharding placements on 1-d mesh 2025-08-26T19:56:09.2820620Z >>> 2025-08-26T19:56:09.2821122Z >>> # local_mm_allreduce_forward is the function wrapped with DTensor/Tensor conversion 2025-08-26T19:56:09.2821283Z >>> local_mm_allreduce_forward = local_map( 2025-08-26T19:56:09.2821510Z >>> mm_allreduce_forward, 2025-08-26T19:56:09.2821664Z >>> out_placements=[Replicate()], 2025-08-26T19:56:09.2821831Z >>> in_placements=[col_wise, row_wise], 2025-08-26T19:56:09.2822055Z >>> device_mesh=device_mesh, 2025-08-26T19:56:09.2822194Z >>> ) 2025-08-26T19:56:09.2822358Z >>> 2025-08-26T19:56:09.2822500Z >>> W_dt = distribute_tensor( 2025-08-26T19:56:09.2822650Z ... W, device_mesh, (col_wise) 2025-08-26T19:56:09.2822819Z ... ) # col-wisely sharded W tensor 2025-08-26T19:56:09.2823026Z >>> X_dt = distribute_tensor( 2025-08-26T19:56:09.2823228Z ... X, device_mesh, (row_wise) 2025-08-26T19:56:09.2823374Z ... ) # row-wisely sharded X tensor 2025-08-26T19:56:09.2823531Z >>> Y_dt = local_mm_allreduce_forward( 2025-08-26T19:56:09.2823712Z ... device_mesh, W_dt, X_dt 2025-08-26T19:56:09.2823875Z ... ) # apply local_mm_allreduce_forward to DTensors 2025-08-26T19:56:09.2824093Z 2025-08-26T19:56:09.2824332Z .. note:: This API is currently experimental and subject to change 2025-08-26T19:56:09.2824446Z 2025-08-26T19:56:09.2824792Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2824906Z 2025-08-26T19:56:09.2825092Z warnings.warn(msg) 2025-08-26T19:56:09.2825222Z 2025-08-26T19:56:09.2825517Z --- Parse Warning: 90 / 146 --- 2025-08-26T19:56:09.2826722Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_sharding in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/experimental/_register_sharding.py line=25. 2025-08-26T19:56:09.2827028Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2827166Z 2025-08-26T19:56:09.2827521Z :meth:`register_sharding` is an experimental API that allows users to register sharding 2025-08-26T19:56:09.2827859Z strategies for an operator when the tensor inputs and outputs are DTensor. 2025-08-26T19:56:09.2828159Z It can be useful when: (1) there doesn't exist a default sharding strategy for ``op``, 2025-08-26T19:56:09.2828441Z e.g. when ``op`` is a custom operator that is not supported by :class:`DTensor`; (2) 2025-08-26T19:56:09.2828798Z when users would like to overwrite default sharding strategies of existing operators. 2025-08-26T19:56:09.2828892Z 2025-08-26T19:56:09.2829101Z Args: 2025-08-26T19:56:09.2829278Z op (Union[OpOverload, List[OpOverload]]): 2025-08-26T19:56:09.2829545Z An op or a list of ops to register the customized sharding function. 2025-08-26T19:56:09.2829706Z 2025-08-26T19:56:09.2829825Z Returns: 2025-08-26T19:56:09.2830185Z A function decorator which can be used to wrap a function that defines the sharding 2025-08-26T19:56:09.2830524Z strategy for the operator specified in ``op``. The defined sharding strategy will be 2025-08-26T19:56:09.2830838Z registered to DTensor and will override the default sharding strategy if DTensor has 2025-08-26T19:56:09.2831230Z already implemented the operator. The customized sharding function takes the same inputs 2025-08-26T19:56:09.2831513Z as the original op (except that if an arg is a :class:`torch.Tensor`, it will be 2025-08-26T19:56:09.2831848Z replaced by a tensor-like object that DTensor uses internally). The function should 2025-08-26T19:56:09.2832186Z return a sequence of 2-tuples, each specifying acceptable output placements and its 2025-08-26T19:56:09.2832466Z corresponding input placements. 2025-08-26T19:56:09.2832580Z 2025-08-26T19:56:09.2832700Z Example: 2025-08-26T19:56:09.2832894Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2833045Z >>> @register_sharding(aten._softmax.default) 2025-08-26T19:56:09.2833276Z >>> def custom_softmax_sharding(x, dim, half_to_float): 2025-08-26T19:56:09.2833515Z >>> softmax_dim = dim if dim >= 0 else dim + x.ndim 2025-08-26T19:56:09.2833664Z >>> acceptable_shardings = [] 2025-08-26T19:56:09.2833824Z >>> 2025-08-26T19:56:09.2834067Z >>> all_replicate = ([Replicate()], [Replicate(), None, None]) 2025-08-26T19:56:09.2834315Z >>> acceptable_shardings.append(all_replicate) 2025-08-26T19:56:09.2834448Z >>> 2025-08-26T19:56:09.2834602Z >>> for sharding_dim in range(x.ndim): 2025-08-26T19:56:09.2834797Z >>> if sharding_dim != softmax_dim: 2025-08-26T19:56:09.2834968Z >>> all_sharded = ( 2025-08-26T19:56:09.2835125Z >>> [Shard(sharding_dim)], 2025-08-26T19:56:09.2835343Z >>> [Shard(sharding_dim), None, None], 2025-08-26T19:56:09.2835483Z >>> ) 2025-08-26T19:56:09.2835703Z >>> acceptable_shardings.append(all_sharded) 2025-08-26T19:56:09.2835821Z >>> 2025-08-26T19:56:09.2835975Z >>> return acceptable_shardings 2025-08-26T19:56:09.2836139Z 2025-08-26T19:56:09.2836406Z .. note:: This API is currently experimental and subject to change 2025-08-26T19:56:09.2836583Z 2025-08-26T19:56:09.2836873Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2836987Z 2025-08-26T19:56:09.2837171Z warnings.warn(msg) 2025-08-26T19:56:09.2837265Z 2025-08-26T19:56:09.2837845Z --- Parse Warning: 91 / 146 --- 2025-08-26T19:56:09.2838936Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=428. 2025-08-26T19:56:09.2839302Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2839415Z 2025-08-26T19:56:09.2839845Z Configure the nn.Module's inputs to convert the input tensors of the nn.Module to DTensors at runtime according to 2025-08-26T19:56:09.2840269Z ``input_layouts``, and perform layout redistribution according to the ``desired_input_layouts``. 2025-08-26T19:56:09.2840398Z 2025-08-26T19:56:09.2840563Z Keyword Args: 2025-08-26T19:56:09.2840812Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:56:09.2841180Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T19:56:09.2841603Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T19:56:09.2841882Z as a placeholder. default: None. 2025-08-26T19:56:09.2842212Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:56:09.2842641Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:56:09.2843124Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T19:56:09.2843335Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T19:56:09.2843730Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T19:56:09.2843953Z default: None 2025-08-26T19:56:09.2844160Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T19:56:09.2844616Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:56:09.2844844Z have the desired DTensor layouts. default: None. 2025-08-26T19:56:09.2844996Z use_local_output (bool, optional): 2025-08-26T19:56:09.2845457Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T19:56:09.2845601Z Returns: 2025-08-26T19:56:09.2846003Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs. 2025-08-26T19:56:09.2846117Z 2025-08-26T19:56:09.2846285Z Example:: 2025-08-26T19:56:09.2846458Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:56:09.2846855Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInput 2025-08-26T19:56:09.2847157Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T19:56:09.2847274Z >>> ... 2025-08-26T19:56:09.2847708Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T19:56:09.2847876Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T19:56:09.2847972Z >>> 2025-08-26T19:56:09.2848448Z >>> # According to the style specified below, the first input of attn will be annotated to Sharded DTensor 2025-08-26T19:56:09.2848630Z >>> # and then redistributed to Replicated DTensor. 2025-08-26T19:56:09.2848927Z >>> parallelize_module( 2025-08-26T19:56:09.2849100Z >>> block, # this can be a submodule or module 2025-08-26T19:56:09.2849235Z >>> tp_mesh, 2025-08-26T19:56:09.2849440Z >>> parallelize_plan={ 2025-08-26T19:56:09.2849612Z >>> "attn": PrepareModuleInput( 2025-08-26T19:56:09.2849828Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T19:56:09.2850038Z >>> desired_input_layouts=(Replicate(), None, None, ...) 2025-08-26T19:56:09.2850164Z >>> ), 2025-08-26T19:56:09.2850314Z >>> } 2025-08-26T19:56:09.2850463Z >>> ) 2025-08-26T19:56:09.2850641Z 2025-08-26T19:56:09.2850933Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2851046Z 2025-08-26T19:56:09.2851229Z warnings.warn(msg) 2025-08-26T19:56:09.2851326Z 2025-08-26T19:56:09.2851668Z --- Parse Warning: 92 / 146 --- 2025-08-26T19:56:09.2852762Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=597. 2025-08-26T19:56:09.2853064Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2853230Z 2025-08-26T19:56:09.2853673Z Configure the nn.Module's outputs to convert the output tensors of the nn.Module to DTensors at runtime according to 2025-08-26T19:56:09.2854142Z ``output_layouts``, and perform layout redistribution according to the ``desired_output_layouts``. 2025-08-26T19:56:09.2854271Z 2025-08-26T19:56:09.2854393Z Keyword Args: 2025-08-26T19:56:09.2854686Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:56:09.2855067Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T19:56:09.2855518Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T19:56:09.2855725Z ``None`` need to be specified as a placeholder. 2025-08-26T19:56:09.2856019Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:56:09.2856454Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T19:56:09.2856620Z have the desired DTensor layouts. 2025-08-26T19:56:09.2856845Z use_local_output (bool, optional): 2025-08-26T19:56:09.2857227Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T19:56:09.2857438Z Returns: 2025-08-26T19:56:09.2857770Z A ParallelStyle object that prepares the sharding layouts of the nn.Module's outputs. 2025-08-26T19:56:09.2857892Z 2025-08-26T19:56:09.2858066Z Example:: 2025-08-26T19:56:09.2858207Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:56:09.2858651Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleOutput 2025-08-26T19:56:09.2858899Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T19:56:09.2859026Z >>> ... 2025-08-26T19:56:09.2859412Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T19:56:09.2859608Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T19:56:09.2859750Z >>> 2025-08-26T19:56:09.2860227Z >>> # According to the style specified below, the output of the TransformerBlock will be converted to Replicated DTensor 2025-08-26T19:56:09.2860454Z >>> # and then redistributed to Sharded DTensor. 2025-08-26T19:56:09.2860634Z >>> parallelize_module( 2025-08-26T19:56:09.2860803Z >>> block, # this can be a submodule or module 2025-08-26T19:56:09.2860972Z >>> tp_mesh, 2025-08-26T19:56:09.2861125Z >>> parallelize_plan = PrepareModuleOutput( 2025-08-26T19:56:09.2861313Z >>> output_layouts=Replicate(), 2025-08-26T19:56:09.2861535Z >>> desired_output_layouts=Shard(0) 2025-08-26T19:56:09.2861651Z >>> ) 2025-08-26T19:56:09.2861809Z >>> ) 2025-08-26T19:56:09.2861926Z 2025-08-26T19:56:09.2862198Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2862416Z 2025-08-26T19:56:09.2862546Z warnings.warn(msg) 2025-08-26T19:56:09.2862703Z 2025-08-26T19:56:09.2862940Z --- Parse Warning: 93 / 146 --- 2025-08-26T19:56:09.2864057Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=PrepareModuleInputOutput in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributed/tensor/parallel/style.py line=705. 2025-08-26T19:56:09.2864431Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2869353Z 2025-08-26T19:56:09.2869851Z Configure the nn.Module's inputs (and outputs) to convert the input tensors (and output tensors, respectively) of the nn.Module 2025-08-26T19:56:09.2870300Z to DTensors at runtime according to ``input_layouts`` (and output_layouts, respectively), and perform layout redistribution 2025-08-26T19:56:09.2870693Z according to the ``desired_input_layouts`` (and ``desired_output_layouts``, respectively). This is a combination of 2025-08-26T19:56:09.2870989Z :class:`PrepareModuleInput` and :class:`PrepareModuleOutput`. 2025-08-26T19:56:09.2871091Z 2025-08-26T19:56:09.2871183Z Keyword Args: 2025-08-26T19:56:09.2871408Z input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:56:09.2871748Z The DTensor layouts of input tensors for the nn.Module, this is used to convert the input tensors to 2025-08-26T19:56:09.2872115Z DTensors. If some inputs are not torch.Tensor or no need to convert to DTensors, ``None`` need to be specified 2025-08-26T19:56:09.2872255Z as a placeholder. default: None. 2025-08-26T19:56:09.2872490Z desired_input_layouts (Union[Placement, Tuple[Optional[Placement]]]): 2025-08-26T19:56:09.2872887Z The desired DTensor layout of input tensors for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:56:09.2873291Z have the desired DTensor layouts. This argument needs to have the same length with ``input_layouts``. default: None. 2025-08-26T19:56:09.2873476Z input_kwarg_layouts (Dict[str, Placement]): 2025-08-26T19:56:09.2873859Z The DTensor layouts of input kwargs for the nn.Module, this is used to convert the input kwarg tensors to DTensors. 2025-08-26T19:56:09.2873954Z default: None 2025-08-26T19:56:09.2874132Z desired_input_kwarg_layouts: (Dict[str, Placement]): 2025-08-26T19:56:09.2874509Z The desired DTensor layout of input kwargs for the nn.Module, this is used to ensure the inputs of the nn.Module 2025-08-26T19:56:09.2874697Z have the desired DTensor layouts. default: None. 2025-08-26T19:56:09.2874816Z use_local_input (bool, optional): 2025-08-26T19:56:09.2875183Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module inputs, default: False. 2025-08-26T19:56:09.2875394Z output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:56:09.2875742Z The DTensor layouts of output tensors for the nn.Module, this is used to convert the output tensors to 2025-08-26T19:56:09.2876142Z DTensors if they are :class:`torch.Tensor`. If some outputs are not torch.Tensor or no need to convert to DTensors, 2025-08-26T19:56:09.2876290Z ``None`` need to be specified as a placeholder. 2025-08-26T19:56:09.2876505Z desired_output_layouts (Union[Placement, Tuple[Placement]]): 2025-08-26T19:56:09.2876904Z The desired DTensor layouts of output tensors for the nn.Module, this is used to ensure the outputs of the nn.Module 2025-08-26T19:56:09.2877025Z have the desired DTensor layouts. 2025-08-26T19:56:09.2877153Z use_local_output (bool, optional): 2025-08-26T19:56:09.2877521Z Whether to use local :class:`torch.Tensor` instead of :class:`DTensor` for the module outputs, default: True. 2025-08-26T19:56:09.2877617Z Returns: 2025-08-26T19:56:09.2877998Z A :class:`ParallelStyle` object that prepares the sharding layouts of the nn.Module's inputs and outputs. 2025-08-26T19:56:09.2878084Z 2025-08-26T19:56:09.2878190Z Example:: 2025-08-26T19:56:09.2878301Z >>> # xdoctest: +SKIP(failing) 2025-08-26T19:56:09.2878657Z >>> from torch.distributed.tensor.parallel import parallelize_module, PrepareModuleInputOutput 2025-08-26T19:56:09.2878852Z >>> from torch.distributed.device_mesh import init_device_mesh 2025-08-26T19:56:09.2878936Z >>> ... 2025-08-26T19:56:09.2879262Z >>> block = TransformerBlock(...) # block is a nn.Module that contains an "attn" Attention submodule 2025-08-26T19:56:09.2879394Z >>> tp_mesh = init_device_mesh("cuda", (8,)) 2025-08-26T19:56:09.2879492Z >>> 2025-08-26T19:56:09.2879831Z >>> # According to the style specified below, the first input of attn will be annotated as Sharded DTensor 2025-08-26T19:56:09.2880198Z >>> # and then redistributed to Replicated DTensor, and the output of the TransformerBlock will be annotated 2025-08-26T19:56:09.2880452Z >>> # as Replicated DTensor and then redistributed to Sharded DTensor. 2025-08-26T19:56:09.2880557Z >>> parallelize_module( 2025-08-26T19:56:09.2880706Z >>> block, # this can be a submodule or module 2025-08-26T19:56:09.2880798Z >>> tp_mesh, 2025-08-26T19:56:09.2880903Z >>> parallelize_plan={ 2025-08-26T19:56:09.2881051Z >>> "attn": PrepareModuleInputOutput( 2025-08-26T19:56:09.2881191Z >>> input_layouts=(Shard(0), None, None, ...), 2025-08-26T19:56:09.2881382Z >>> desired_input_layouts=(Replicate(), None, None, ...), 2025-08-26T19:56:09.2881503Z >>> output_layouts=Replicate(), 2025-08-26T19:56:09.2881633Z >>> desired_output_layouts=Shard(0), 2025-08-26T19:56:09.2881728Z >>> ), 2025-08-26T19:56:09.2881811Z >>> } 2025-08-26T19:56:09.2881909Z >>> ) 2025-08-26T19:56:09.2881989Z 2025-08-26T19:56:09.2882278Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2882370Z 2025-08-26T19:56:09.2882467Z warnings.warn(msg) 2025-08-26T19:56:09.2882548Z 2025-08-26T19:56:09.2882801Z --- Parse Warning: 94 / 146 --- 2025-08-26T19:56:09.2883953Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=LowRankMultivariateNormal in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/lowrank_multivariate_normal.py line=56. 2025-08-26T19:56:09.2884232Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2884316Z 2025-08-26T19:56:09.2884644Z Creates a multivariate normal distribution with covariance matrix having a low-rank form 2025-08-26T19:56:09.2884838Z parameterized by :attr:`cov_factor` and :attr:`cov_diag`:: 2025-08-26T19:56:09.2884949Z 2025-08-26T19:56:09.2885141Z covariance_matrix = cov_factor @ cov_factor.T + cov_diag 2025-08-26T19:56:09.2885223Z 2025-08-26T19:56:09.2885324Z Example: 2025-08-26T19:56:09.2885472Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T19:56:09.2885615Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:09.2885747Z >>> m = LowRankMultivariateNormal( 2025-08-26T19:56:09.2885929Z ... torch.zeros(2), torch.tensor([[1.0], [0.0]]), torch.ones(2) 2025-08-26T19:56:09.2886027Z ... ) 2025-08-26T19:56:09.2886325Z >>> m.sample() # normally distributed with mean=`[0,0]`, cov_factor=`[[1],[0]]`, cov_diag=`[1,1]` 2025-08-26T19:56:09.2886427Z tensor([-0.2102, -0.5429]) 2025-08-26T19:56:09.2886519Z 2025-08-26T19:56:09.2886606Z Args: 2025-08-26T19:56:09.2886860Z loc (Tensor): mean of the distribution with shape `batch_shape + event_shape` 2025-08-26T19:56:09.2887127Z cov_factor (Tensor): factor part of low-rank form of covariance matrix with shape 2025-08-26T19:56:09.2887256Z `batch_shape + event_shape + (rank,)` 2025-08-26T19:56:09.2887531Z cov_diag (Tensor): diagonal part of low-rank form of covariance matrix with shape 2025-08-26T19:56:09.2887641Z `batch_shape + event_shape` 2025-08-26T19:56:09.2887734Z 2025-08-26T19:56:09.2887817Z Note: 2025-08-26T19:56:09.2888091Z The computation for determinant and inverse of covariance matrix is avoided when 2025-08-26T19:56:09.2888345Z `cov_factor.shape[1] << cov_factor.shape[0]` thanks to `Woodbury matrix identity 2025-08-26T19:56:09.2888563Z `_ and 2025-08-26T19:56:09.2888964Z `matrix determinant lemma `_. 2025-08-26T19:56:09.2889224Z Thanks to these formulas, we just need to compute the determinant and inverse of 2025-08-26T19:56:09.2889393Z the small size "capacitance" matrix:: 2025-08-26T19:56:09.2889493Z 2025-08-26T19:56:09.2889679Z capacitance = I + cov_factor.T @ inv(cov_diag) @ cov_factor 2025-08-26T19:56:09.2889771Z 2025-08-26T19:56:09.2890029Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2890111Z 2025-08-26T19:56:09.2890225Z warnings.warn(msg) 2025-08-26T19:56:09.2890306Z 2025-08-26T19:56:09.2890515Z --- Parse Warning: 95 / 146 --- 2025-08-26T19:56:09.2891555Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MixtureSameFamily in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/mixture_same_family.py line=15. 2025-08-26T19:56:09.2891824Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2891918Z 2025-08-26T19:56:09.2892152Z The `MixtureSameFamily` distribution implements a (batch of) mixture 2025-08-26T19:56:09.2892416Z distribution where all component are from different parameterizations of 2025-08-26T19:56:09.2892663Z the same distribution type. It is parameterized by a `Categorical` 2025-08-26T19:56:09.2892866Z "selecting distribution" (over `k` component) and a component 2025-08-26T19:56:09.2893088Z distribution, i.e., a `Distribution` with a rightmost batch shape 2025-08-26T19:56:09.2893253Z (equal to `[k]`) which indexes each (batch of) component. 2025-08-26T19:56:09.2893348Z 2025-08-26T19:56:09.2893439Z Examples:: 2025-08-26T19:56:09.2893520Z 2025-08-26T19:56:09.2893679Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.2893885Z >>> # Construct Gaussian Mixture Model in 1D consisting of 5 equally 2025-08-26T19:56:09.2894012Z >>> # weighted normal distributions 2025-08-26T19:56:09.2894131Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T19:56:09.2894306Z >>> comp = D.Normal(torch.randn(5,), torch.rand(5,)) 2025-08-26T19:56:09.2894443Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T19:56:09.2894527Z 2025-08-26T19:56:09.2894732Z >>> # Construct Gaussian Mixture Model in 2D consisting of 5 equally 2025-08-26T19:56:09.2894874Z >>> # weighted bivariate normal distributions 2025-08-26T19:56:09.2894995Z >>> mix = D.Categorical(torch.ones(5,)) 2025-08-26T19:56:09.2895120Z >>> comp = D.Independent(D.Normal( 2025-08-26T19:56:09.2895252Z ... torch.randn(5,2), torch.rand(5,2)), 1) 2025-08-26T19:56:09.2895375Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T19:56:09.2895467Z 2025-08-26T19:56:09.2895651Z >>> # Construct a batch of 3 Gaussian Mixture Models in 2D each 2025-08-26T19:56:09.2895866Z >>> # consisting of 5 random weighted bivariate normal distributions 2025-08-26T19:56:09.2895987Z >>> mix = D.Categorical(torch.rand(3,5)) 2025-08-26T19:56:09.2896102Z >>> comp = D.Independent(D.Normal( 2025-08-26T19:56:09.2896251Z ... torch.randn(3,5,2), torch.rand(3,5,2)), 1) 2025-08-26T19:56:09.2896374Z >>> gmm = MixtureSameFamily(mix, comp) 2025-08-26T19:56:09.2896464Z 2025-08-26T19:56:09.2896547Z Args: 2025-08-26T19:56:09.2896757Z mixture_distribution: `torch.distributions.Categorical`-like 2025-08-26T19:56:09.2896958Z instance. Manages the probability of selecting component. 2025-08-26T19:56:09.2897130Z The number of categories must match the rightmost batch 2025-08-26T19:56:09.2897333Z dimension of the `component_distribution`. Must have either 2025-08-26T19:56:09.2897476Z scalar `batch_shape` or `batch_shape` matching 2025-08-26T19:56:09.2897615Z `component_distribution.batch_shape[:-1]` 2025-08-26T19:56:09.2897845Z component_distribution: `torch.distributions.Distribution`-like 2025-08-26T19:56:09.2898027Z instance. Right-most batch dimension indexes component. 2025-08-26T19:56:09.2898148Z 2025-08-26T19:56:09.2898402Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2898485Z 2025-08-26T19:56:09.2898599Z warnings.warn(msg) 2025-08-26T19:56:09.2898681Z 2025-08-26T19:56:09.2898887Z --- Parse Warning: 96 / 146 --- 2025-08-26T19:56:09.2899904Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedBernoulli in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_bernoulli.py line=120. 2025-08-26T19:56:09.2900176Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2900268Z 2025-08-26T19:56:09.2900458Z Creates a RelaxedBernoulli distribution, parametrized by 2025-08-26T19:56:09.2900665Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits` 2025-08-26T19:56:09.2900886Z (but not both). This is a relaxed version of the `Bernoulli` distribution, 2025-08-26T19:56:09.2901076Z so the values are in (0, 1), and has reparametrizable samples. 2025-08-26T19:56:09.2901213Z 2025-08-26T19:56:09.2901306Z Example:: 2025-08-26T19:56:09.2901400Z 2025-08-26T19:56:09.2901542Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:09.2901677Z >>> m = RelaxedBernoulli(torch.tensor([2.2]), 2025-08-26T19:56:09.2901814Z ... torch.tensor([0.1, 0.2, 0.3, 0.99])) 2025-08-26T19:56:09.2901903Z >>> m.sample() 2025-08-26T19:56:09.2902033Z tensor([ 0.2951, 0.3442, 0.8918, 0.9021]) 2025-08-26T19:56:09.2902142Z 2025-08-26T19:56:09.2902230Z Args: 2025-08-26T19:56:09.2902386Z temperature (Tensor): relaxation temperature 2025-08-26T19:56:09.2902562Z probs (Number, Tensor): the probability of sampling `1` 2025-08-26T19:56:09.2902736Z logits (Number, Tensor): the log-odds of sampling `1` 2025-08-26T19:56:09.2902818Z 2025-08-26T19:56:09.2903106Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2903201Z 2025-08-26T19:56:09.2903302Z warnings.warn(msg) 2025-08-26T19:56:09.2903394Z 2025-08-26T19:56:09.2903583Z --- Parse Warning: 97 / 146 --- 2025-08-26T19:56:09.2904656Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=RelaxedOneHotCategorical in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/distributions/relaxed_categorical.py line=109. 2025-08-26T19:56:09.2904936Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2905017Z 2025-08-26T19:56:09.2905247Z Creates a RelaxedOneHotCategorical distribution parametrized by 2025-08-26T19:56:09.2905444Z :attr:`temperature`, and either :attr:`probs` or :attr:`logits`. 2025-08-26T19:56:09.2905688Z This is a relaxed version of the :class:`OneHotCategorical` distribution, so 2025-08-26T19:56:09.2905870Z its samples are on simplex, and are reparametrizable. 2025-08-26T19:56:09.2905957Z 2025-08-26T19:56:09.2906060Z Example:: 2025-08-26T19:56:09.2906142Z 2025-08-26T19:56:09.2906283Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:09.2906453Z >>> m = RelaxedOneHotCategorical(torch.tensor([2.2]), 2025-08-26T19:56:09.2906584Z ... torch.tensor([0.1, 0.2, 0.3, 0.4])) 2025-08-26T19:56:09.2906688Z >>> m.sample() 2025-08-26T19:56:09.2906810Z tensor([ 0.1294, 0.2324, 0.3859, 0.2523]) 2025-08-26T19:56:09.2906891Z 2025-08-26T19:56:09.2906989Z Args: 2025-08-26T19:56:09.2907136Z temperature (Tensor): relaxation temperature 2025-08-26T19:56:09.2907258Z probs (Tensor): event probabilities 2025-08-26T19:56:09.2907461Z logits (Tensor): unnormalized log probability for each event 2025-08-26T19:56:09.2907545Z 2025-08-26T19:56:09.2907814Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2907957Z 2025-08-26T19:56:09.2908055Z warnings.warn(msg) 2025-08-26T19:56:09.2908144Z 2025-08-26T19:56:09.2908332Z --- Parse Warning: 98 / 146 --- 2025-08-26T19:56:09.2909383Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assoc_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=245. 2025-08-26T19:56:09.2909653Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2909858Z Return a new dict with new, potentially nested, key value pair 2025-08-26T19:56:09.2909939Z 2025-08-26T19:56:09.2910038Z >>> purchase = { 2025-08-26T19:56:09.2910147Z ... "name": "Alice", 2025-08-26T19:56:09.2910324Z ... "order": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T19:56:09.2910452Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T19:56:09.2910580Z ... } 2025-08-26T19:56:09.2910790Z >>> assoc_in(purchase, ["order", "costs"], [0.25, 1.00]) # doctest: +SKIP 2025-08-26T19:56:09.2910918Z {'credit card': '5555-1234-1234-1234', 2025-08-26T19:56:09.2911011Z 'name': 'Alice', 2025-08-26T19:56:09.2911178Z 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} 2025-08-26T19:56:09.2911272Z 2025-08-26T19:56:09.2911526Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2911619Z 2025-08-26T19:56:09.2911740Z warnings.warn(msg) 2025-08-26T19:56:09.2911823Z 2025-08-26T19:56:09.2912017Z --- Parse Warning: 99 / 146 --- 2025-08-26T19:56:09.2913093Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=update_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=261. 2025-08-26T19:56:09.2913376Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2913531Z Update value in a (potentially) nested dictionary 2025-08-26T19:56:09.2913614Z 2025-08-26T19:56:09.2913708Z inputs: 2025-08-26T19:56:09.2913822Z d - dictionary on which to operate 2025-08-26T19:56:09.2914055Z keys - list or tuple giving the location of the value to be changed in d 2025-08-26T19:56:09.2914184Z func - function to operate on that value 2025-08-26T19:56:09.2914264Z 2025-08-26T19:56:09.2914468Z If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the 2025-08-26T19:56:09.2914704Z original dictionary with v replaced by func(v), but does not mutate the 2025-08-26T19:56:09.2914816Z original dictionary. 2025-08-26T19:56:09.2914898Z 2025-08-26T19:56:09.2915113Z If k0 is not a key in d, update_in creates nested dictionaries to the depth 2025-08-26T19:56:09.2915341Z specified by the keys, with the innermost value set to func(default). 2025-08-26T19:56:09.2915424Z 2025-08-26T19:56:09.2915538Z >>> inc = lambda x: x + 1 2025-08-26T19:56:09.2915647Z >>> update_in({"a": 0}, ["a"], inc) 2025-08-26T19:56:09.2915731Z {'a': 1} 2025-08-26T19:56:09.2915824Z 2025-08-26T19:56:09.2915924Z >>> transaction = { 2025-08-26T19:56:09.2916028Z ... "name": "Alice", 2025-08-26T19:56:09.2916221Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T19:56:09.2916345Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T19:56:09.2916435Z ... } 2025-08-26T19:56:09.2916654Z >>> update_in(transaction, ["purchase", "costs"], sum) # doctest: +SKIP 2025-08-26T19:56:09.2916774Z {'credit card': '5555-1234-1234-1234', 2025-08-26T19:56:09.2916867Z 'name': 'Alice', 2025-08-26T19:56:09.2917067Z 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} 2025-08-26T19:56:09.2917161Z 2025-08-26T19:56:09.2917283Z >>> # updating a value when k0 is not in d 2025-08-26T19:56:09.2917414Z >>> update_in({}, [1, 2, 3], str, default="bar") 2025-08-26T19:56:09.2917515Z {1: {2: {3: 'bar'}}} 2025-08-26T19:56:09.2917634Z >>> update_in({1: "foo"}, [2, 3, 4], inc, 0) 2025-08-26T19:56:09.2917737Z {1: 'foo', 2: {3: {4: 1}}} 2025-08-26T19:56:09.2917819Z 2025-08-26T19:56:09.2918077Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2918171Z 2025-08-26T19:56:09.2918270Z warnings.warn(msg) 2025-08-26T19:56:09.2918362Z 2025-08-26T19:56:09.2918552Z --- Parse Warning: 100 / 146 --- 2025-08-26T19:56:09.2919582Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=get_in in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=320. 2025-08-26T19:56:09.2919896Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2920066Z Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. 2025-08-26T19:56:09.2920159Z 2025-08-26T19:56:09.2920341Z If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless 2025-08-26T19:56:09.2920547Z ``no_default`` is specified, then it raises KeyError or IndexError. 2025-08-26T19:56:09.2920641Z 2025-08-26T19:56:09.2920876Z ``get_in`` is a generalization of ``operator.getitem`` for nested data 2025-08-26T19:56:09.2921024Z structures such as dictionaries and lists. 2025-08-26T19:56:09.2921106Z 2025-08-26T19:56:09.2921204Z >>> transaction = { 2025-08-26T19:56:09.2921315Z ... "name": "Alice", 2025-08-26T19:56:09.2921510Z ... "purchase": {"items": ["Apple", "Orange"], "costs": [0.50, 1.25]}, 2025-08-26T19:56:09.2921672Z ... "credit card": "5555-1234-1234-1234", 2025-08-26T19:56:09.2921759Z ... } 2025-08-26T19:56:09.2921898Z >>> get_in(["purchase", "items", 0], transaction) 2025-08-26T19:56:09.2921996Z 'Apple' 2025-08-26T19:56:09.2922106Z >>> get_in(["name"], transaction) 2025-08-26T19:56:09.2922203Z 'Alice' 2025-08-26T19:56:09.2922335Z >>> get_in(["purchase", "total"], transaction) 2025-08-26T19:56:09.2922485Z >>> get_in(["purchase", "items", "apple"], transaction) 2025-08-26T19:56:09.2922632Z >>> get_in(["purchase", "items", 10], transaction) 2025-08-26T19:56:09.2922770Z >>> get_in(["purchase", "total"], transaction, 0) 2025-08-26T19:56:09.2922865Z 0 2025-08-26T19:56:09.2922980Z >>> get_in(["y"], {}, no_default=True) 2025-08-26T19:56:09.2923094Z Traceback (most recent call last): 2025-08-26T19:56:09.2923188Z ... 2025-08-26T19:56:09.2923280Z KeyError: 'y' 2025-08-26T19:56:09.2923377Z 2025-08-26T19:56:09.2923462Z See Also: 2025-08-26T19:56:09.2923556Z itertoolz.get 2025-08-26T19:56:09.2923665Z operator.getitem 2025-08-26T19:56:09.2923746Z 2025-08-26T19:56:09.2924001Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2924092Z 2025-08-26T19:56:09.2924186Z warnings.warn(msg) 2025-08-26T19:56:09.2924282Z 2025-08-26T19:56:09.2924469Z --- Parse Warning: 101 / 146 --- 2025-08-26T19:56:09.2925515Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=groupby in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/unification/unification_tools.py line=373. 2025-08-26T19:56:09.2925794Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2925908Z Group a collection by a key function 2025-08-26T19:56:09.2926001Z 2025-08-26T19:56:09.2926199Z >>> names = ["Alice", "Bob", "Charlie", "Dan", "Edith", "Frank"] 2025-08-26T19:56:09.2926326Z >>> groupby(len, names) # doctest: +SKIP 2025-08-26T19:56:09.2926500Z {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} 2025-08-26T19:56:09.2926580Z 2025-08-26T19:56:09.2926702Z >>> iseven = lambda x: x % 2 == 0 2025-08-26T19:56:09.2926872Z >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP 2025-08-26T19:56:09.2926985Z {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} 2025-08-26T19:56:09.2927076Z 2025-08-26T19:56:09.2927222Z Non-callable keys imply grouping on a member. 2025-08-26T19:56:09.2927313Z 2025-08-26T19:56:09.2927398Z >>> groupby( 2025-08-26T19:56:09.2927489Z ... "gender", 2025-08-26T19:56:09.2927583Z ... [ 2025-08-26T19:56:09.2927704Z ... {"name": "Alice", "gender": "F"}, 2025-08-26T19:56:09.2927835Z ... {"name": "Bob", "gender": "M"}, 2025-08-26T19:56:09.2927960Z ... {"name": "Charlie", "gender": "M"}, 2025-08-26T19:56:09.2928076Z ... ], 2025-08-26T19:56:09.2928186Z ... ) # doctest:+SKIP 2025-08-26T19:56:09.2928300Z {'F': [{'gender': 'F', 'name': 'Alice'}], 2025-08-26T19:56:09.2928410Z 'M': [{'gender': 'M', 'name': 'Bob'}, 2025-08-26T19:56:09.2928535Z {'gender': 'M', 'name': 'Charlie'}]} 2025-08-26T19:56:09.2928615Z 2025-08-26T19:56:09.2928772Z Not to be confused with ``itertools.groupby`` 2025-08-26T19:56:09.2928948Z 2025-08-26T19:56:09.2929036Z See Also: 2025-08-26T19:56:09.2929162Z countby 2025-08-26T19:56:09.2929245Z 2025-08-26T19:56:09.2929517Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2929597Z 2025-08-26T19:56:09.2929694Z warnings.warn(msg) 2025-08-26T19:56:09.2929785Z 2025-08-26T19:56:09.2930015Z --- Parse Warning: 102 / 146 --- 2025-08-26T19:56:09.2930898Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=calculate_gain in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/init.py line=142. 2025-08-26T19:56:09.2931169Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2931402Z Return the recommended gain value for the given nonlinearity function. 2025-08-26T19:56:09.2931499Z 2025-08-26T19:56:09.2931604Z The values are as follows: 2025-08-26T19:56:09.2931696Z 2025-08-26T19:56:09.2931814Z ================= ==================================================== 2025-08-26T19:56:09.2931917Z nonlinearity gain 2025-08-26T19:56:09.2932044Z ================= ==================================================== 2025-08-26T19:56:09.2932149Z Linear / Identity :math:`1` 2025-08-26T19:56:09.2932257Z Conv{1,2,3}D :math:`1` 2025-08-26T19:56:09.2932356Z Sigmoid :math:`1` 2025-08-26T19:56:09.2932466Z Tanh :math:`\frac{5}{3}` 2025-08-26T19:56:09.2932583Z ReLU :math:`\sqrt{2}` 2025-08-26T19:56:09.2932780Z Leaky Relu :math:`\sqrt{\frac{2}{1 + \text{negative\_slope}^2}}` 2025-08-26T19:56:09.2932900Z SELU :math:`\frac{3}{4}` 2025-08-26T19:56:09.2933014Z ================= ==================================================== 2025-08-26T19:56:09.2933097Z 2025-08-26T19:56:09.2933202Z .. warning:: 2025-08-26T19:56:09.2933394Z In order to implement `Self-Normalizing Neural Networks`_ , 2025-08-26T19:56:09.2933654Z you should use ``nonlinearity='linear'`` instead of ``nonlinearity='selu'``. 2025-08-26T19:56:09.2933823Z This gives the initial weights a variance of ``1 / N``, 2025-08-26T19:56:09.2934051Z which is necessary to induce a stable fixed point in the forward pass. 2025-08-26T19:56:09.2934335Z In contrast, the default gain for ``SELU`` sacrifices the normalization 2025-08-26T19:56:09.2934526Z effect for more stable gradient flow in rectangular layers. 2025-08-26T19:56:09.2934623Z 2025-08-26T19:56:09.2934709Z Args: 2025-08-26T19:56:09.2934910Z nonlinearity: the non-linear function (`nn.functional` name) 2025-08-26T19:56:09.2935099Z param: optional parameter for the non-linear function 2025-08-26T19:56:09.2935182Z 2025-08-26T19:56:09.2935279Z Examples: 2025-08-26T19:56:09.2935398Z >>> gain = nn.init.calculate_gain( 2025-08-26T19:56:09.2935504Z ... "leaky_relu", 0.2 2025-08-26T19:56:09.2935643Z ... ) # leaky_relu with negative_slope=0.2 2025-08-26T19:56:09.2935724Z 2025-08-26T19:56:09.2936223Z .. _Self-Normalizing Neural Networks: https://papers.nips.cc/paper/2017/hash/5d44ee6f2c3f71b73125876103c8f6c4-Abstract.html 2025-08-26T19:56:09.2936308Z 2025-08-26T19:56:09.2936569Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2936683Z 2025-08-26T19:56:09.2936783Z warnings.warn(msg) 2025-08-26T19:56:09.2936860Z 2025-08-26T19:56:09.2937060Z --- Parse Warning: 103 / 146 --- 2025-08-26T19:56:09.2938797Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=603. 2025-08-26T19:56:09.2939146Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2939330Z Applies Batch Normalization over a N-Dimensional input. 2025-08-26T19:56:09.2939417Z 2025-08-26T19:56:09.2939770Z The N-D input is a mini-batch of [N-2]D inputs with additional channel dimension) as described in the paper 2025-08-26T19:56:09.2940038Z `Batch Normalization: Accelerating Deep Network Training by Reducing 2025-08-26T19:56:09.2940263Z Internal Covariate Shift `__ . 2025-08-26T19:56:09.2940342Z 2025-08-26T19:56:09.2940441Z .. math:: 2025-08-26T19:56:09.2940522Z 2025-08-26T19:56:09.2940741Z y = \frac{x - \mathrm{E}[x]}{ \sqrt{\mathrm{Var}[x] + \epsilon}} * \gamma + \beta 2025-08-26T19:56:09.2940832Z 2025-08-26T19:56:09.2941062Z The mean and standard-deviation are calculated per-dimension over all 2025-08-26T19:56:09.2941309Z mini-batches of the same process groups. :math:`\gamma` and :math:`\beta` 2025-08-26T19:56:09.2941556Z are learnable parameter vectors of size `C` (where `C` is the input size). 2025-08-26T19:56:09.2941733Z By default, the elements of :math:`\gamma` are sampled from 2025-08-26T19:56:09.2941942Z :math:`\mathcal{U}(0, 1)` and the elements of :math:`\beta` are set to 0. 2025-08-26T19:56:09.2942203Z The standard-deviation is calculated via the biased estimator, equivalent to 2025-08-26T19:56:09.2942333Z `torch.var(input, unbiased=False)`. 2025-08-26T19:56:09.2942419Z 2025-08-26T19:56:09.2942655Z Also by default, during training this layer keeps running estimates of its 2025-08-26T19:56:09.2942902Z computed mean and variance, which are then used for normalization during 2025-08-26T19:56:09.2943148Z evaluation. The running estimates are kept with a default :attr:`momentum` 2025-08-26T19:56:09.2943244Z of 0.1. 2025-08-26T19:56:09.2943324Z 2025-08-26T19:56:09.2943550Z If :attr:`track_running_stats` is set to ``False``, this layer then does not 2025-08-26T19:56:09.2943780Z keep running estimates, and batch statistics are instead used during 2025-08-26T19:56:09.2943885Z evaluation time as well. 2025-08-26T19:56:09.2943974Z 2025-08-26T19:56:09.2944060Z .. note:: 2025-08-26T19:56:09.2944283Z This :attr:`momentum` argument is different from one used in optimizer 2025-08-26T19:56:09.2944561Z classes and the conventional notion of momentum. Mathematically, the 2025-08-26T19:56:09.2944701Z update rule for running statistics here is 2025-08-26T19:56:09.2944977Z :math:`\hat{x}_\text{new} = (1 - \text{momentum}) \times \hat{x} + \text{momentum} \times x_t`, 2025-08-26T19:56:09.2945184Z where :math:`\hat{x}` is the estimated statistic and :math:`x_t` is the 2025-08-26T19:56:09.2945285Z new observed value. 2025-08-26T19:56:09.2945373Z 2025-08-26T19:56:09.2945680Z Because the Batch Normalization is done for each channel in the ``C`` dimension, computing 2025-08-26T19:56:09.2945943Z statistics on ``(N, +)`` slices, it's common terminology to call this Volumetric Batch 2025-08-26T19:56:09.2946124Z Normalization or Spatio-temporal Batch Normalization. 2025-08-26T19:56:09.2946207Z 2025-08-26T19:56:09.2946361Z Currently :class:`SyncBatchNorm` only supports 2025-08-26T19:56:09.2946650Z :class:`~torch.nn.DistributedDataParallel` (DDP) with single GPU per process. Use 2025-08-26T19:56:09.2946907Z :meth:`torch.nn.SyncBatchNorm.convert_sync_batchnorm()` to convert 2025-08-26T19:56:09.2947116Z :attr:`BatchNorm*D` layer to :class:`SyncBatchNorm` before wrapping 2025-08-26T19:56:09.2947213Z Network with DDP. 2025-08-26T19:56:09.2947298Z 2025-08-26T19:56:09.2947385Z Args: 2025-08-26T19:56:09.2947566Z num_features: :math:`C` from an expected input of size 2025-08-26T19:56:09.2947662Z :math:`(N, C, +)` 2025-08-26T19:56:09.2947877Z eps: a value added to the denominator for numerical stability. 2025-08-26T19:56:09.2947985Z Default: ``1e-5`` 2025-08-26T19:56:09.2948180Z momentum: the value used for the running_mean and running_var 2025-08-26T19:56:09.2948404Z computation. Can be set to ``None`` for cumulative moving average 2025-08-26T19:56:09.2948553Z (i.e. simple average). Default: 0.1 2025-08-26T19:56:09.2948761Z affine: a boolean value that when set to ``True``, this module has 2025-08-26T19:56:09.2948924Z learnable affine parameters. Default: ``True`` 2025-08-26T19:56:09.2949140Z track_running_stats: a boolean value that when set to ``True``, this 2025-08-26T19:56:09.2949379Z module tracks the running mean and variance, and when set to ``False``, 2025-08-26T19:56:09.2949601Z this module does not track such statistics, and initializes statistics 2025-08-26T19:56:09.2949806Z buffers :attr:`running_mean` and :attr:`running_var` as ``None``. 2025-08-26T19:56:09.2950044Z When these buffers are ``None``, this module always uses batch statistics. 2025-08-26T19:56:09.2950197Z in both training and eval modes. Default: ``True`` 2025-08-26T19:56:09.2950456Z process_group: synchronization of stats happen within each process group 2025-08-26T19:56:09.2950686Z individually. Default behavior is synchronization across the whole 2025-08-26T19:56:09.2950784Z world 2025-08-26T19:56:09.2950861Z 2025-08-26T19:56:09.2950946Z Shape: 2025-08-26T19:56:09.2951062Z - Input: :math:`(N, C, +)` 2025-08-26T19:56:09.2951210Z - Output: :math:`(N, C, +)` (same shape as input) 2025-08-26T19:56:09.2951290Z 2025-08-26T19:56:09.2951383Z .. note:: 2025-08-26T19:56:09.2951631Z Synchronization of batchnorm statistics occurs only while training, i.e. 2025-08-26T19:56:09.2951848Z synchronization is disabled when ``model.eval()`` is set or if 2025-08-26T19:56:09.2951978Z ``self.training`` is otherwise ``False``. 2025-08-26T19:56:09.2952060Z 2025-08-26T19:56:09.2952156Z Examples:: 2025-08-26T19:56:09.2952236Z 2025-08-26T19:56:09.2952346Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.2952462Z >>> # With Learnable Parameters 2025-08-26T19:56:09.2952602Z >>> m = nn.SyncBatchNorm(100) 2025-08-26T19:56:09.2952739Z >>> # creating process group (optional) 2025-08-26T19:56:09.2952880Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T19:56:09.2952993Z >>> ranks = list(range(8)) 2025-08-26T19:56:09.2953097Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T19:56:09.2953248Z >>> # Note: every rank calls into new_group for every 2025-08-26T19:56:09.2953408Z >>> # process group created, even if that rank is not 2025-08-26T19:56:09.2953510Z >>> # part of the group. 2025-08-26T19:56:09.2953776Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T19:56:09.2953978Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T19:56:09.2954095Z >>> # Without Learnable Parameters 2025-08-26T19:56:09.2954309Z >>> m = nn.BatchNorm3d(100, affine=False, process_group=process_group) 2025-08-26T19:56:09.2954438Z >>> input = torch.randn(20, 100, 35, 45, 10) 2025-08-26T19:56:09.2954575Z >>> output = m(input) 2025-08-26T19:56:09.2954654Z 2025-08-26T19:56:09.2954771Z >>> # network is nn.BatchNorm layer 2025-08-26T19:56:09.2955057Z >>> sync_bn_network = nn.SyncBatchNorm.convert_sync_batchnorm(network, process_group) 2025-08-26T19:56:09.2955222Z >>> # only single gpu per process is currently supported 2025-08-26T19:56:09.2955452Z >>> ddp_sync_bn_network = torch.nn.parallel.DistributedDataParallel( 2025-08-26T19:56:09.2955591Z >>> sync_bn_network, 2025-08-26T19:56:09.2955720Z >>> device_ids=[args.local_rank], 2025-08-26T19:56:09.2955856Z >>> output_device=args.local_rank) 2025-08-26T19:56:09.2955936Z 2025-08-26T19:56:09.2956230Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2956313Z 2025-08-26T19:56:09.2956410Z warnings.warn(msg) 2025-08-26T19:56:09.2956494Z 2025-08-26T19:56:09.2956710Z --- Parse Warning: 104 / 146 --- 2025-08-26T19:56:09.2957764Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyncBatchNorm.convert_sync_batchnorm in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/batchnorm.py line=830. 2025-08-26T19:56:09.2958031Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2958345Z Converts all :attr:`BatchNorm*D` layers in the model to :class:`torch.nn.SyncBatchNorm` layers. 2025-08-26T19:56:09.2958437Z 2025-08-26T19:56:09.2958523Z Args: 2025-08-26T19:56:09.2958786Z module (nn.Module): module containing one or more :attr:`BatchNorm*D` layers 2025-08-26T19:56:09.2959009Z process_group (optional): process group to scope synchronization, 2025-08-26T19:56:09.2959126Z default is the whole world 2025-08-26T19:56:09.2959218Z 2025-08-26T19:56:09.2959302Z Returns: 2025-08-26T19:56:09.2959569Z The original :attr:`module` with the converted :class:`torch.nn.SyncBatchNorm` 2025-08-26T19:56:09.2959781Z layers. If the original :attr:`module` is a :attr:`BatchNorm*D` layer, 2025-08-26T19:56:09.2959987Z a new :class:`torch.nn.SyncBatchNorm` layer object will be returned 2025-08-26T19:56:09.2960088Z instead. 2025-08-26T19:56:09.2960169Z 2025-08-26T19:56:09.2960275Z Example:: 2025-08-26T19:56:09.2960354Z 2025-08-26T19:56:09.2960478Z >>> # Network with nn.BatchNorm layer 2025-08-26T19:56:09.2960630Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:09.2960751Z >>> module = torch.nn.Sequential( 2025-08-26T19:56:09.2960886Z >>> torch.nn.Linear(20, 100), 2025-08-26T19:56:09.2961042Z >>> torch.nn.BatchNorm1d(100), 2025-08-26T19:56:09.2961136Z >>> ).cuda() 2025-08-26T19:56:09.2961273Z >>> # creating process group (optional) 2025-08-26T19:56:09.2961415Z >>> # ranks is a list of int identifying rank ids. 2025-08-26T19:56:09.2961539Z >>> ranks = list(range(8)) 2025-08-26T19:56:09.2961645Z >>> r1, r2 = ranks[:4], ranks[4:] 2025-08-26T19:56:09.2961793Z >>> # Note: every rank calls into new_group for every 2025-08-26T19:56:09.2961961Z >>> # process group created, even if that rank is not 2025-08-26T19:56:09.2962064Z >>> # part of the group. 2025-08-26T19:56:09.2962200Z >>> # xdoctest: +SKIP("distributed") 2025-08-26T19:56:09.2962449Z >>> process_groups = [torch.distributed.new_group(pids) for pids in [r1, r2]] 2025-08-26T19:56:09.2962659Z >>> process_group = process_groups[0 if dist.get_rank() <= 3 else 1] 2025-08-26T19:56:09.2962996Z >>> sync_bn_module = torch.nn.SyncBatchNorm.convert_sync_batchnorm(module, process_group) 2025-08-26T19:56:09.2963073Z 2025-08-26T19:56:09.2963166Z 2025-08-26T19:56:09.2963418Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2963495Z 2025-08-26T19:56:09.2963605Z warnings.warn(msg) 2025-08-26T19:56:09.2963684Z 2025-08-26T19:56:09.2963891Z --- Parse Warning: 105 / 146 --- 2025-08-26T19:56:09.2964814Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Unflatten in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/flatten.py line=66. 2025-08-26T19:56:09.2965081Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2965173Z 2025-08-26T19:56:09.2965538Z Unflattens a tensor dim expanding it to a desired shape. For use with :class:`~nn.Sequential`. 2025-08-26T19:56:09.2965630Z 2025-08-26T19:56:09.2965901Z * :attr:`dim` specifies the dimension of the input tensor to be unflattened, and it can 2025-08-26T19:56:09.2966127Z be either `int` or `str` when `Tensor` or `NamedTensor` is used, respectively. 2025-08-26T19:56:09.2966215Z 2025-08-26T19:56:09.2966532Z * :attr:`unflattened_size` is the new shape of the unflattened dimension of the tensor and it can be 2025-08-26T19:56:09.2966797Z a `tuple` of ints or a `list` of ints or `torch.Size` for `Tensor` input; a `NamedShape` 2025-08-26T19:56:09.2966967Z (tuple of `(name, size)` tuples) for `NamedTensor` input. 2025-08-26T19:56:09.2967044Z 2025-08-26T19:56:09.2967141Z Shape: 2025-08-26T19:56:09.2967354Z - Input: :math:`(*, S_{\text{dim}}, *)`, where :math:`S_{\text{dim}}` is the size at 2025-08-26T19:56:09.2967620Z dimension :attr:`dim` and :math:`*` means any number of dimensions including none. 2025-08-26T19:56:09.2967845Z - Output: :math:`(*, U_1, ..., U_n, *)`, where :math:`U` = :attr:`unflattened_size` and 2025-08-26T19:56:09.2967974Z :math:`\prod_{i=1}^n U_i = S_{\text{dim}}`. 2025-08-26T19:56:09.2968065Z 2025-08-26T19:56:09.2968147Z Args: 2025-08-26T19:56:09.2968311Z dim (Union[int, str]): Dimension to be unflattened 2025-08-26T19:56:09.2968663Z unflattened_size (Union[torch.Size, Tuple, List, NamedShape]): New shape of the unflattened dimension 2025-08-26T19:56:09.2968743Z 2025-08-26T19:56:09.2968925Z Examples: 2025-08-26T19:56:09.2969035Z >>> input = torch.randn(2, 50) 2025-08-26T19:56:09.2969145Z >>> # With tuple of ints 2025-08-26T19:56:09.2969242Z >>> m = nn.Sequential( 2025-08-26T19:56:09.2969337Z >>> nn.Linear(50, 50), 2025-08-26T19:56:09.2969456Z >>> nn.Unflatten(1, (2, 5, 5)) 2025-08-26T19:56:09.2969537Z >>> ) 2025-08-26T19:56:09.2969675Z >>> output = m(input) 2025-08-26T19:56:09.2969769Z >>> output.size() 2025-08-26T19:56:09.2969862Z torch.Size([2, 2, 5, 5]) 2025-08-26T19:56:09.2969970Z >>> # With torch.Size 2025-08-26T19:56:09.2970065Z >>> m = nn.Sequential( 2025-08-26T19:56:09.2970157Z >>> nn.Linear(50, 50), 2025-08-26T19:56:09.2970288Z >>> nn.Unflatten(1, torch.Size([2, 5, 5])) 2025-08-26T19:56:09.2970368Z >>> ) 2025-08-26T19:56:09.2970475Z >>> output = m(input) 2025-08-26T19:56:09.2970566Z >>> output.size() 2025-08-26T19:56:09.2970663Z torch.Size([2, 2, 5, 5]) 2025-08-26T19:56:09.2970795Z >>> # With namedshape (tuple of tuples) 2025-08-26T19:56:09.2970942Z >>> input = torch.randn(2, 50, names=("N", "features")) 2025-08-26T19:56:09.2971158Z >>> unflatten = nn.Unflatten("features", (("C", 2), ("H", 5), ("W", 5))) 2025-08-26T19:56:09.2971265Z >>> output = unflatten(input) 2025-08-26T19:56:09.2971362Z >>> output.size() 2025-08-26T19:56:09.2971491Z torch.Size([2, 2, 5, 5]) 2025-08-26T19:56:09.2971569Z 2025-08-26T19:56:09.2971835Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.2971909Z 2025-08-26T19:56:09.2972007Z warnings.warn(msg) 2025-08-26T19:56:09.2972095Z 2025-08-26T19:56:09.2972301Z --- Parse Warning: 106 / 146 --- 2025-08-26T19:56:09.2973351Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=TripletMarginWithDistanceLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1798. 2025-08-26T19:56:09.2973615Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2973815Z Creates a criterion that measures the triplet loss given input 2025-08-26T19:56:09.2974044Z tensors :math:`a`, :math:`p`, and :math:`n` (representing anchor, 2025-08-26T19:56:09.2974261Z positive, and negative examples, respectively), and a nonnegative, 2025-08-26T19:56:09.2974528Z real-valued function ("distance function") used to compute the relationship 2025-08-26T19:56:09.2974747Z between the anchor and positive example ("positive distance") and the 2025-08-26T19:56:09.2974904Z anchor and negative example ("negative distance"). 2025-08-26T19:56:09.2974994Z 2025-08-26T19:56:09.2975200Z The unreduced loss (i.e., with :attr:`reduction` set to ``'none'``) 2025-08-26T19:56:09.2975310Z can be described as: 2025-08-26T19:56:09.2975388Z 2025-08-26T19:56:09.2975476Z .. math:: 2025-08-26T19:56:09.2975627Z \ell(a, p, n) = L = \{l_1,\dots,l_N\}^\top, \quad 2025-08-26T19:56:09.2975779Z l_i = \max \{d(a_i, p_i) - d(a_i, n_i) + {\rm margin}, 0\} 2025-08-26T19:56:09.2975873Z 2025-08-26T19:56:09.2976120Z where :math:`N` is the batch size; :math:`d` is a nonnegative, real-valued function 2025-08-26T19:56:09.2976415Z quantifying the closeness of two tensors, referred to as the :attr:`distance_function`; 2025-08-26T19:56:09.2976670Z and :math:`margin` is a nonnegative margin representing the minimum difference 2025-08-26T19:56:09.2976916Z between the positive and negative distances that is required for the loss to 2025-08-26T19:56:09.2977158Z be 0. The input tensors have :math:`N` elements each and can be of any shape 2025-08-26T19:56:09.2977277Z that the distance function can handle. 2025-08-26T19:56:09.2977354Z 2025-08-26T19:56:09.2977484Z If :attr:`reduction` is not ``'none'`` 2025-08-26T19:56:09.2977581Z (default ``'mean'``), then: 2025-08-26T19:56:09.2977678Z 2025-08-26T19:56:09.2977765Z .. math:: 2025-08-26T19:56:09.2977854Z \ell(x, y) = 2025-08-26T19:56:09.2977958Z \begin{cases} 2025-08-26T19:56:09.2978160Z \operatorname{mean}(L), & \text{if reduction} = \text{`mean';}\\ 2025-08-26T19:56:09.2978393Z \operatorname{sum}(L), & \text{if reduction} = \text{`sum'.} 2025-08-26T19:56:09.2978484Z \end{cases} 2025-08-26T19:56:09.2978567Z 2025-08-26T19:56:09.2978813Z See also :class:`~torch.nn.TripletMarginLoss`, which computes the triplet 2025-08-26T19:56:09.2979062Z loss for input tensors using the :math:`l_p` distance as the distance function. 2025-08-26T19:56:09.2979151Z 2025-08-26T19:56:09.2979232Z Args: 2025-08-26T19:56:09.2979507Z distance_function (Callable, optional): A nonnegative, real-valued function that 2025-08-26T19:56:09.2979709Z quantifies the closeness of two tensors. If not specified, 2025-08-26T19:56:09.2979877Z `nn.PairwiseDistance` will be used. Default: ``None`` 2025-08-26T19:56:09.2980158Z margin (float, optional): A nonnegative margin representing the minimum difference 2025-08-26T19:56:09.2980432Z between the positive and negative distances required for the loss to be 0. Larger 2025-08-26T19:56:09.2980744Z margins penalize cases where the negative examples are not distant enough from the 2025-08-26T19:56:09.2980931Z anchors, relative to the positives. Default: :math:`1`. 2025-08-26T19:56:09.2981178Z swap (bool, optional): Whether to use the distance swap described in the paper 2025-08-26T19:56:09.2981449Z `Learning shallow convolutional feature descriptors with triplet losses` by 2025-08-26T19:56:09.2981713Z V. Balntas, E. Riba et al. If True, and if the positive example is closer to the 2025-08-26T19:56:09.2981987Z negative example than the anchor is, swaps the positive example and the anchor in 2025-08-26T19:56:09.2982131Z the loss computation. Default: ``False``. 2025-08-26T19:56:09.2982413Z reduction (str, optional): Specifies the (optional) reduction to apply to the output: 2025-08-26T19:56:09.2982637Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T19:56:09.2982820Z ``'mean'``: the sum of the output will be divided by the number of 2025-08-26T19:56:09.2983071Z elements in the output, ``'sum'``: the output will be summed. Default: ``'mean'`` 2025-08-26T19:56:09.2983151Z 2025-08-26T19:56:09.2983233Z 2025-08-26T19:56:09.2983328Z Shape: 2025-08-26T19:56:09.2983571Z - Input: :math:`(N, *)` where :math:`*` represents any number of additional dimensions 2025-08-26T19:56:09.2983718Z as supported by the distance function. 2025-08-26T19:56:09.2983969Z - Output: A Tensor of shape :math:`(N)` if :attr:`reduction` is ``'none'``, or a scalar 2025-08-26T19:56:09.2984059Z otherwise. 2025-08-26T19:56:09.2984151Z 2025-08-26T19:56:09.2984235Z Examples: 2025-08-26T19:56:09.2984313Z 2025-08-26T19:56:09.2984429Z >>> # Initialize embeddings 2025-08-26T19:56:09.2984551Z >>> embedding = nn.Embedding(1000, 128) 2025-08-26T19:56:09.2984691Z >>> anchor_ids = torch.randint(0, 1000, (1,)) 2025-08-26T19:56:09.2984822Z >>> positive_ids = torch.randint(0, 1000, (1,)) 2025-08-26T19:56:09.2984950Z >>> negative_ids = torch.randint(0, 1000, (1,)) 2025-08-26T19:56:09.2985072Z >>> anchor = embedding(anchor_ids) 2025-08-26T19:56:09.2985192Z >>> positive = embedding(positive_ids) 2025-08-26T19:56:09.2985317Z >>> negative = embedding(negative_ids) 2025-08-26T19:56:09.2985397Z >>> 2025-08-26T19:56:09.2985509Z >>> # Built-in Distance Function 2025-08-26T19:56:09.2985616Z >>> triplet_loss = \ 2025-08-26T19:56:09.2985898Z >>> nn.TripletMarginWithDistanceLoss(distance_function=nn.PairwiseDistance()) 2025-08-26T19:56:09.2986063Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T19:56:09.2986164Z >>> output.backward() 2025-08-26T19:56:09.2986275Z >>> 2025-08-26T19:56:09.2986390Z >>> # Custom Distance Function 2025-08-26T19:56:09.2986493Z >>> def l_infinity(x1, x2): 2025-08-26T19:56:09.2986657Z >>> return torch.max(torch.abs(x1 - x2), dim=1).values 2025-08-26T19:56:09.2986737Z >>> 2025-08-26T19:56:09.2986927Z >>> # xdoctest: +SKIP("FIXME: Would call backwards a second time") 2025-08-26T19:56:09.2987032Z >>> triplet_loss = ( 2025-08-26T19:56:09.2987318Z >>> nn.TripletMarginWithDistanceLoss(distance_function=l_infinity, margin=1.5)) 2025-08-26T19:56:09.2987484Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T19:56:09.2987584Z >>> output.backward() 2025-08-26T19:56:09.2987668Z >>> 2025-08-26T19:56:09.2987796Z >>> # Custom Distance Function (Lambda) 2025-08-26T19:56:09.2987893Z >>> triplet_loss = ( 2025-08-26T19:56:09.2988032Z >>> nn.TripletMarginWithDistanceLoss( 2025-08-26T19:56:09.2988254Z >>> distance_function=lambda x, y: 1.0 - F.cosine_similarity(x, y))) 2025-08-26T19:56:09.2988436Z >>> output = triplet_loss(anchor, positive, negative) 2025-08-26T19:56:09.2988542Z >>> output.backward() 2025-08-26T19:56:09.2988621Z 2025-08-26T19:56:09.2988710Z Reference: 2025-08-26T19:56:09.2989024Z V. Balntas, et al.: Learning shallow convolutional feature descriptors with triplet losses: 2025-08-26T19:56:09.2989249Z https://bmva-archive.org.uk/bmvc/2016/papers/paper119/index.html 2025-08-26T19:56:09.2989338Z 2025-08-26T19:56:09.2989623Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 17)) 2025-08-26T19:56:09.2989702Z 2025-08-26T19:56:09.2989806Z warnings.warn(msg) 2025-08-26T19:56:09.2989883Z 2025-08-26T19:56:09.2990094Z --- Parse Warning: 107 / 146 --- 2025-08-26T19:56:09.2991005Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CTCLoss in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/loss.py line=1933. 2025-08-26T19:56:09.2991284Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.2991434Z The Connectionist Temporal Classification loss. 2025-08-26T19:56:09.2991513Z 2025-08-26T19:56:09.2991907Z Calculates loss between a continuous (unsegmented) time series and a target sequence. CTCLoss sums over the 2025-08-26T19:56:09.2992270Z probability of possible alignments of input to target, producing a loss value which is differentiable 2025-08-26T19:56:09.2992623Z with respect to each input node. The alignment of input to target is assumed to be "many-to-one", which 2025-08-26T19:56:09.2992926Z limits the length of the target sequence such that it must be :math:`\leq` the input length. 2025-08-26T19:56:09.2993008Z 2025-08-26T19:56:09.2993102Z Args: 2025-08-26T19:56:09.2993270Z blank (int, optional): blank label. Default :math:`0`. 2025-08-26T19:56:09.2993525Z reduction (str, optional): Specifies the reduction to apply to the output: 2025-08-26T19:56:09.2993710Z ``'none'`` | ``'mean'`` | ``'sum'``. ``'none'``: no reduction will be applied, 2025-08-26T19:56:09.2993921Z ``'mean'``: the output losses will be divided by the target lengths and 2025-08-26T19:56:09.2994183Z then the mean over the batch is taken, ``'sum'``: the output losses will be summed. 2025-08-26T19:56:09.2994281Z Default: ``'mean'`` 2025-08-26T19:56:09.2994405Z zero_infinity (bool, optional): 2025-08-26T19:56:09.2994604Z Whether to zero infinite losses and the associated gradients. 2025-08-26T19:56:09.2994705Z Default: ``False`` 2025-08-26T19:56:09.2994901Z Infinite losses mainly occur when the inputs are too short 2025-08-26T19:56:09.2995015Z to be aligned to the targets. 2025-08-26T19:56:09.2995136Z 2025-08-26T19:56:09.2995223Z Shape: 2025-08-26T19:56:09.2995414Z - Log_probs: Tensor of size :math:`(T, N, C)` or :math:`(T, C)`, 2025-08-26T19:56:09.2995548Z where :math:`T = \text{input length}`, 2025-08-26T19:56:09.2995665Z :math:`N = \text{batch size}`, and 2025-08-26T19:56:09.2995834Z :math:`C = \text{number of classes (including blank)}`. 2025-08-26T19:56:09.2996061Z The logarithmized probabilities of the outputs (e.g. obtained with 2025-08-26T19:56:09.2996201Z :func:`torch.nn.functional.log_softmax`). 2025-08-26T19:56:09.2996338Z - Targets: Tensor of size :math:`(N, S)` or 2025-08-26T19:56:09.2996495Z :math:`(\operatorname{sum}(\text{target\_lengths}))`, 2025-08-26T19:56:09.2996631Z where :math:`N = \text{batch size}` and 2025-08-26T19:56:09.2996794Z :math:`S = \text{max target length, if shape is } (N, S)`. 2025-08-26T19:56:09.2996998Z It represents the target sequences. Each element in the target 2025-08-26T19:56:09.2997275Z sequence is a class index. And the target index cannot be blank (default=0). 2025-08-26T19:56:09.2997432Z In the :math:`(N, S)` form, targets are padded to the 2025-08-26T19:56:09.2997580Z length of the longest sequence, and stacked. 2025-08-26T19:56:09.2997772Z In the :math:`(\operatorname{sum}(\text{target\_lengths}))` form, 2025-08-26T19:56:09.2997910Z the targets are assumed to be un-padded and 2025-08-26T19:56:09.2998092Z concatenated within 1 dimension. 2025-08-26T19:56:09.2998303Z - Input_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T19:56:09.2998520Z where :math:`N = \text{batch size}`. It represents the lengths of the 2025-08-26T19:56:09.2998726Z inputs (must each be :math:`\leq T`). And the lengths are specified 2025-08-26T19:56:09.2999006Z for each sequence to achieve masking under the assumption that sequences 2025-08-26T19:56:09.2999126Z are padded to equal lengths. 2025-08-26T19:56:09.2999337Z - Target_lengths: Tuple or tensor of size :math:`(N)` or :math:`()`, 2025-08-26T19:56:09.2999571Z where :math:`N = \text{batch size}`. It represents lengths of the targets. 2025-08-26T19:56:09.2999796Z Lengths are specified for each sequence to achieve masking under the 2025-08-26T19:56:09.3000060Z assumption that sequences are padded to equal lengths. If target shape is 2025-08-26T19:56:09.3000236Z :math:`(N,S)`, target_lengths are effectively the stop index 2025-08-26T19:56:09.3000495Z :math:`s_n` for each target sequence, such that ``target_n = targets[n,0:s_n]`` for 2025-08-26T19:56:09.3000690Z each target in a batch. Lengths must each be :math:`\leq S` 2025-08-26T19:56:09.3000941Z If the targets are given as a 1d tensor that is the concatenation of individual 2025-08-26T19:56:09.3001201Z targets, the target_lengths must add up to the total length of the tensor. 2025-08-26T19:56:09.3001398Z - Output: scalar if :attr:`reduction` is ``'mean'`` (default) or 2025-08-26T19:56:09.3001635Z ``'sum'``. If :attr:`reduction` is ``'none'``, then :math:`(N)` if input is batched or 2025-08-26T19:56:09.3001850Z :math:`()` if input is unbatched, where :math:`N = \text{batch size}`. 2025-08-26T19:56:09.3001932Z 2025-08-26T19:56:09.3002037Z Examples: 2025-08-26T19:56:09.3002120Z 2025-08-26T19:56:09.3002235Z >>> # Target are to be padded 2025-08-26T19:56:09.3002366Z >>> T = 50 # Input sequence length 2025-08-26T19:56:09.3002503Z >>> C = 20 # Number of classes (including blank) 2025-08-26T19:56:09.3002612Z >>> N = 16 # Batch size 2025-08-26T19:56:09.3002848Z >>> S = 30 # Target sequence length of longest target in batch (padding length) 2025-08-26T19:56:09.3003064Z >>> S_min = 10 # Minimum target length, for demonstration purposes 2025-08-26T19:56:09.3003165Z >>> 2025-08-26T19:56:09.3003369Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T19:56:09.3003595Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T19:56:09.3003679Z >>> 2025-08-26T19:56:09.3003878Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T19:56:09.3004112Z >>> target = torch.randint(low=1, high=C, size=(N, S), dtype=torch.long) 2025-08-26T19:56:09.3004196Z >>> 2025-08-26T19:56:09.3004430Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T19:56:09.3004550Z >>> target_lengths = torch.randint( 2025-08-26T19:56:09.3004647Z ... low=S_min, 2025-08-26T19:56:09.3004759Z ... high=S, 2025-08-26T19:56:09.3004854Z ... size=(N,), 2025-08-26T19:56:09.3005004Z ... dtype=torch.long, 2025-08-26T19:56:09.3005088Z ... ) 2025-08-26T19:56:09.3005193Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T19:56:09.3005391Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T19:56:09.3005490Z >>> loss.backward() 2025-08-26T19:56:09.3005584Z >>> 2025-08-26T19:56:09.3005666Z >>> 2025-08-26T19:56:09.3005780Z >>> # Target are to be un-padded 2025-08-26T19:56:09.3005938Z >>> T = 50 # Input sequence length 2025-08-26T19:56:09.3006077Z >>> C = 20 # Number of classes (including blank) 2025-08-26T19:56:09.3006186Z >>> N = 16 # Batch size 2025-08-26T19:56:09.3006268Z >>> 2025-08-26T19:56:09.3006471Z >>> # Initialize random batch of input vectors, for *size = (T,N,C) 2025-08-26T19:56:09.3006719Z >>> input = torch.randn(T, N, C).log_softmax(2).detach().requires_grad_() 2025-08-26T19:56:09.3006944Z >>> input_lengths = torch.full(size=(N,), fill_value=T, dtype=torch.long) 2025-08-26T19:56:09.3007037Z >>> 2025-08-26T19:56:09.3007236Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T19:56:09.3007477Z >>> target_lengths = torch.randint(low=1, high=T, size=(N,), dtype=torch.long) 2025-08-26T19:56:09.3007595Z >>> target = torch.randint( 2025-08-26T19:56:09.3007683Z ... low=1, 2025-08-26T19:56:09.3007784Z ... high=C, 2025-08-26T19:56:09.3007903Z ... size=(sum(target_lengths),), 2025-08-26T19:56:09.3008006Z ... dtype=torch.long, 2025-08-26T19:56:09.3008103Z ... ) 2025-08-26T19:56:09.3008206Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T19:56:09.3008395Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T19:56:09.3008515Z >>> loss.backward() 2025-08-26T19:56:09.3008597Z >>> 2025-08-26T19:56:09.3008689Z >>> 2025-08-26T19:56:09.3008982Z >>> # Target are to be un-padded and unbatched (effectively N=1) 2025-08-26T19:56:09.3009096Z >>> T = 50 # Input sequence length 2025-08-26T19:56:09.3009247Z >>> C = 20 # Number of classes (including blank) 2025-08-26T19:56:09.3009332Z >>> 2025-08-26T19:56:09.3009541Z >>> # Initialize random batch of input vectors, for *size = (T,C) 2025-08-26T19:56:09.3009679Z >>> # xdoctest: +SKIP("FIXME: error in doctest") 2025-08-26T19:56:09.3009884Z >>> input = torch.randn(T, C).log_softmax(1).detach().requires_grad_() 2025-08-26T19:56:09.3010052Z >>> input_lengths = torch.tensor(T, dtype=torch.long) 2025-08-26T19:56:09.3010135Z >>> 2025-08-26T19:56:09.3010342Z >>> # Initialize random batch of targets (0 = blank, 1:C = classes) 2025-08-26T19:56:09.3010616Z >>> target_lengths = torch.randint(low=1, high=T, size=(), dtype=torch.long) 2025-08-26T19:56:09.3010723Z >>> target = torch.randint( 2025-08-26T19:56:09.3010825Z ... low=1, 2025-08-26T19:56:09.3010910Z ... high=C, 2025-08-26T19:56:09.3011032Z ... size=(target_lengths,), 2025-08-26T19:56:09.3011137Z ... dtype=torch.long, 2025-08-26T19:56:09.3011220Z ... ) 2025-08-26T19:56:09.3011335Z >>> ctc_loss = nn.CTCLoss() 2025-08-26T19:56:09.3011518Z >>> loss = ctc_loss(input, target, input_lengths, target_lengths) 2025-08-26T19:56:09.3011626Z >>> loss.backward() 2025-08-26T19:56:09.3011711Z 2025-08-26T19:56:09.3011801Z Reference: 2025-08-26T19:56:09.3011992Z A. Graves et al.: Connectionist Temporal Classification: 2025-08-26T19:56:09.3012228Z Labelling Unsegmented Sequence Data with Recurrent Neural Networks: 2025-08-26T19:56:09.3012410Z https://www.cs.toronto.edu/~graves/icml_2006.pdf 2025-08-26T19:56:09.3012522Z 2025-08-26T19:56:09.3012607Z Note: 2025-08-26T19:56:09.3012867Z In order to use CuDNN, the following must be satisfied: :attr:`targets` must be 2025-08-26T19:56:09.3013125Z in concatenated format, all :attr:`input_lengths` must be `T`. :math:`blank=0`, 2025-08-26T19:56:09.3013359Z :attr:`target_lengths` :math:`\leq 256`, the integer arguments must be of 2025-08-26T19:56:09.3013471Z dtype :attr:`torch.int32`. 2025-08-26T19:56:09.3013552Z 2025-08-26T19:56:09.3013865Z The regular implementation uses the (more common in PyTorch) `torch.long` dtype. 2025-08-26T19:56:09.3013947Z 2025-08-26T19:56:09.3014039Z 2025-08-26T19:56:09.3014124Z Note: 2025-08-26T19:56:09.3014371Z In some circumstances when using the CUDA backend with CuDNN, this operator 2025-08-26T19:56:09.3014669Z may select a nondeterministic algorithm to increase performance. If this is 2025-08-26T19:56:09.3014923Z undesirable, you can try to make the operation deterministic (potentially at 2025-08-26T19:56:09.3015172Z a performance cost) by setting ``torch.backends.cudnn.deterministic = 2025-08-26T19:56:09.3015258Z True``. 2025-08-26T19:56:09.3015458Z Please see the notes on :doc:`/notes/randomness` for background. 2025-08-26T19:56:09.3015557Z 2025-08-26T19:56:09.3015813Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3015908Z 2025-08-26T19:56:09.3016009Z warnings.warn(msg) 2025-08-26T19:56:09.3016093Z 2025-08-26T19:56:09.3016325Z --- Parse Warning: 108 / 146 --- 2025-08-26T19:56:09.3017246Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MaxUnpool2d in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/pooling.py line=410. 2025-08-26T19:56:09.3017530Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3017692Z Computes a partial inverse of :class:`MaxPool2d`. 2025-08-26T19:56:09.3017774Z 2025-08-26T19:56:09.3018053Z :class:`MaxPool2d` is not fully invertible, since the non-maximal values are lost. 2025-08-26T19:56:09.3018135Z 2025-08-26T19:56:09.3018380Z :class:`MaxUnpool2d` takes in as input the output of :class:`MaxPool2d` 2025-08-26T19:56:09.3018627Z including the indices of the maximal values and computes a partial inverse 2025-08-26T19:56:09.3018778Z in which all non-maximal values are set to zero. 2025-08-26T19:56:09.3018873Z 2025-08-26T19:56:09.3018959Z Note: 2025-08-26T19:56:09.3019292Z This operation may behave nondeterministically when the input indices has repeat values. 2025-08-26T19:56:09.3019682Z See https://github.com/pytorch/pytorch/issues/80827 and :doc:`/notes/randomness` for more information. 2025-08-26T19:56:09.3019797Z 2025-08-26T19:56:09.3020048Z .. note:: :class:`MaxPool2d` can map several input sizes to the same output 2025-08-26T19:56:09.3020227Z sizes. Hence, the inversion process can get ambiguous. 2025-08-26T19:56:09.3020431Z To accommodate this, you can provide the needed output size 2025-08-26T19:56:09.3020645Z as an additional argument :attr:`output_size` in the forward call. 2025-08-26T19:56:09.3020772Z See the Inputs and Example below. 2025-08-26T19:56:09.3020865Z 2025-08-26T19:56:09.3020952Z Args: 2025-08-26T19:56:09.3021152Z kernel_size (int or tuple): Size of the max pooling window. 2025-08-26T19:56:09.3021326Z stride (int or tuple): Stride of the max pooling window. 2025-08-26T19:56:09.3021462Z It is set to :attr:`kernel_size` by default. 2025-08-26T19:56:09.3021665Z padding (int or tuple): Padding that was added to the input 2025-08-26T19:56:09.3021747Z 2025-08-26T19:56:09.3021871Z Inputs: 2025-08-26T19:56:09.3021996Z - `input`: the input Tensor to invert 2025-08-26T19:56:09.3022205Z - `indices`: the indices given out by :class:`~torch.nn.MaxPool2d` 2025-08-26T19:56:09.3022381Z - `output_size` (optional): the targeted output size 2025-08-26T19:56:09.3022463Z 2025-08-26T19:56:09.3022560Z Shape: 2025-08-26T19:56:09.3022748Z - Input: :math:`(N, C, H_{in}, W_{in})` or :math:`(C, H_{in}, W_{in})`. 2025-08-26T19:56:09.3022986Z - Output: :math:`(N, C, H_{out}, W_{out})` or :math:`(C, H_{out}, W_{out})`, where 2025-08-26T19:56:09.3023081Z 2025-08-26T19:56:09.3023174Z .. math:: 2025-08-26T19:56:09.3023458Z H_{out} = (H_{in} - 1) \times \text{stride[0]} - 2 \times \text{padding[0]} + \text{kernel\_size[0]} 2025-08-26T19:56:09.3023540Z 2025-08-26T19:56:09.3023629Z .. math:: 2025-08-26T19:56:09.3023933Z W_{out} = (W_{in} - 1) \times \text{stride[1]} - 2 \times \text{padding[1]} + \text{kernel\_size[1]} 2025-08-26T19:56:09.3024017Z 2025-08-26T19:56:09.3024196Z or as given by :attr:`output_size` in the call operator 2025-08-26T19:56:09.3024277Z 2025-08-26T19:56:09.3024368Z Example:: 2025-08-26T19:56:09.3024466Z 2025-08-26T19:56:09.3024631Z >>> pool = nn.MaxPool2d(2, stride=2, return_indices=True) 2025-08-26T19:56:09.3024760Z >>> unpool = nn.MaxUnpool2d(2, stride=2) 2025-08-26T19:56:09.3024910Z >>> input = torch.tensor([[[[ 1., 2., 3., 4.], 2025-08-26T19:56:09.3025022Z [ 5., 6., 7., 8.], 2025-08-26T19:56:09.3025141Z [ 9., 10., 11., 12.], 2025-08-26T19:56:09.3025255Z [13., 14., 15., 16.]]]]) 2025-08-26T19:56:09.3025372Z >>> output, indices = pool(input) 2025-08-26T19:56:09.3025495Z >>> unpool(output, indices) 2025-08-26T19:56:09.3025604Z tensor([[[[ 0., 0., 0., 0.], 2025-08-26T19:56:09.3025714Z [ 0., 6., 0., 8.], 2025-08-26T19:56:09.3025813Z [ 0., 0., 0., 0.], 2025-08-26T19:56:09.3025914Z [ 0., 14., 0., 16.]]]]) 2025-08-26T19:56:09.3026141Z >>> # Now using output_size to resolve an ambiguous size for the inverse 2025-08-26T19:56:09.3026286Z >>> input = torch.tensor([[[[ 1., 2., 3., 4., 5.], 2025-08-26T19:56:09.3026411Z [ 6., 7., 8., 9., 10.], 2025-08-26T19:56:09.3026521Z [11., 12., 13., 14., 15.], 2025-08-26T19:56:09.3026637Z [16., 17., 18., 19., 20.]]]]) 2025-08-26T19:56:09.3026767Z >>> output, indices = pool(input) 2025-08-26T19:56:09.3026942Z >>> # This call will not work without specifying output_size 2025-08-26T19:56:09.3027142Z >>> unpool(output, indices, output_size=input.size()) 2025-08-26T19:56:09.3027252Z tensor([[[[ 0., 0., 0., 0., 0.], 2025-08-26T19:56:09.3027352Z [ 0., 7., 0., 9., 0.], 2025-08-26T19:56:09.3027464Z [ 0., 0., 0., 0., 0.], 2025-08-26T19:56:09.3027567Z [ 0., 17., 0., 19., 0.]]]]) 2025-08-26T19:56:09.3027662Z 2025-08-26T19:56:09.3027744Z 2025-08-26T19:56:09.3027826Z 2025-08-26T19:56:09.3028102Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3028187Z 2025-08-26T19:56:09.3028297Z warnings.warn(msg) 2025-08-26T19:56:09.3028378Z 2025-08-26T19:56:09.3028581Z --- Parse Warning: 109 / 146 --- 2025-08-26T19:56:09.3029515Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=EmbeddingBag in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/sparse.py line=272. 2025-08-26T19:56:09.3029833Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3030173Z Compute sums or means of 'bags' of embeddings, without instantiating the intermediate embeddings. 2025-08-26T19:56:09.3030256Z 2025-08-26T19:56:09.3030585Z For bags of constant length, no :attr:`per_sample_weights`, no indices equal to :attr:`padding_idx`, 2025-08-26T19:56:09.3030713Z and with 2D inputs, this class 2025-08-26T19:56:09.3030796Z 2025-08-26T19:56:09.3031151Z * with ``mode="sum"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.sum(dim=1)``, 2025-08-26T19:56:09.3031475Z * with ``mode="mean"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.mean(dim=1)``, 2025-08-26T19:56:09.3031818Z * with ``mode="max"`` is equivalent to :class:`~torch.nn.Embedding` followed by ``torch.max(dim=1)``. 2025-08-26T19:56:09.3031903Z 2025-08-26T19:56:09.3032265Z However, :class:`~torch.nn.EmbeddingBag` is much more time and memory efficient than using a chain of these 2025-08-26T19:56:09.3032377Z operations. 2025-08-26T19:56:09.3032460Z 2025-08-26T19:56:09.3032725Z EmbeddingBag also supports per-sample weights as an argument to the forward 2025-08-26T19:56:09.3032979Z pass. This scales the output of the Embedding before performing a weighted 2025-08-26T19:56:09.3033235Z reduction as specified by ``mode``. If :attr:`per_sample_weights` is passed, the 2025-08-26T19:56:09.3033488Z only supported ``mode`` is ``"sum"``, which computes a weighted sum according to 2025-08-26T19:56:09.3033599Z :attr:`per_sample_weights`. 2025-08-26T19:56:09.3033695Z 2025-08-26T19:56:09.3033779Z Args: 2025-08-26T19:56:09.3033966Z num_embeddings (int): size of the dictionary of embeddings 2025-08-26T19:56:09.3034151Z embedding_dim (int): the size of each embedding vector 2025-08-26T19:56:09.3034473Z max_norm (float, optional): If given, each embedding vector with norm larger than :attr:`max_norm` 2025-08-26T19:56:09.3034639Z is renormalized to have norm :attr:`max_norm`. 2025-08-26T19:56:09.3034982Z norm_type (float, optional): The p of the p-norm to compute for the :attr:`max_norm` option. Default ``2``. 2025-08-26T19:56:09.3035315Z scale_grad_by_freq (bool, optional): if given, this will scale gradients by the inverse of frequency of 2025-08-26T19:56:09.3035489Z the words in the mini-batch. Default ``False``. 2025-08-26T19:56:09.3035677Z Note: this option is not supported when ``mode="max"``. 2025-08-26T19:56:09.3035941Z mode (str, optional): ``"sum"``, ``"mean"`` or ``"max"``. Specifies the way to reduce the bag. 2025-08-26T19:56:09.3036168Z ``"sum"`` computes the weighted sum, taking :attr:`per_sample_weights` 2025-08-26T19:56:09.3036441Z into consideration. ``"mean"`` computes the average of the values 2025-08-26T19:56:09.3036619Z in the bag, ``"max"`` computes the max value over each bag. 2025-08-26T19:56:09.3036736Z Default: ``"mean"`` 2025-08-26T19:56:09.3037073Z sparse (bool, optional): if ``True``, gradient w.r.t. :attr:`weight` matrix will be a sparse tensor. See 2025-08-26T19:56:09.3037341Z Notes for more details regarding sparse gradients. Note: this option is not 2025-08-26T19:56:09.3037697Z supported when ``mode="max"``. 2025-08-26T19:56:09.3038077Z include_last_offset (bool, optional): if ``True``, :attr:`offsets` has one additional element, where the last element 2025-08-26T19:56:09.3038307Z is equivalent to the size of `indices`. This matches the CSR format. 2025-08-26T19:56:09.3038737Z padding_idx (int, optional): If specified, the entries at :attr:`padding_idx` do not contribute to the 2025-08-26T19:56:09.3039015Z gradient; therefore, the embedding vector at :attr:`padding_idx` is not updated 2025-08-26T19:56:09.3039277Z during training, i.e. it remains as a fixed "pad". For a newly constructed 2025-08-26T19:56:09.3039588Z EmbeddingBag, the embedding vector at :attr:`padding_idx` will default to all 2025-08-26T19:56:09.3039857Z zeros, but can be updated to another value to be used as the padding vector. 2025-08-26T19:56:09.3040106Z Note that the embedding vector at :attr:`padding_idx` is excluded from the 2025-08-26T19:56:09.3040290Z reduction. 2025-08-26T19:56:09.3040388Z 2025-08-26T19:56:09.3040478Z Attributes: 2025-08-26T19:56:09.3040817Z weight (Tensor): the learnable weights of the module of shape `(num_embeddings, embedding_dim)` 2025-08-26T19:56:09.3040965Z initialized from :math:`\mathcal{N}(0, 1)`. 2025-08-26T19:56:09.3041046Z 2025-08-26T19:56:09.3041154Z Examples:: 2025-08-26T19:56:09.3041234Z 2025-08-26T19:56:09.3041421Z >>> # an EmbeddingBag module containing 10 tensors of size 3 2025-08-26T19:56:09.3041584Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum') 2025-08-26T19:56:09.3041721Z >>> # a batch of 2 samples of 4 indices each 2025-08-26T19:56:09.3041926Z >>> input = torch.tensor([1, 2, 4, 5, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T19:56:09.3042077Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T19:56:09.3042234Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:09.3042356Z >>> embedding_sum(input, offsets) 2025-08-26T19:56:09.3042470Z tensor([[-0.8861, -5.4350, -0.0523], 2025-08-26T19:56:09.3042588Z [ 1.1306, -2.5798, -1.0044]]) 2025-08-26T19:56:09.3042671Z 2025-08-26T19:56:09.3042795Z >>> # Example with padding_idx 2025-08-26T19:56:09.3043008Z >>> embedding_sum = nn.EmbeddingBag(10, 3, mode='sum', padding_idx=2) 2025-08-26T19:56:09.3043193Z >>> input = torch.tensor([2, 2, 2, 2, 4, 3, 2, 9], dtype=torch.long) 2025-08-26T19:56:09.3043356Z >>> offsets = torch.tensor([0, 4], dtype=torch.long) 2025-08-26T19:56:09.3043472Z >>> embedding_sum(input, offsets) 2025-08-26T19:56:09.3043588Z tensor([[ 0.0000, 0.0000, 0.0000], 2025-08-26T19:56:09.3043692Z [-0.7082, 3.2145, -2.6251]]) 2025-08-26T19:56:09.3043772Z 2025-08-26T19:56:09.3043962Z >>> # An EmbeddingBag can be loaded from an Embedding like so 2025-08-26T19:56:09.3044157Z >>> embedding = nn.Embedding(10, 3, padding_idx=2) 2025-08-26T19:56:09.3044328Z >>> embedding_sum = nn.EmbeddingBag.from_pretrained( 2025-08-26T19:56:09.3044434Z embedding.weight, 2025-08-26T19:56:09.3044567Z padding_idx=embedding.padding_idx, 2025-08-26T19:56:09.3044675Z mode='sum') 2025-08-26T19:56:09.3044759Z 2025-08-26T19:56:09.3045031Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3045112Z 2025-08-26T19:56:09.3045213Z warnings.warn(msg) 2025-08-26T19:56:09.3045307Z 2025-08-26T19:56:09.3045520Z --- Parse Warning: 110 / 146 --- 2025-08-26T19:56:09.3046515Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Transformer.forward in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py line=186. 2025-08-26T19:56:09.3046789Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3046974Z Take in and process masked source/target sequences. 2025-08-26T19:56:09.3047072Z 2025-08-26T19:56:09.3047165Z .. note:: 2025-08-26T19:56:09.3047261Z 2025-08-26T19:56:09.3047660Z If a boolean tensor is provided for any of the [src/tgt/memory]_mask arguments, positions with a ``True`` value are 2025-08-26T19:56:09.3047811Z not allowed to participate in the attention, 2025-08-26T19:56:09.3048046Z which is the opposite of the definition for :attr:`attn_mask` 2025-08-26T19:56:09.3048240Z in :func:`torch.nn.functional.scaled_dot_product_attention`. 2025-08-26T19:56:09.3048333Z 2025-08-26T19:56:09.3048418Z Args: 2025-08-26T19:56:09.3048557Z src: the sequence to the encoder (required). 2025-08-26T19:56:09.3048735Z tgt: the sequence to the decoder (required). 2025-08-26T19:56:09.3049004Z src_mask: the additive mask for the src sequence (optional). 2025-08-26T19:56:09.3049205Z tgt_mask: the additive mask for the tgt sequence (optional). 2025-08-26T19:56:09.3049416Z memory_mask: the additive mask for the encoder output (optional). 2025-08-26T19:56:09.3049648Z src_key_padding_mask: the Tensor mask for src keys per batch (optional). 2025-08-26T19:56:09.3049892Z tgt_key_padding_mask: the Tensor mask for tgt keys per batch (optional). 2025-08-26T19:56:09.3050151Z memory_key_padding_mask: the Tensor mask for memory keys per batch (optional). 2025-08-26T19:56:09.3050376Z src_is_causal: If specified, applies a causal mask as ``src_mask``. 2025-08-26T19:56:09.3050526Z Default: ``None``; try to detect a causal mask. 2025-08-26T19:56:09.3050621Z Warning: 2025-08-26T19:56:09.3050799Z ``src_is_causal`` provides a hint that ``src_mask`` is 2025-08-26T19:56:09.3050981Z the causal mask. Providing incorrect hints can result in 2025-08-26T19:56:09.3051163Z incorrect execution, including forward and backward 2025-08-26T19:56:09.3051266Z compatibility. 2025-08-26T19:56:09.3051476Z tgt_is_causal: If specified, applies a causal mask as ``tgt_mask``. 2025-08-26T19:56:09.3051634Z Default: ``None``; try to detect a causal mask. 2025-08-26T19:56:09.3051727Z Warning: 2025-08-26T19:56:09.3051899Z ``tgt_is_causal`` provides a hint that ``tgt_mask`` is 2025-08-26T19:56:09.3052078Z the causal mask. Providing incorrect hints can result in 2025-08-26T19:56:09.3052244Z incorrect execution, including forward and backward 2025-08-26T19:56:09.3052356Z compatibility. 2025-08-26T19:56:09.3052537Z memory_is_causal: If specified, applies a causal mask as 2025-08-26T19:56:09.3052682Z ``memory_mask``. 2025-08-26T19:56:09.3052782Z Default: ``False``. 2025-08-26T19:56:09.3052874Z Warning: 2025-08-26T19:56:09.3053025Z ``memory_is_causal`` provides a hint that 2025-08-26T19:56:09.3053194Z ``memory_mask`` is the causal mask. Providing incorrect 2025-08-26T19:56:09.3053366Z hints can result in incorrect execution, including 2025-08-26T19:56:09.3053496Z forward and backward compatibility. 2025-08-26T19:56:09.3053578Z 2025-08-26T19:56:09.3053676Z Shape: 2025-08-26T19:56:09.3053930Z - src: :math:`(S, E)` for unbatched input, :math:`(S, N, E)` if `batch_first=False` or 2025-08-26T19:56:09.3054063Z `(N, S, E)` if `batch_first=True`. 2025-08-26T19:56:09.3054310Z - tgt: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T19:56:09.3054458Z `(N, T, E)` if `batch_first=True`. 2025-08-26T19:56:09.3054663Z - src_mask: :math:`(S, S)` or :math:`(N\cdot\text{num\_heads}, S, S)`. 2025-08-26T19:56:09.3054850Z - tgt_mask: :math:`(T, T)` or :math:`(N\cdot\text{num\_heads}, T, T)`. 2025-08-26T19:56:09.3054977Z - memory_mask: :math:`(T, S)`. 2025-08-26T19:56:09.3055224Z - src_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T19:56:09.3055504Z - tgt_key_padding_mask: :math:`(T)` for unbatched input otherwise :math:`(N, T)`. 2025-08-26T19:56:09.3055767Z - memory_key_padding_mask: :math:`(S)` for unbatched input otherwise :math:`(N, S)`. 2025-08-26T19:56:09.3055848Z 2025-08-26T19:56:09.3056177Z Note: [src/tgt/memory]_mask ensures that position :math:`i` is allowed to attend the unmasked 2025-08-26T19:56:09.3056418Z positions. If a BoolTensor is provided, positions with ``True`` 2025-08-26T19:56:09.3056702Z are not allowed to attend while ``False`` values will be unchanged. If a FloatTensor 2025-08-26T19:56:09.3056872Z is provided, it will be added to the attention weight. 2025-08-26T19:56:09.3057185Z [src/tgt/memory]_key_padding_mask provides specified elements in the key to be ignored by 2025-08-26T19:56:09.3057413Z the attention. If a BoolTensor is provided, the positions with the 2025-08-26T19:56:09.3057731Z value of ``True`` will be ignored while the position with the value of ``False`` will be unchanged. 2025-08-26T19:56:09.3057825Z 2025-08-26T19:56:09.3058088Z - output: :math:`(T, E)` for unbatched input, :math:`(T, N, E)` if `batch_first=False` or 2025-08-26T19:56:09.3058210Z `(N, T, E)` if `batch_first=True`. 2025-08-26T19:56:09.3058304Z 2025-08-26T19:56:09.3058557Z Note: Due to the multi-head attention architecture in the transformer model, 2025-08-26T19:56:09.3058817Z the output sequence length of a transformer is same as the input sequence 2025-08-26T19:56:09.3058940Z (i.e. target) length of the decoder. 2025-08-26T19:56:09.3059021Z 2025-08-26T19:56:09.3059361Z where :math:`S` is the source sequence length, :math:`T` is the target sequence length, :math:`N` is the 2025-08-26T19:56:09.3059500Z batch size, :math:`E` is the feature number 2025-08-26T19:56:09.3059599Z 2025-08-26T19:56:09.3059692Z Examples: 2025-08-26T19:56:09.3059801Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3059930Z >>> output = transformer_model( 2025-08-26T19:56:09.3060081Z ... src, tgt, src_mask=src_mask, tgt_mask=tgt_mask 2025-08-26T19:56:09.3060177Z ... ) 2025-08-26T19:56:09.3060261Z 2025-08-26T19:56:09.3060521Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3060658Z 2025-08-26T19:56:09.3060757Z warnings.warn(msg) 2025-08-26T19:56:09.3060849Z 2025-08-26T19:56:09.3061061Z --- Parse Warning: 111 / 146 --- 2025-08-26T19:56:09.3062102Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel.join in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=1766. 2025-08-26T19:56:09.3062384Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3062465Z 2025-08-26T19:56:09.3062720Z Context manager for training with uneven inputs across processes in DDP. 2025-08-26T19:56:09.3062809Z 2025-08-26T19:56:09.3063038Z This context manager will keep track of already-joined DDP processes, 2025-08-26T19:56:09.3063263Z and "shadow" the forward and backward passes by inserting collective 2025-08-26T19:56:09.3063502Z communication operations to match with the ones created by non-joined 2025-08-26T19:56:09.3063779Z DDP processes. This will ensure each collective call has a corresponding 2025-08-26T19:56:09.3064003Z call by already-joined DDP processes, preventing hangs or errors that 2025-08-26T19:56:09.3064210Z would otherwise happen when training with uneven inputs across 2025-08-26T19:56:09.3064466Z processes. Alternatively, if the flag ``throw_on_early_termination`` is 2025-08-26T19:56:09.3064680Z specified to be ``True``, all trainers will throw an error once one rank 2025-08-26T19:56:09.3064933Z runs out of inputs, allowing these errors to be caught and handled 2025-08-26T19:56:09.3065051Z according to application logic. 2025-08-26T19:56:09.3065132Z 2025-08-26T19:56:09.3065368Z Once all DDP processes have joined, the context manager will broadcast 2025-08-26T19:56:09.3065625Z the model corresponding to the last joined process to all processes to 2025-08-26T19:56:09.3065794Z ensure the model is the same across all processes 2025-08-26T19:56:09.3065906Z (which is guaranteed by DDP). 2025-08-26T19:56:09.3065991Z 2025-08-26T19:56:09.3066210Z To use this to enable training with uneven inputs across processes, 2025-08-26T19:56:09.3066437Z simply wrap this context manager around your training loop. No further 2025-08-26T19:56:09.3066631Z modifications to the model or data loading is required. 2025-08-26T19:56:09.3066716Z 2025-08-26T19:56:09.3066810Z .. warning:: 2025-08-26T19:56:09.3067040Z If the model or training loop this context manager is wrapped around 2025-08-26T19:56:09.3067230Z has additional distributed collective operations, such as 2025-08-26T19:56:09.3067435Z ``SyncBatchNorm`` in the model's forward pass, then the flag 2025-08-26T19:56:09.3067644Z ``throw_on_early_termination`` must be enabled. This is because this 2025-08-26T19:56:09.3067863Z context manager is not aware of non-DDP collective communication. 2025-08-26T19:56:09.3068056Z This flag will cause all ranks to throw when any one rank 2025-08-26T19:56:09.3068271Z exhausts inputs, allowing these errors to be caught and recovered 2025-08-26T19:56:09.3068389Z from across all ranks. 2025-08-26T19:56:09.3068473Z 2025-08-26T19:56:09.3068560Z Args: 2025-08-26T19:56:09.3068757Z divide_by_initial_world_size (bool): If ``True``, will divide 2025-08-26T19:56:09.3068966Z gradients by the initial ``world_size`` DDP training was launched 2025-08-26T19:56:09.3069148Z with. If ``False``, will compute the effective world size 2025-08-26T19:56:09.3069336Z (number of ranks that have not depleted their inputs yet) and 2025-08-26T19:56:09.3069488Z divide gradients by that during allreduce. Set 2025-08-26T19:56:09.3069680Z ``divide_by_initial_world_size=True`` to ensure every input 2025-08-26T19:56:09.3069898Z sample including the uneven inputs have equal weight in terms of 2025-08-26T19:56:09.3070119Z how much they contribute to the global gradient. This is 2025-08-26T19:56:09.3070296Z achieved by always dividing the gradient by the initial 2025-08-26T19:56:09.3070496Z ``world_size`` even when we encounter uneven inputs. If you set 2025-08-26T19:56:09.3070666Z this to ``False``, we divide the gradient by the remaining 2025-08-26T19:56:09.3070863Z number of nodes. This ensures parity with training on a smaller 2025-08-26T19:56:09.3071063Z ``world_size`` although it also means the uneven inputs would 2025-08-26T19:56:09.3071260Z contribute more towards the global gradient. Typically, you 2025-08-26T19:56:09.3071462Z would want to set this to ``True`` for cases where the last few 2025-08-26T19:56:09.3071660Z inputs of your training job are uneven. In extreme cases, where 2025-08-26T19:56:09.3071849Z there is a large discrepancy in the number of inputs, setting 2025-08-26T19:56:09.3072035Z this to ``False`` might provide better results. 2025-08-26T19:56:09.3072246Z enable (bool): Whether to enable uneven input detection or not. Pass 2025-08-26T19:56:09.3072435Z in ``enable=False`` to disable in cases where you know that 2025-08-26T19:56:09.3072625Z inputs are even across participating processes. Default is 2025-08-26T19:56:09.3072713Z ``True``. 2025-08-26T19:56:09.3072910Z throw_on_early_termination (bool): Whether to throw an error 2025-08-26T19:56:09.3073128Z or continue training when at least one rank has exhausted 2025-08-26T19:56:09.3073328Z inputs. If ``True``, will throw upon the first rank reaching end 2025-08-26T19:56:09.3073499Z of data. If ``False``, will continue training with a smaller 2025-08-26T19:56:09.3073695Z effective world size until all ranks are joined. Note that if 2025-08-26T19:56:09.3073857Z this flag is specified, then the flag 2025-08-26T19:56:09.3074038Z ``divide_by_initial_world_size`` would be ignored. Default 2025-08-26T19:56:09.3074143Z is ``False``. 2025-08-26T19:56:09.3074223Z 2025-08-26T19:56:09.3074304Z 2025-08-26T19:56:09.3074409Z Example:: 2025-08-26T19:56:09.3074491Z 2025-08-26T19:56:09.3074623Z >>> # xdoctest: +SKIP("Distributed") 2025-08-26T19:56:09.3074717Z >>> import torch 2025-08-26T19:56:09.3074841Z >>> import torch.distributed as dist 2025-08-26T19:56:09.3074946Z >>> import os 2025-08-26T19:56:09.3075074Z >>> import torch.multiprocessing as mp 2025-08-26T19:56:09.3075178Z >>> import torch.nn as nn 2025-08-26T19:56:09.3075293Z >>> # On each spawned worker 2025-08-26T19:56:09.3075391Z >>> def worker(rank): 2025-08-26T19:56:09.3075584Z >>> dist.init_process_group("nccl", rank=rank, world_size=2) 2025-08-26T19:56:09.3075700Z >>> torch.cuda.set_device(rank) 2025-08-26T19:56:09.3075841Z >>> model = nn.Linear(1, 1, bias=False).to(rank) 2025-08-26T19:56:09.3076031Z >>> model = torch.nn.parallel.DistributedDataParallel( 2025-08-26T19:56:09.3076173Z >>> model, device_ids=[rank], output_device=rank 2025-08-26T19:56:09.3076270Z >>> ) 2025-08-26T19:56:09.3076399Z >>> # Rank 1 gets one more input than rank 0. 2025-08-26T19:56:09.3076587Z >>> inputs = [torch.tensor([1]).float() for _ in range(10 + rank)] 2025-08-26T19:56:09.3076701Z >>> with model.join(): 2025-08-26T19:56:09.3076805Z >>> for _ in range(5): 2025-08-26T19:56:09.3076923Z >>> for inp in inputs: 2025-08-26T19:56:09.3077039Z >>> loss = model(inp).sum() 2025-08-26T19:56:09.3077143Z >>> loss.backward() 2025-08-26T19:56:09.3077347Z >>> # Without the join() API, the below synchronization will hang 2025-08-26T19:56:09.3077522Z >>> # blocking for rank 1's allreduce to complete. 2025-08-26T19:56:09.3077664Z >>> torch.cuda.synchronize(device=rank) 2025-08-26T19:56:09.3077746Z 2025-08-26T19:56:09.3078003Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3078098Z 2025-08-26T19:56:09.3078197Z warnings.warn(msg) 2025-08-26T19:56:09.3078291Z 2025-08-26T19:56:09.3078496Z --- Parse Warning: 112 / 146 --- 2025-08-26T19:56:09.3079611Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedDataParallel._register_fused_optim in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/parallel/distributed.py line=2057. 2025-08-26T19:56:09.3079900Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3079984Z 2025-08-26T19:56:09.3080318Z Register an optimizer in DDP to optimize parameter immediately after its gradient reduction. 2025-08-26T19:56:09.3080432Z 2025-08-26T19:56:09.3080646Z Registers an optimizer with DDP such that the optimization for a 2025-08-26T19:56:09.3080871Z parameter will run immediately when that parameter's gradient is 2025-08-26T19:56:09.3081078Z finished with reduction, instead of waiting for all parameters' 2025-08-26T19:56:09.3081313Z gradients to finish reduction. This can result in a training speedup 2025-08-26T19:56:09.3081535Z depending on your workload since the optimizer can run while gradient 2025-08-26T19:56:09.3081795Z reduction for other parameters are still ongoing. In addition, this has 2025-08-26T19:56:09.3082033Z the potential to reduce peak memory consumption during training, as it 2025-08-26T19:56:09.3082237Z only needs to load the per-parameter optimizer states of a single 2025-08-26T19:56:09.3082464Z parameter at a time, instead of loading all per-parameter optimizer 2025-08-26T19:56:09.3082582Z states at once. 2025-08-26T19:56:09.3082666Z 2025-08-26T19:56:09.3082762Z Args: 2025-08-26T19:56:09.3082963Z optim (Type): a ``torch.optim.Optimizer`` class to be registered 2025-08-26T19:56:09.3083078Z as a fused optimizer. 2025-08-26T19:56:09.3083249Z *args (Sequence[Any]): Arguments to forward to `optim`. 2025-08-26T19:56:09.3083464Z optim_params (Optional[Iterable[torch.Tensor]]): Set of parameters 2025-08-26T19:56:09.3083701Z to optimize, similar to `params` argument of traditional `torch.optim` 2025-08-26T19:56:09.3083909Z Optimizers. If this is omitted, all DDP model parameters will be 2025-08-26T19:56:09.3084012Z optimized. 2025-08-26T19:56:09.3084211Z **kwargs: (Dict[str, Any]): Keyword arguments to forward to `optim`. 2025-08-26T19:56:09.3084291Z 2025-08-26T19:56:09.3084397Z .. warning :: 2025-08-26T19:56:09.3084613Z _register_fused_optim should only be called once on a DDP instance, 2025-08-26T19:56:09.3084844Z and registering multiple fused optimizers for the same DDP model 2025-08-26T19:56:09.3084976Z is not currently supported. Please ping 2025-08-26T19:56:09.3085217Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T19:56:09.3085327Z for your use case. 2025-08-26T19:56:09.3085408Z 2025-08-26T19:56:09.3085509Z .. warning :: 2025-08-26T19:56:09.3085703Z _register_fused_optim and register_comm_hook currently do not 2025-08-26T19:56:09.3085920Z compose together, meaning that custom DDP communication hooks are 2025-08-26T19:56:09.3086108Z not supported with overlapped optimizers. Please ping 2025-08-26T19:56:09.3086340Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T19:56:09.3086449Z for your use case. 2025-08-26T19:56:09.3086530Z 2025-08-26T19:56:09.3086617Z .. warning :: 2025-08-26T19:56:09.3086859Z Gradient accumulation and DDP `no_sync` are currently not supported 2025-08-26T19:56:09.3087014Z with overlapped optimizer. Please ping 2025-08-26T19:56:09.3087256Z https://github.com/pytorch/pytorch/issues/71595 if this is necessary 2025-08-26T19:56:09.3087353Z for your use case. 2025-08-26T19:56:09.3087434Z 2025-08-26T19:56:09.3087534Z Example:: 2025-08-26T19:56:09.3087616Z 2025-08-26T19:56:09.3087761Z >>> # xdoctest: +SKIP("No rendezvous handler") 2025-08-26T19:56:09.3088064Z >>> torch.distributed.init_process_group(backend='nccl', world_size=4, init_method='...') 2025-08-26T19:56:09.3088267Z >>> net = torch.nn.parallel.DistributedDataParallel(model, pg) 2025-08-26T19:56:09.3088371Z >>> lr = 1e-2 2025-08-26T19:56:09.3088467Z >>> betas = (0.9, 0.99) 2025-08-26T19:56:09.3088568Z >>> eps = 1e-6 2025-08-26T19:56:09.3088876Z >>> net._register_fused_optim(torch.optim.Adam, lr, betas=betas, eps=eps) 2025-08-26T19:56:09.3089006Z >>> # Example with subset of parameters 2025-08-26T19:56:09.3089164Z >>> params_to_opt = [list(net.parameters())[0]] 2025-08-26T19:56:09.3089309Z >>> net._register_fused_optim( 2025-08-26T19:56:09.3089557Z ... torch.optim.Adam, lr, optim_params=params_to_opt, betas=betas, eps=eps 2025-08-26T19:56:09.3089642Z ... ) 2025-08-26T19:56:09.3089723Z 2025-08-26T19:56:09.3089996Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3090080Z 2025-08-26T19:56:09.3090180Z warnings.warn(msg) 2025-08-26T19:56:09.3090276Z 2025-08-26T19:56:09.3090513Z --- Parse Warning: 113 / 146 --- 2025-08-26T19:56:09.3091560Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv2d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=14. 2025-08-26T19:56:09.3091867Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3092106Z Convert ``memory_format`` of ``nn.Conv2d.weight`` to ``memory_format``. 2025-08-26T19:56:09.3092189Z 2025-08-26T19:56:09.3092469Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T19:56:09.3092759Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T19:56:09.3093021Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T19:56:09.3093345Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T19:56:09.3093427Z 2025-08-26T19:56:09.3093515Z .. note:: 2025-08-26T19:56:09.3093766Z Calling ``model.to(memory_format=torch.channels_last)`` is more aggressive 2025-08-26T19:56:09.3093993Z than the utility function ``convert_conv2d_weight_memory_format``. Any 2025-08-26T19:56:09.3094221Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T19:56:09.3094454Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T19:56:09.3094681Z One place we are confident in is that NHWC(channels_last) conversion for 2025-08-26T19:56:09.3094919Z convolution in cuDNN, as it is beneficial to run convolution in NHWC, 2025-08-26T19:56:09.3095125Z even in cases where we have to apply permutation to input tensors. 2025-08-26T19:56:09.3095222Z 2025-08-26T19:56:09.3095454Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T19:56:09.3095572Z channels_last. This ensures that; 2025-08-26T19:56:09.3095805Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T19:56:09.3096042Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T19:56:09.3096296Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T19:56:09.3096442Z from memory_format conversion. 2025-08-26T19:56:09.3096523Z 2025-08-26T19:56:09.3096764Z The optimal case is that, layers between convolution layers are channels 2025-08-26T19:56:09.3097008Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T19:56:09.3097255Z encounters the first convolution layer and stay in that memory format. 2025-08-26T19:56:09.3097498Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T19:56:09.3097584Z 2025-08-26T19:56:09.3097824Z In case where a channels last incompatible layer is between convolution 2025-08-26T19:56:09.3098039Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T19:56:09.3098281Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T19:56:09.3098514Z contiguous format and be permuted to channels last when it encounters 2025-08-26T19:56:09.3098769Z another convolution layer. There's no point in propagating that 2025-08-26T19:56:09.3098991Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T19:56:09.3099094Z ``memory_format``. 2025-08-26T19:56:09.3099191Z 2025-08-26T19:56:09.3099428Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T19:56:09.3099667Z there might have been a better spot to fuse the permutation other than 2025-08-26T19:56:09.3099817Z immediately before a convolution. 2025-08-26T19:56:09.3099902Z 2025-08-26T19:56:09.3100002Z Args: 2025-08-26T19:56:09.3100221Z module (nn.Module): ``nn.Conv2d`` & ``nn.ConvTranspose2d`` or container 2025-08-26T19:56:09.3100341Z ``nn.Module`` 2025-08-26T19:56:09.3100549Z memory_format: user specified ``memory_format``, 2025-08-26T19:56:09.3100740Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T19:56:09.3100839Z 2025-08-26T19:56:09.3100928Z Returns: 2025-08-26T19:56:09.3101074Z The original module with updated ``nn.Conv2d`` 2025-08-26T19:56:09.3101169Z 2025-08-26T19:56:09.3101260Z Example: 2025-08-26T19:56:09.3101418Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:09.3101576Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T19:56:09.3101687Z >>> input = torch.randint( 2025-08-26T19:56:09.3101856Z ... 1, 10, (2, 8, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T19:56:09.3101940Z ... ) 2025-08-26T19:56:09.3102062Z >>> model = nn.Sequential( 2025-08-26T19:56:09.3102181Z >>> nn.Conv2d(8, 4, 3)).cuda().half() 2025-08-26T19:56:09.3102288Z >>> # This is identical to: 2025-08-26T19:56:09.3102549Z >>> # nn.utils.convert_conv2d_weight_memory_format(model, torch.channels_last) 2025-08-26T19:56:09.3102720Z >>> model = nn.utils.convert_conv2d_weight_memory_format( 2025-08-26T19:56:09.3102848Z ... model, torch.channels_last 2025-08-26T19:56:09.3102932Z ... ) 2025-08-26T19:56:09.3103031Z >>> out = model(input) 2025-08-26T19:56:09.3103126Z 2025-08-26T19:56:09.3103382Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3103474Z 2025-08-26T19:56:09.3103572Z warnings.warn(msg) 2025-08-26T19:56:09.3103652Z 2025-08-26T19:56:09.3103869Z --- Parse Warning: 114 / 146 --- 2025-08-26T19:56:09.3104895Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=convert_conv3d_weight_memory_format in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/memory_format.py line=93. 2025-08-26T19:56:09.3105206Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3105427Z Convert ``memory_format`` of ``nn.Conv3d.weight`` to ``memory_format`` 2025-08-26T19:56:09.3105706Z The conversion recursively applies to nested ``nn.Module``, including ``module``. 2025-08-26T19:56:09.3105996Z Note that it only changes the memory_format, but not the semantics of each dimensions. 2025-08-26T19:56:09.3106256Z This function is used to facilitate the computation to adopt NHWC kernels, which 2025-08-26T19:56:09.3106581Z provides considerable speed up for fp16 data on CUDA devices with compute capability >= 7.0 2025-08-26T19:56:09.3106663Z 2025-08-26T19:56:09.3106753Z .. note:: 2025-08-26T19:56:09.3107021Z Calling ``model.to(memory_format=torch.channels_last_3d)`` is more aggressive 2025-08-26T19:56:09.3107247Z than the utility function ``convert_conv3d_weight_memory_format``. Any 2025-08-26T19:56:09.3107472Z layer with 4d weight will be affected by ``model.to``, which does not 2025-08-26T19:56:09.3107734Z necessarily benefit from conversion to specified ``memory_format``. 2025-08-26T19:56:09.3107986Z One place we are confident in is that NDHWC(channels_last_3d) conversion for 2025-08-26T19:56:09.3108213Z convolution in cuDNN, as it is beneficial to run convolution in NDHWC, 2025-08-26T19:56:09.3108421Z even in cases where we have to apply permutation to input tensors. 2025-08-26T19:56:09.3108520Z 2025-08-26T19:56:09.3108774Z Hence our strategy here is to convert only the weight of convolution to 2025-08-26T19:56:09.3108911Z channels_last_3d. This ensures that; 2025-08-26T19:56:09.3109134Z 1. Fast convolution kernels will be used, the benefit of which could 2025-08-26T19:56:09.3109372Z outweigh overhead of permutation (if input is not in the same format). 2025-08-26T19:56:09.3109650Z 2. No unnecessary permutations are applied on layers that do not benefit 2025-08-26T19:56:09.3109771Z from memory_format conversion. 2025-08-26T19:56:09.3109866Z 2025-08-26T19:56:09.3110097Z The optimal case is that, layers between convolution layers are channels 2025-08-26T19:56:09.3110338Z last compatible. Input tensor would be permuted to channels last when it 2025-08-26T19:56:09.3110583Z encounters the first convolution layer and stay in that memory format. 2025-08-26T19:56:09.3110826Z Hence following convolutions will not need to permute its input tensor. 2025-08-26T19:56:09.3110920Z 2025-08-26T19:56:09.3111145Z In case where a channels last incompatible layer is between convolution 2025-08-26T19:56:09.3111362Z layers, we need to permute the input tensor back to contiguous format 2025-08-26T19:56:09.3111600Z for that layer. The input tensor will go through the remaining layers in 2025-08-26T19:56:09.3111831Z contiguous format and be permuted to channels last when it encounters 2025-08-26T19:56:09.3112057Z another convolution layer. There's no point in propagating that 2025-08-26T19:56:09.3112278Z permutation to an earlier layer, as most layers are quite agnostic to 2025-08-26T19:56:09.3112377Z ``memory_format``. 2025-08-26T19:56:09.3112472Z 2025-08-26T19:56:09.3112706Z This claim might change when PyTorch supports fusion of permutation, as 2025-08-26T19:56:09.3112942Z there might have been a better spot to fuse the permutation other than 2025-08-26T19:56:09.3113065Z immediately before a convolution. 2025-08-26T19:56:09.3113146Z 2025-08-26T19:56:09.3113243Z Args: 2025-08-26T19:56:09.3113458Z module (nn.Module): ``nn.Conv3d`` & ``nn.ConvTranspose3d`` or container 2025-08-26T19:56:09.3113577Z ``nn.Module`` 2025-08-26T19:56:09.3113731Z memory_format: user specified ``memory_format``, 2025-08-26T19:56:09.3113941Z e.g. ``torch.channels_last`` or ``torch.contiguous_format`` 2025-08-26T19:56:09.3114038Z 2025-08-26T19:56:09.3114126Z Returns: 2025-08-26T19:56:09.3114285Z The original module with updated ``nn.Conv3d`` 2025-08-26T19:56:09.3114367Z 2025-08-26T19:56:09.3114454Z Example: 2025-08-26T19:56:09.3114607Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CUDA) 2025-08-26T19:56:09.3114764Z >>> # xdoctest: +REQUIRES(env:CUBLAS_WORKSPACE_CONFIG) 2025-08-26T19:56:09.3114885Z >>> input = torch.randint( 2025-08-26T19:56:09.3115041Z ... 1, 10, (2, 8, 4, 4, 4), dtype=torch.float16, device="cuda" 2025-08-26T19:56:09.3115125Z ... ) 2025-08-26T19:56:09.3115243Z >>> model = nn.Sequential( 2025-08-26T19:56:09.3115359Z >>> nn.Conv3d(8, 4, 3)).cuda().half() 2025-08-26T19:56:09.3115476Z >>> # This is identical to: 2025-08-26T19:56:09.3115738Z >>> # nn.utils.convert_conv3d_weight_memory_format(model, torch.channels_last_3d) 2025-08-26T19:56:09.3115931Z >>> model = nn.utils.convert_conv3d_weight_memory_format( 2025-08-26T19:56:09.3116064Z ... model, torch.channels_last_3d 2025-08-26T19:56:09.3116148Z ... ) 2025-08-26T19:56:09.3116261Z >>> out = model(input) 2025-08-26T19:56:09.3116344Z 2025-08-26T19:56:09.3116603Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3116697Z 2025-08-26T19:56:09.3116796Z warnings.warn(msg) 2025-08-26T19:56:09.3116901Z 2025-08-26T19:56:09.3117116Z --- Parse Warning: 115 / 146 --- 2025-08-26T19:56:09.3118105Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_parametrization in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/parametrize.py line=424. 2025-08-26T19:56:09.3118419Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3118584Z Register a parametrization to a tensor in a module. 2025-08-26T19:56:09.3118681Z 2025-08-26T19:56:09.3118961Z Assume that ``tensor_name="weight"`` for simplicity. When accessing ``module.weight``, 2025-08-26T19:56:09.3119252Z the module will return the parametrized version ``parametrization(module.weight)``. 2025-08-26T19:56:09.3119532Z If the original tensor requires a gradient, the backward pass will differentiate 2025-08-26T19:56:09.3119827Z through :attr:`parametrization`, and the optimizer will update the tensor accordingly. 2025-08-26T19:56:09.3119922Z 2025-08-26T19:56:09.3120238Z The first time that a module registers a parametrization, this function will add an attribute 2025-08-26T19:56:09.3120484Z ``parametrizations`` to the module of type :class:`~ParametrizationList`. 2025-08-26T19:56:09.3120577Z 2025-08-26T19:56:09.3120837Z The list of parametrizations on the tensor ``weight`` will be accessible under 2025-08-26T19:56:09.3120981Z ``module.parametrizations.weight``. 2025-08-26T19:56:09.3121062Z 2025-08-26T19:56:09.3121203Z The original tensor will be accessible under 2025-08-26T19:56:09.3121369Z ``module.parametrizations.weight.original``. 2025-08-26T19:56:09.3121452Z 2025-08-26T19:56:09.3121734Z Parametrizations may be concatenated by registering several parametrizations 2025-08-26T19:56:09.3121836Z on the same attribute. 2025-08-26T19:56:09.3121917Z 2025-08-26T19:56:09.3122178Z The training mode of a registered parametrization is updated on registration 2025-08-26T19:56:09.3122317Z to match the training mode of the host module 2025-08-26T19:56:09.3122410Z 2025-08-26T19:56:09.3122720Z Parametrized parameters and buffers have an inbuilt caching system that can be activated 2025-08-26T19:56:09.3122852Z using the context manager :func:`cached`. 2025-08-26T19:56:09.3122973Z 2025-08-26T19:56:09.3123218Z A :attr:`parametrization` may optionally implement a method with signature 2025-08-26T19:56:09.3123298Z 2025-08-26T19:56:09.3123418Z .. code-block:: python 2025-08-26T19:56:09.3123499Z 2025-08-26T19:56:09.3123731Z def right_inverse(self, X: Tensor) -> Union[Tensor, Sequence[Tensor]] 2025-08-26T19:56:09.3123813Z 2025-08-26T19:56:09.3124081Z This method is called on the unparametrized tensor when the first parametrization 2025-08-26T19:56:09.3124308Z is registered to compute the initial value of the original tensor. 2025-08-26T19:56:09.3124620Z If this method is not implemented, the original tensor will be just the unparametrized tensor. 2025-08-26T19:56:09.3124713Z 2025-08-26T19:56:09.3125031Z If all the parametrizations registered on a tensor implement `right_inverse` it is possible 2025-08-26T19:56:09.3125326Z to initialize a parametrized tensor by assigning to it, as shown in the example below. 2025-08-26T19:56:09.3125454Z 2025-08-26T19:56:09.3125689Z It is possible for the first parametrization to depend on several inputs. 2025-08-26T19:56:09.3125950Z This may be implemented returning a tuple of tensors from ``right_inverse`` 2025-08-26T19:56:09.3126190Z (see the example implementation of a ``RankOne`` parametrization below). 2025-08-26T19:56:09.3126285Z 2025-08-26T19:56:09.3126627Z In this case, the unconstrained tensors are also located under ``module.parametrizations.weight`` 2025-08-26T19:56:09.3126799Z with names ``original0``, ``original1``,... 2025-08-26T19:56:09.3126897Z 2025-08-26T19:56:09.3126987Z .. note:: 2025-08-26T19:56:09.3127068Z 2025-08-26T19:56:09.3127352Z If unsafe=False (default) both the forward and right_inverse methods will be called 2025-08-26T19:56:09.3127506Z once to perform a number of consistency checks. 2025-08-26T19:56:09.3127819Z If unsafe=True, then right_inverse will be called if the tensor is not parametrized, 2025-08-26T19:56:09.3127946Z and nothing will be called otherwise. 2025-08-26T19:56:09.3128026Z 2025-08-26T19:56:09.3128128Z .. note:: 2025-08-26T19:56:09.3128208Z 2025-08-26T19:56:09.3128430Z In most situations, ``right_inverse`` will be a function such that 2025-08-26T19:56:09.3128554Z ``forward(right_inverse(X)) == X`` (see 2025-08-26T19:56:09.3128925Z `right inverse `_). 2025-08-26T19:56:09.3129203Z Sometimes, when the parametrization is not surjective, it may be reasonable 2025-08-26T19:56:09.3129299Z to relax this. 2025-08-26T19:56:09.3129399Z 2025-08-26T19:56:09.3129489Z .. warning:: 2025-08-26T19:56:09.3129570Z 2025-08-26T19:56:09.3129867Z If a parametrization depends on several inputs, :func:`~register_parametrization` 2025-08-26T19:56:09.3130133Z will register a number of new parameters. If such parametrization is registered 2025-08-26T19:56:09.3130424Z after the optimizer is created, these new parameters will need to be added manually 2025-08-26T19:56:09.3130623Z to the optimizer. See :meth:`torch.Optimizer.add_param_group`. 2025-08-26T19:56:09.3130703Z 2025-08-26T19:56:09.3130798Z Args: 2025-08-26T19:56:09.3131016Z module (nn.Module): module on which to register the parametrization 2025-08-26T19:56:09.3131252Z tensor_name (str): name of the parameter or buffer on which to register 2025-08-26T19:56:09.3131361Z the parametrization 2025-08-26T19:56:09.3131572Z parametrization (nn.Module): the parametrization to register 2025-08-26T19:56:09.3131678Z Keyword args: 2025-08-26T19:56:09.3131900Z unsafe (bool): a boolean flag that denotes whether the parametrization 2025-08-26T19:56:09.3132147Z may change the dtype and shape of the tensor. Default: `False` 2025-08-26T19:56:09.3132424Z Warning: the parametrization is not checked for consistency upon registration. 2025-08-26T19:56:09.3132545Z Enable this flag at your own risk. 2025-08-26T19:56:09.3132642Z 2025-08-26T19:56:09.3132727Z Raises: 2025-08-26T19:56:09.3133036Z ValueError: if the module does not have a parameter or a buffer named :attr:`tensor_name` 2025-08-26T19:56:09.3133119Z 2025-08-26T19:56:09.3133208Z Examples: 2025-08-26T19:56:09.3133377Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK) 2025-08-26T19:56:09.3133477Z >>> import torch 2025-08-26T19:56:09.3133599Z >>> import torch.nn as nn 2025-08-26T19:56:09.3133739Z >>> import torch.nn.utils.parametrize as P 2025-08-26T19:56:09.3133824Z >>> 2025-08-26T19:56:09.3133953Z >>> class Symmetric(nn.Module): 2025-08-26T19:56:09.3134065Z >>> def forward(self, X): 2025-08-26T19:56:09.3134290Z >>> return X.triu() + X.triu(1).T # Return a symmetric matrix 2025-08-26T19:56:09.3134374Z >>> 2025-08-26T19:56:09.3134491Z >>> def right_inverse(self, A): 2025-08-26T19:56:09.3134606Z >>> return A.triu() 2025-08-26T19:56:09.3134693Z >>> 2025-08-26T19:56:09.3134805Z >>> m = nn.Linear(5, 5) 2025-08-26T19:56:09.3134977Z >>> P.register_parametrization(m, "weight", Symmetric()) 2025-08-26T19:56:09.3135253Z >>> print(torch.allclose(m.weight, m.weight.T)) # m.weight is now symmetric 2025-08-26T19:56:09.3135353Z True 2025-08-26T19:56:09.3135454Z >>> A = torch.rand(5, 5) 2025-08-26T19:56:09.3135582Z >>> A = A + A.T # A is now symmetric 2025-08-26T19:56:09.3135783Z >>> m.weight = A # Initialize the weight to be the symmetric matrix A 2025-08-26T19:56:09.3135934Z >>> print(torch.allclose(m.weight, A)) 2025-08-26T19:56:09.3136036Z True 2025-08-26T19:56:09.3136116Z 2025-08-26T19:56:09.3136223Z >>> class RankOne(nn.Module): 2025-08-26T19:56:09.3136346Z >>> def forward(self, x, y): 2025-08-26T19:56:09.3136490Z >>> # Form a rank 1 matrix multiplying two vectors 2025-08-26T19:56:09.3136638Z >>> return x.unsqueeze(-1) @ y.unsqueeze(-2) 2025-08-26T19:56:09.3136720Z >>> 2025-08-26T19:56:09.3136836Z >>> def right_inverse(self, Z): 2025-08-26T19:56:09.3136971Z >>> # Project Z onto the rank 1 matrices 2025-08-26T19:56:09.3137128Z >>> U, S, Vh = torch.linalg.svd(Z, full_matrices=False) 2025-08-26T19:56:09.3137258Z >>> # Return rescaled singular vectors 2025-08-26T19:56:09.3137539Z >>> s0_sqrt = S[0].sqrt().unsqueeze(-1) 2025-08-26T19:56:09.3137694Z >>> return U[..., :, 0] * s0_sqrt, Vh[..., 0, :] * s0_sqrt 2025-08-26T19:56:09.3137789Z >>> 2025-08-26T19:56:09.3137941Z >>> linear_rank_one = P.register_parametrization( 2025-08-26T19:56:09.3138079Z ... nn.Linear(4, 4), "weight", RankOne() 2025-08-26T19:56:09.3138163Z ... ) 2025-08-26T19:56:09.3138371Z >>> print(torch.linalg.matrix_rank(linear_rank_one.weight).item()) 2025-08-26T19:56:09.3138471Z 1 2025-08-26T19:56:09.3138552Z 2025-08-26T19:56:09.3138649Z 2025-08-26T19:56:09.3138907Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3138987Z 2025-08-26T19:56:09.3139099Z warnings.warn(msg) 2025-08-26T19:56:09.3139180Z 2025-08-26T19:56:09.3139413Z --- Parse Warning: 116 / 146 --- 2025-08-26T19:56:09.3140314Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ln_structured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=979. 2025-08-26T19:56:09.3140649Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3140977Z Prune tensor by removing channels with the lowest L\ ``n``-norm along the specified dimension. 2025-08-26T19:56:09.3141061Z 2025-08-26T19:56:09.3141311Z Prunes tensor corresponding to parameter called ``name`` in ``module`` 2025-08-26T19:56:09.3141532Z by removing the specified ``amount`` of (currently unpruned) channels 2025-08-26T19:56:09.3141713Z along the specified ``dim`` with the lowest L\ ``n``-norm. 2025-08-26T19:56:09.3141925Z Modifies module in place (and also return the modified module) 2025-08-26T19:56:09.3142009Z by: 2025-08-26T19:56:09.3142101Z 2025-08-26T19:56:09.3142311Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T19:56:09.3142535Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T19:56:09.3142763Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T19:56:09.3143012Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T19:56:09.3143121Z ``name+'_orig'``. 2025-08-26T19:56:09.3143202Z 2025-08-26T19:56:09.3143286Z Args: 2025-08-26T19:56:09.3143477Z module (nn.Module): module containing the tensor to prune 2025-08-26T19:56:09.3143660Z name (str): parameter name within ``module`` on which pruning 2025-08-26T19:56:09.3143763Z will act. 2025-08-26T19:56:09.3143974Z amount (int or float): quantity of parameters to prune. 2025-08-26T19:56:09.3144151Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T19:56:09.3144368Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T19:56:09.3144503Z absolute number of parameters to prune. 2025-08-26T19:56:09.3144748Z n (int, float, inf, -inf, 'fro', 'nuc'): See documentation of valid 2025-08-26T19:56:09.3144913Z entries for argument ``p`` in :func:`torch.norm`. 2025-08-26T19:56:09.3145116Z dim (int): index of the dim along which we define channels to prune. 2025-08-26T19:56:09.3145370Z importance_scores (torch.Tensor): tensor of importance scores (of same 2025-08-26T19:56:09.3145562Z shape as module parameter) used to compute mask for pruning. 2025-08-26T19:56:09.3145799Z The values in this tensor indicate the importance of the corresponding 2025-08-26T19:56:09.3145934Z elements in the parameter being pruned. 2025-08-26T19:56:09.3146165Z If unspecified or None, the module parameter will be used in its place. 2025-08-26T19:56:09.3146260Z 2025-08-26T19:56:09.3146345Z Returns: 2025-08-26T19:56:09.3146578Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T19:56:09.3146662Z 2025-08-26T19:56:09.3146750Z Examples: 2025-08-26T19:56:09.3146891Z >>> from torch.nn.utils import prune 2025-08-26T19:56:09.3147001Z >>> m = prune.ln_structured( 2025-08-26T19:56:09.3147198Z ... nn.Conv2d(5, 3, 2), "weight", amount=0.3, dim=1, n=float("-inf") 2025-08-26T19:56:09.3147285Z ... ) 2025-08-26T19:56:09.3147366Z 2025-08-26T19:56:09.3147635Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3147715Z 2025-08-26T19:56:09.3147824Z warnings.warn(msg) 2025-08-26T19:56:09.3147903Z 2025-08-26T19:56:09.3148107Z --- Parse Warning: 117 / 146 --- 2025-08-26T19:56:09.3149050Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=global_unstructured in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1026. 2025-08-26T19:56:09.3149319Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3149443Z 2025-08-26T19:56:09.3149886Z Globally prunes tensors corresponding to all parameters in ``parameters`` by applying the specified ``pruning_method``. 2025-08-26T19:56:09.3149966Z 2025-08-26T19:56:09.3150093Z Modifies modules in place by: 2025-08-26T19:56:09.3150174Z 2025-08-26T19:56:09.3150395Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T19:56:09.3150616Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T19:56:09.3150828Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T19:56:09.3151051Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T19:56:09.3151145Z ``name+'_orig'``. 2025-08-26T19:56:09.3151237Z 2025-08-26T19:56:09.3151323Z Args: 2025-08-26T19:56:09.3151527Z parameters (Iterable of (module, name) tuples): parameters of 2025-08-26T19:56:09.3151736Z the model to prune in a global fashion, i.e. by aggregating all 2025-08-26T19:56:09.3151978Z weights prior to deciding which ones to prune. module must be of 2025-08-26T19:56:09.3152145Z type :class:`nn.Module`, and name must be a string. 2025-08-26T19:56:09.3152369Z pruning_method (function): a valid pruning function from this module, 2025-08-26T19:56:09.3152545Z or a custom one implemented by the user that satisfies the 2025-08-26T19:56:09.3152788Z implementation guidelines and has ``PRUNING_TYPE='unstructured'``. 2025-08-26T19:56:09.3153050Z importance_scores (dict): a dictionary mapping (module, name) tuples to 2025-08-26T19:56:09.3153291Z the corresponding parameter's importance scores tensor. The tensor 2025-08-26T19:56:09.3153502Z should be the same shape as the parameter, and is used for computing 2025-08-26T19:56:09.3153601Z mask for pruning. 2025-08-26T19:56:09.3153846Z If unspecified or None, the parameter will be used in place of its 2025-08-26T19:56:09.3153952Z importance scores. 2025-08-26T19:56:09.3154094Z kwargs: other keyword arguments such as: 2025-08-26T19:56:09.3154290Z amount (int or float): quantity of parameters to prune across the 2025-08-26T19:56:09.3154393Z specified parameters. 2025-08-26T19:56:09.3154579Z If ``float``, should be between 0.0 and 1.0 and represent the 2025-08-26T19:56:09.3154783Z fraction of parameters to prune. If ``int``, it represents the 2025-08-26T19:56:09.3154925Z absolute number of parameters to prune. 2025-08-26T19:56:09.3155007Z 2025-08-26T19:56:09.3155092Z Raises: 2025-08-26T19:56:09.3155258Z TypeError: if ``PRUNING_TYPE != 'unstructured'`` 2025-08-26T19:56:09.3155338Z 2025-08-26T19:56:09.3155435Z Note: 2025-08-26T19:56:09.3155653Z Since global structured pruning doesn't make much sense unless the 2025-08-26T19:56:09.3155855Z norm is normalized by the size of the parameter, we now limit the 2025-08-26T19:56:09.3156018Z scope of global pruning to unstructured methods. 2025-08-26T19:56:09.3156098Z 2025-08-26T19:56:09.3156198Z Examples: 2025-08-26T19:56:09.3156318Z >>> from torch.nn.utils import prune 2025-08-26T19:56:09.3156444Z >>> from collections import OrderedDict 2025-08-26T19:56:09.3156556Z >>> net = nn.Sequential( 2025-08-26T19:56:09.3156649Z ... OrderedDict( 2025-08-26T19:56:09.3156738Z ... [ 2025-08-26T19:56:09.3156874Z ... ("first", nn.Linear(10, 4)), 2025-08-26T19:56:09.3156995Z ... ("second", nn.Linear(4, 1)), 2025-08-26T19:56:09.3157092Z ... ] 2025-08-26T19:56:09.3157175Z ... ) 2025-08-26T19:56:09.3157259Z ... ) 2025-08-26T19:56:09.3157374Z >>> parameters_to_prune = ( 2025-08-26T19:56:09.3157477Z ... (net.first, "weight"), 2025-08-26T19:56:09.3157626Z ... (net.second, "weight"), 2025-08-26T19:56:09.3163286Z ... ) 2025-08-26T19:56:09.3163455Z >>> prune.global_unstructured( 2025-08-26T19:56:09.3163582Z ... parameters_to_prune, 2025-08-26T19:56:09.3163724Z ... pruning_method=prune.L1Unstructured, 2025-08-26T19:56:09.3163818Z ... amount=10, 2025-08-26T19:56:09.3163915Z ... ) 2025-08-26T19:56:09.3164147Z >>> print(sum(torch.nn.utils.parameters_to_vector(net.buffers()) == 0)) 2025-08-26T19:56:09.3164250Z tensor(10) 2025-08-26T19:56:09.3164332Z 2025-08-26T19:56:09.3164420Z 2025-08-26T19:56:09.3164699Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3164782Z 2025-08-26T19:56:09.3164894Z warnings.warn(msg) 2025-08-26T19:56:09.3164975Z 2025-08-26T19:56:09.3165216Z --- Parse Warning: 118 / 146 --- 2025-08-26T19:56:09.3166146Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=custom_from_mask in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/prune.py line=1149. 2025-08-26T19:56:09.3166516Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3166933Z Prune tensor corresponding to parameter called ``name`` in ``module`` by applying the pre-computed mask in ``mask``. 2025-08-26T19:56:09.3167016Z 2025-08-26T19:56:09.3167232Z Modifies module in place (and also return the modified module) by: 2025-08-26T19:56:09.3167329Z 2025-08-26T19:56:09.3167576Z 1) adding a named buffer called ``name+'_mask'`` corresponding to the 2025-08-26T19:56:09.3167813Z binary mask applied to the parameter ``name`` by the pruning method. 2025-08-26T19:56:09.3168027Z 2) replacing the parameter ``name`` by its pruned version, while the 2025-08-26T19:56:09.3168277Z original (unpruned) parameter is stored in a new parameter named 2025-08-26T19:56:09.3168392Z ``name+'_orig'``. 2025-08-26T19:56:09.3168474Z 2025-08-26T19:56:09.3168576Z Args: 2025-08-26T19:56:09.3168761Z module (nn.Module): module containing the tensor to prune 2025-08-26T19:56:09.3169042Z name (str): parameter name within ``module`` on which pruning 2025-08-26T19:56:09.3169149Z will act. 2025-08-26T19:56:09.3169329Z mask (Tensor): binary mask to be applied to the parameter. 2025-08-26T19:56:09.3169423Z 2025-08-26T19:56:09.3169510Z Returns: 2025-08-26T19:56:09.3169737Z module (nn.Module): modified (i.e. pruned) version of the input module 2025-08-26T19:56:09.3169830Z 2025-08-26T19:56:09.3169918Z Examples: 2025-08-26T19:56:09.3170056Z >>> from torch.nn.utils import prune 2025-08-26T19:56:09.3170173Z >>> m = prune.custom_from_mask( 2025-08-26T19:56:09.3170352Z ... nn.Linear(5, 3), name="bias", mask=torch.tensor([0, 1, 0]) 2025-08-26T19:56:09.3170455Z ... ) 2025-08-26T19:56:09.3170557Z >>> print(m.bias_mask) 2025-08-26T19:56:09.3170653Z tensor([0., 1., 0.]) 2025-08-26T19:56:09.3170748Z 2025-08-26T19:56:09.3170833Z 2025-08-26T19:56:09.3171104Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3171183Z 2025-08-26T19:56:09.3171281Z warnings.warn(msg) 2025-08-26T19:56:09.3171371Z 2025-08-26T19:56:09.3171578Z --- Parse Warning: 119 / 146 --- 2025-08-26T19:56:09.3172502Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=pad_packed_sequence in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/rnn.py line=350. 2025-08-26T19:56:09.3172770Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3172922Z Pad a packed batch of variable length sequences. 2025-08-26T19:56:09.3173051Z 2025-08-26T19:56:09.3173232Z It is an inverse operation to :func:`pack_padded_sequence`. 2025-08-26T19:56:09.3173325Z 2025-08-26T19:56:09.3173609Z The returned Tensor's data will be of size ``T x B x *`` (if :attr:`batch_first` is ``False``) 2025-08-26T19:56:09.3173854Z or ``B x T x *`` (if :attr:`batch_first` is ``True``) , where ``T`` is the length of the longest 2025-08-26T19:56:09.3173984Z sequence and ``B`` is the batch size. 2025-08-26T19:56:09.3174064Z 2025-08-26T19:56:09.3174161Z Example: 2025-08-26T19:56:09.3174408Z >>> from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence 2025-08-26T19:56:09.3174559Z >>> seq = torch.tensor([[1, 2, 0], [3, 0, 0], [4, 5, 6]]) 2025-08-26T19:56:09.3174671Z >>> lens = [2, 1, 3] 2025-08-26T19:56:09.3174790Z >>> packed = pack_padded_sequence( 2025-08-26T19:56:09.3174956Z ... seq, lens, batch_first=True, enforce_sorted=False 2025-08-26T19:56:09.3175071Z ... ) 2025-08-26T19:56:09.3175161Z >>> packed 2025-08-26T19:56:09.3175418Z PackedSequence(data=tensor([4, 1, 3, 5, 2, 6]), batch_sizes=tensor([3, 2, 1]), 2025-08-26T19:56:09.3175642Z sorted_indices=tensor([2, 0, 1]), unsorted_indices=tensor([1, 2, 0])) 2025-08-26T19:56:09.3175903Z >>> seq_unpacked, lens_unpacked = pad_packed_sequence(packed, batch_first=True) 2025-08-26T19:56:09.3176001Z >>> seq_unpacked 2025-08-26T19:56:09.3176098Z tensor([[1, 2, 0], 2025-08-26T19:56:09.3176226Z [3, 0, 0], 2025-08-26T19:56:09.3176318Z [4, 5, 6]]) 2025-08-26T19:56:09.3176426Z >>> lens_unpacked 2025-08-26T19:56:09.3176521Z tensor([2, 1, 3]) 2025-08-26T19:56:09.3176605Z 2025-08-26T19:56:09.3176709Z .. note:: 2025-08-26T19:56:09.3176887Z :attr:`total_length` is useful to implement the 2025-08-26T19:56:09.3177131Z ``pack sequence -> recurrent network -> unpack sequence`` pattern in a 2025-08-26T19:56:09.3177355Z :class:`~torch.nn.Module` wrapped in :class:`~torch.nn.DataParallel`. 2025-08-26T19:56:09.3177592Z See :ref:`this FAQ section ` for 2025-08-26T19:56:09.3177692Z details. 2025-08-26T19:56:09.3177775Z 2025-08-26T19:56:09.3177872Z Args: 2025-08-26T19:56:09.3178006Z sequence (PackedSequence): batch to pad 2025-08-26T19:56:09.3178250Z batch_first (bool, optional): if ``True``, the output will be in ``B x T x *`` 2025-08-26T19:56:09.3178376Z format, ``T x B x *`` otherwise. 2025-08-26T19:56:09.3178573Z padding_value (float, optional): values for padded elements. 2025-08-26T19:56:09.3178814Z total_length (int, optional): if not ``None``, the output will be padded to 2025-08-26T19:56:09.3179060Z have length :attr:`total_length`. This method will throw :class:`ValueError` 2025-08-26T19:56:09.3179253Z if :attr:`total_length` is less than the max sequence length in 2025-08-26T19:56:09.3179364Z :attr:`sequence`. 2025-08-26T19:56:09.3179447Z 2025-08-26T19:56:09.3179546Z Returns: 2025-08-26T19:56:09.3179740Z Tuple of Tensor containing the padded sequence, and a Tensor 2025-08-26T19:56:09.3179942Z containing the list of lengths of each sequence in the batch. 2025-08-26T19:56:09.3180183Z Batch elements will be re-ordered as they were ordered originally when 2025-08-26T19:56:09.3180402Z the batch was passed to ``pack_padded_sequence`` or ``pack_sequence``. 2025-08-26T19:56:09.3180500Z 2025-08-26T19:56:09.3180757Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3180837Z 2025-08-26T19:56:09.3180947Z warnings.warn(msg) 2025-08-26T19:56:09.3181028Z 2025-08-26T19:56:09.3181256Z --- Parse Warning: 120 / 146 --- 2025-08-26T19:56:09.3182191Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SequentialLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=808. 2025-08-26T19:56:09.3182457Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3182800Z Contains a list of schedulers expected to be called sequentially during the optimization process. 2025-08-26T19:56:09.3182882Z 2025-08-26T19:56:09.3183273Z Specifically, the schedulers will be called according to the milestone points, which should provide exact 2025-08-26T19:56:09.3183496Z intervals by which each scheduler should be called at a given epoch. 2025-08-26T19:56:09.3183577Z 2025-08-26T19:56:09.3183675Z Args: 2025-08-26T19:56:09.3183817Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:09.3183980Z schedulers (list): List of chained schedulers. 2025-08-26T19:56:09.3184226Z milestones (list): List of integers that reflects milestone points. 2025-08-26T19:56:09.3184393Z last_epoch (int): The index of last epoch. Default: -1. 2025-08-26T19:56:09.3184482Z 2025-08-26T19:56:09.3184569Z Example: 2025-08-26T19:56:09.3184680Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3184835Z >>> # Assuming optimizer uses lr = 0.05 for all groups 2025-08-26T19:56:09.3184944Z >>> # lr = 0.005 if epoch == 0 2025-08-26T19:56:09.3185119Z >>> # lr = 0.005 if epoch == 1 2025-08-26T19:56:09.3185226Z >>> # lr = 0.005 if epoch == 2 2025-08-26T19:56:09.3185325Z >>> # ... 2025-08-26T19:56:09.3185435Z >>> # lr = 0.05 if epoch == 20 2025-08-26T19:56:09.3185542Z >>> # lr = 0.045 if epoch == 21 2025-08-26T19:56:09.3185690Z >>> # lr = 0.0405 if epoch == 22 2025-08-26T19:56:09.3185900Z >>> scheduler1 = ConstantLR(optimizer, factor=0.1, total_iters=20) 2025-08-26T19:56:09.3186072Z >>> scheduler2 = ExponentialLR(optimizer, gamma=0.9) 2025-08-26T19:56:09.3186182Z >>> scheduler = SequentialLR( 2025-08-26T19:56:09.3186277Z ... optimizer, 2025-08-26T19:56:09.3186425Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T19:56:09.3186526Z ... milestones=[20], 2025-08-26T19:56:09.3186610Z ... ) 2025-08-26T19:56:09.3186727Z >>> for epoch in range(100): 2025-08-26T19:56:09.3186823Z >>> train(...) 2025-08-26T19:56:09.3186928Z >>> validate(...) 2025-08-26T19:56:09.3187030Z >>> scheduler.step() 2025-08-26T19:56:09.3187112Z 2025-08-26T19:56:09.3187305Z .. image:: ../scripts/lr_scheduler_images/SequentialLR.png 2025-08-26T19:56:09.3187386Z 2025-08-26T19:56:09.3187655Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3187740Z 2025-08-26T19:56:09.3187839Z warnings.warn(msg) 2025-08-26T19:56:09.3187928Z 2025-08-26T19:56:09.3188121Z --- Parse Warning: 121 / 146 --- 2025-08-26T19:56:09.3189090Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ReduceLROnPlateau in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1233. 2025-08-26T19:56:09.3189346Z Caused by: DoctestParseError('Failed to parse doctest in _package_groups') 2025-08-26T19:56:09.3189536Z Reduce learning rate when a metric has stopped improving. 2025-08-26T19:56:09.3189629Z 2025-08-26T19:56:09.3189838Z Models often benefit from reducing the learning rate by a factor 2025-08-26T19:56:09.3190041Z of 2-10 once learning stagnates. This scheduler reads a metrics 2025-08-26T19:56:09.3190241Z quantity and if no improvement is seen for a 'patience' number 2025-08-26T19:56:09.3190403Z of epochs, the learning rate is reduced. 2025-08-26T19:56:09.3190492Z 2025-08-26T19:56:09.3190578Z Args: 2025-08-26T19:56:09.3190730Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:09.3190888Z mode (str): One of `min`, `max`. In `min` mode, lr will 2025-08-26T19:56:09.3191050Z be reduced when the quantity monitored has stopped 2025-08-26T19:56:09.3191230Z decreasing; in `max` mode it will be reduced when the 2025-08-26T19:56:09.3191427Z quantity monitored has stopped increasing. Default: 'min'. 2025-08-26T19:56:09.3191611Z factor (float): Factor by which the learning rate will be 2025-08-26T19:56:09.3191750Z reduced. new_lr = lr * factor. Default: 0.1. 2025-08-26T19:56:09.3191972Z patience (int): The number of allowed epochs with no improvement after 2025-08-26T19:56:09.3192113Z which the learning rate will be reduced. 2025-08-26T19:56:09.3192373Z For example, consider the case of having no patience (`patience = 0`). 2025-08-26T19:56:09.3192758Z In the first epoch, a baseline is established and is always considered good as there's no previous baseline. 2025-08-26T19:56:09.3192966Z In the second epoch, if the performance is worse than the baseline, 2025-08-26T19:56:09.3193128Z we have what is considered an intolerable epoch. 2025-08-26T19:56:09.3193397Z Since the count of intolerable epochs (1) is greater than the patience level (0), 2025-08-26T19:56:09.3193596Z the learning rate is reduced at the end of this epoch. 2025-08-26T19:56:09.3193940Z From the third epoch onwards, the learning rate continues to be reduced at the end of each epoch 2025-08-26T19:56:09.3194262Z if the performance is worse than the baseline. If the performance improves or remains the same, 2025-08-26T19:56:09.3194425Z the learning rate is not adjusted. 2025-08-26T19:56:09.3194524Z Default: 10. 2025-08-26T19:56:09.3194717Z threshold (float): Threshold for measuring the new optimum, 2025-08-26T19:56:09.3194894Z to only focus on significant changes. Default: 1e-4. 2025-08-26T19:56:09.3195069Z threshold_mode (str): One of `rel`, `abs`. In `rel` mode, 2025-08-26T19:56:09.3195239Z dynamic_threshold = best * ( 1 + threshold ) in 'max' 2025-08-26T19:56:09.3195383Z mode or best * ( 1 - threshold ) in `min` mode. 2025-08-26T19:56:09.3195545Z In `abs` mode, dynamic_threshold = best + threshold in 2025-08-26T19:56:09.3195742Z `max` mode or best - threshold in `min` mode. Default: 'rel'. 2025-08-26T19:56:09.3195918Z cooldown (int): Number of epochs to wait before resuming 2025-08-26T19:56:09.3196113Z normal operation after lr has been reduced. Default: 0. 2025-08-26T19:56:09.3196281Z min_lr (float or list): A scalar or a list of scalars. A 2025-08-26T19:56:09.3196448Z lower bound on the learning rate of all param groups 2025-08-26T19:56:09.3196598Z or each group respectively. Default: 0. 2025-08-26T19:56:09.3196780Z eps (float): Minimal decay applied to lr. If the difference 2025-08-26T19:56:09.3196975Z between new and old lr is smaller than eps, the update is 2025-08-26T19:56:09.3197088Z ignored. Default: 1e-8. 2025-08-26T19:56:09.3197169Z 2025-08-26T19:56:09.3197270Z Example: 2025-08-26T19:56:09.3197374Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3197620Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T19:56:09.3197781Z >>> scheduler = ReduceLROnPlateau(optimizer, "min") 2025-08-26T19:56:09.3197890Z >>> for epoch in range(10): 2025-08-26T19:56:09.3197999Z >>> train(...) 2025-08-26T19:56:09.3198147Z >>> val_loss = validate(...) 2025-08-26T19:56:09.3198311Z >>> # Note that step should be called after validate() 2025-08-26T19:56:09.3198426Z >>> scheduler.step(val_loss) 2025-08-26T19:56:09.3198504Z 2025-08-26T19:56:09.3198712Z .. image:: ../scripts/lr_scheduler_images/ReduceLROnPlateau.png 2025-08-26T19:56:09.3198796Z 2025-08-26T19:56:09.3199232Z Original Error: IndentationError('unexpected indent', ('', 8, 4, ' scheduler.step(val_loss)\n', 8, -1)) 2025-08-26T19:56:09.3199314Z 2025-08-26T19:56:09.3199425Z scheduler.step(val_loss) 2025-08-26T19:56:09.3199519Z ^ 2025-08-26T19:56:09.3199617Z warnings.warn(msg) 2025-08-26T19:56:09.3199709Z 2025-08-26T19:56:09.3199905Z --- Parse Warning: 122 / 146 --- 2025-08-26T19:56:09.3200808Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CyclicLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1430. 2025-08-26T19:56:09.3201118Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3201451Z Sets the learning rate of each parameter group according to cyclical learning rate policy (CLR). 2025-08-26T19:56:09.3201544Z 2025-08-26T19:56:09.3201832Z The policy cycles the learning rate between two boundaries with a constant frequency, 2025-08-26T19:56:09.3202095Z as detailed in the paper `Cyclical Learning Rates for Training Neural Networks`_. 2025-08-26T19:56:09.3202371Z The distance between the two boundaries can be scaled on a per-iteration 2025-08-26T19:56:09.3202475Z or per-cycle basis. 2025-08-26T19:56:09.3202570Z 2025-08-26T19:56:09.3202821Z Cyclical learning rate policy changes the learning rate after every batch. 2025-08-26T19:56:09.3203045Z `step` should be called after a batch has been used for training. 2025-08-26T19:56:09.3203139Z 2025-08-26T19:56:09.3203350Z This class has three built-in policies, as put forth in the paper: 2025-08-26T19:56:09.3203443Z 2025-08-26T19:56:09.3203651Z * "triangular": A basic triangular cycle without amplitude scaling. 2025-08-26T19:56:09.3203954Z * "triangular2": A basic triangular cycle that scales initial amplitude by half each cycle. 2025-08-26T19:56:09.3204293Z * "exp_range": A cycle that scales initial amplitude by :math:`\text{gamma}^{\text{cycle iterations}}` 2025-08-26T19:56:09.3204404Z at each cycle iteration. 2025-08-26T19:56:09.3204499Z 2025-08-26T19:56:09.3204743Z This implementation was adapted from the github repo: `bckenstler/CLR`_ 2025-08-26T19:56:09.3204822Z 2025-08-26T19:56:09.3204916Z Args: 2025-08-26T19:56:09.3205059Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:09.3205249Z base_lr (float or list): Initial learning rate which is the 2025-08-26T19:56:09.3205421Z lower boundary in the cycle for each parameter group. 2025-08-26T19:56:09.3205624Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T19:56:09.3205766Z for each parameter group. Functionally, 2025-08-26T19:56:09.3205924Z it defines the cycle amplitude (max_lr - base_lr). 2025-08-26T19:56:09.3206066Z The lr at any cycle is the sum of base_lr 2025-08-26T19:56:09.3206209Z and some scaling of the amplitude; therefore 2025-08-26T19:56:09.3206367Z max_lr may not actually be reached depending on 2025-08-26T19:56:09.3206480Z scaling function. 2025-08-26T19:56:09.3206653Z step_size_up (int): Number of training iterations in the 2025-08-26T19:56:09.3206797Z increasing half of a cycle. Default: 2000 2025-08-26T19:56:09.3206975Z step_size_down (int): Number of training iterations in the 2025-08-26T19:56:09.3207174Z decreasing half of a cycle. If step_size_down is None, 2025-08-26T19:56:09.3207316Z it is set to step_size_up. Default: None 2025-08-26T19:56:09.3207483Z mode (str): One of {triangular, triangular2, exp_range}. 2025-08-26T19:56:09.3207647Z Values correspond to policies detailed above. 2025-08-26T19:56:09.3207799Z If scale_fn is not None, this argument is ignored. 2025-08-26T19:56:09.3207907Z Default: 'triangular' 2025-08-26T19:56:09.3208084Z gamma (float): Constant in 'exp_range' scaling function: 2025-08-26T19:56:09.3208195Z gamma**(cycle iterations) 2025-08-26T19:56:09.3208301Z Default: 1.0 2025-08-26T19:56:09.3208490Z scale_fn (function): Custom scaling policy defined by a single 2025-08-26T19:56:09.3208609Z argument lambda function, where 2025-08-26T19:56:09.3208743Z 0 <= scale_fn(x) <= 1 for all x >= 0. 2025-08-26T19:56:09.3208952Z If specified, then 'mode' is ignored. 2025-08-26T19:56:09.3209097Z Default: None 2025-08-26T19:56:09.3209225Z scale_mode (str): {'cycle', 'iterations'}. 2025-08-26T19:56:09.3209357Z Defines whether scale_fn is evaluated on 2025-08-26T19:56:09.3209504Z cycle number or cycle iterations (training 2025-08-26T19:56:09.3209624Z iterations since start of cycle). 2025-08-26T19:56:09.3209737Z Default: 'cycle' 2025-08-26T19:56:09.3209966Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T19:56:09.3210160Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T19:56:09.3210272Z Default: True 2025-08-26T19:56:09.3210494Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T19:56:09.3210743Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T19:56:09.3210911Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T19:56:09.3211059Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T19:56:09.3211169Z Default: 0.8 2025-08-26T19:56:09.3211385Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T19:56:09.3211531Z for each parameter group. Functionally, 2025-08-26T19:56:09.3211725Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T19:56:09.3211924Z The momentum at any cycle is the difference of max_momentum 2025-08-26T19:56:09.3212066Z and some scaling of the amplitude; therefore 2025-08-26T19:56:09.3212240Z base_momentum may not actually be reached depending on 2025-08-26T19:56:09.3212433Z scaling function. Note that momentum is cycled inversely 2025-08-26T19:56:09.3212649Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T19:56:09.3212780Z and learning rate is 'base_lr' 2025-08-26T19:56:09.3212873Z Default: 0.9 2025-08-26T19:56:09.3213097Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T19:56:09.3213328Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T19:56:09.3213547Z batch instead of after each epoch, this number represents the total 2025-08-26T19:56:09.3213785Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T19:56:09.3213981Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T19:56:09.3214075Z Default: -1 2025-08-26T19:56:09.3214166Z 2025-08-26T19:56:09.3214252Z Example: 2025-08-26T19:56:09.3214362Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3214595Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.1, momentum=0.9) 2025-08-26T19:56:09.3214779Z >>> scheduler = torch.optim.lr_scheduler.CyclicLR( 2025-08-26T19:56:09.3214885Z ... optimizer, 2025-08-26T19:56:09.3214979Z ... base_lr=0.01, 2025-08-26T19:56:09.3215082Z ... max_lr=0.1, 2025-08-26T19:56:09.3215182Z ... step_size_up=10, 2025-08-26T19:56:09.3215265Z ... ) 2025-08-26T19:56:09.3215429Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T19:56:09.3215534Z >>> for epoch in range(10): 2025-08-26T19:56:09.3215647Z >>> for batch in data_loader: 2025-08-26T19:56:09.3215761Z >>> train_batch(...) 2025-08-26T19:56:09.3215863Z >>> scheduler.step() 2025-08-26T19:56:09.3215955Z 2025-08-26T19:56:09.3216118Z .. image:: ../scripts/lr_scheduler_images/CyclicLR.png 2025-08-26T19:56:09.3216199Z 2025-08-26T19:56:09.3216524Z .. _Cyclical Learning Rates for Training Neural Networks: https://arxiv.org/abs/1506.01186 2025-08-26T19:56:09.3216720Z .. _bckenstler/CLR: https://github.com/bckenstler/CLR 2025-08-26T19:56:09.3216816Z 2025-08-26T19:56:09.3217073Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3217153Z 2025-08-26T19:56:09.3217264Z warnings.warn(msg) 2025-08-26T19:56:09.3217343Z 2025-08-26T19:56:09.3217568Z --- Parse Warning: 123 / 146 --- 2025-08-26T19:56:09.3218613Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CosineAnnealingWarmRestarts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1722. 2025-08-26T19:56:09.3218881Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3219153Z Set the learning rate of each parameter group using a cosine annealing schedule. 2025-08-26T19:56:09.3219261Z 2025-08-26T19:56:09.3219459Z The :math:`\eta_{max}` is set to the initial lr, :math:`T_{cur}` 2025-08-26T19:56:09.3219702Z is the number of epochs since the last restart and :math:`T_{i}` is the number 2025-08-26T19:56:09.3219842Z of epochs between two warm restarts in SGDR: 2025-08-26T19:56:09.3219933Z 2025-08-26T19:56:09.3220022Z .. math:: 2025-08-26T19:56:09.3220215Z \eta_t = \eta_{min} + \frac{1}{2}(\eta_{max} - \eta_{min})\left(1 + 2025-08-26T19:56:09.3220358Z \cos\left(\frac{T_{cur}}{T_{i}}\pi\right)\right) 2025-08-26T19:56:09.3220437Z 2025-08-26T19:56:09.3220622Z When :math:`T_{cur}=T_{i}`, set :math:`\eta_t = \eta_{min}`. 2025-08-26T19:56:09.3220813Z When :math:`T_{cur}=0` after restart, set :math:`\eta_t=\eta_{max}`. 2025-08-26T19:56:09.3220909Z 2025-08-26T19:56:09.3221016Z It has been proposed in 2025-08-26T19:56:09.3221190Z `SGDR: Stochastic Gradient Descent with Warm Restarts`_. 2025-08-26T19:56:09.3221288Z 2025-08-26T19:56:09.3221376Z Args: 2025-08-26T19:56:09.3221523Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:09.3221685Z T_0 (int): Number of iterations until the first restart. 2025-08-26T19:56:09.3221973Z T_mult (int, optional): A factor by which :math:`T_{i}` increases after a restart. Default: 1. 2025-08-26T19:56:09.3222175Z eta_min (float, optional): Minimum learning rate. Default: 0. 2025-08-26T19:56:09.3222391Z last_epoch (int, optional): The index of the last epoch. Default: -1. 2025-08-26T19:56:09.3222486Z 2025-08-26T19:56:09.3222659Z .. _SGDR\: Stochastic Gradient Descent with Warm Restarts: 2025-08-26T19:56:09.3222780Z https://arxiv.org/abs/1608.03983 2025-08-26T19:56:09.3222873Z 2025-08-26T19:56:09.3222961Z Example: 2025-08-26T19:56:09.3223073Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3223263Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=0.05) 2025-08-26T19:56:09.3223527Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingWarmRestarts( 2025-08-26T19:56:09.3223641Z ... optimizer, T_0=20 2025-08-26T19:56:09.3223724Z ... ) 2025-08-26T19:56:09.3223840Z >>> for epoch in range(100): 2025-08-26T19:56:09.3223934Z >>> train(...) 2025-08-26T19:56:09.3224028Z >>> validate(...) 2025-08-26T19:56:09.3224143Z >>> scheduler.step() 2025-08-26T19:56:09.3224222Z 2025-08-26T19:56:09.3224474Z .. image:: ../scripts/lr_scheduler_images/CosineAnnealingWarmRestarts.png 2025-08-26T19:56:09.3224557Z 2025-08-26T19:56:09.3224809Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3224901Z 2025-08-26T19:56:09.3225000Z warnings.warn(msg) 2025-08-26T19:56:09.3225080Z 2025-08-26T19:56:09.3225292Z --- Parse Warning: 124 / 146 --- 2025-08-26T19:56:09.3226213Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=OneCycleLR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/lr_scheduler.py line=1872. 2025-08-26T19:56:09.3226521Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3226830Z Sets the learning rate of each parameter group according to the 1cycle learning rate policy. 2025-08-26T19:56:09.3226919Z 2025-08-26T19:56:09.3227242Z The 1cycle policy anneals the learning rate from an initial learning rate to some maximum 2025-08-26T19:56:09.3227537Z learning rate and then from that maximum learning rate to some minimum learning rate much 2025-08-26T19:56:09.3227664Z lower than the initial learning rate. 2025-08-26T19:56:09.3227891Z This policy was initially described in the paper `Super-Convergence: 2025-08-26T19:56:09.3228148Z Very Fast Training of Neural Networks Using Large Learning Rates`_. 2025-08-26T19:56:09.3228229Z 2025-08-26T19:56:09.3228475Z The 1cycle learning rate policy changes the learning rate after every batch. 2025-08-26T19:56:09.3228678Z `step` should be called after a batch has been used for training. 2025-08-26T19:56:09.3228756Z 2025-08-26T19:56:09.3228874Z This scheduler is not chainable. 2025-08-26T19:56:09.3228952Z 2025-08-26T19:56:09.3229192Z Note also that the total number of steps in the cycle can be determined in one 2025-08-26T19:56:09.3229338Z of two ways (listed in order of precedence): 2025-08-26T19:56:09.3229417Z 2025-08-26T19:56:09.3229575Z #. A value for total_steps is explicitly provided. 2025-08-26T19:56:09.3229758Z #. A number of epochs (epochs) and a number of steps per epoch 2025-08-26T19:56:09.3229872Z (steps_per_epoch) are provided. 2025-08-26T19:56:09.3230044Z In this case, the number of total steps is inferred by 2025-08-26T19:56:09.3230170Z total_steps = epochs * steps_per_epoch 2025-08-26T19:56:09.3230260Z 2025-08-26T19:56:09.3230500Z You must either provide a value for total_steps or provide a value for both 2025-08-26T19:56:09.3230605Z epochs and steps_per_epoch. 2025-08-26T19:56:09.3230692Z 2025-08-26T19:56:09.3231001Z The default behaviour of this scheduler follows the fastai implementation of 1cycle, which 2025-08-26T19:56:09.3231303Z claims that "unpublished work has shown even better results by using only two phases". To 2025-08-26T19:56:09.3231548Z mimic the behaviour of the original paper instead, set ``three_phase=True``. 2025-08-26T19:56:09.3231627Z 2025-08-26T19:56:09.3231720Z Args: 2025-08-26T19:56:09.3231857Z optimizer (Optimizer): Wrapped optimizer. 2025-08-26T19:56:09.3232068Z max_lr (float or list): Upper learning rate boundaries in the cycle 2025-08-26T19:56:09.3232180Z for each parameter group. 2025-08-26T19:56:09.3232414Z total_steps (int): The total number of steps in the cycle. Note that 2025-08-26T19:56:09.3232634Z if a value is not provided here, then it must be inferred by providing 2025-08-26T19:56:09.3232765Z a value for epochs and steps_per_epoch. 2025-08-26T19:56:09.3232867Z Default: None 2025-08-26T19:56:09.3233067Z epochs (int): The number of epochs to train for. This is used along 2025-08-26T19:56:09.3233313Z with steps_per_epoch in order to infer the total number of steps in the cycle 2025-08-26T19:56:09.3233459Z if a value for total_steps is not provided. 2025-08-26T19:56:09.3233555Z Default: None 2025-08-26T19:56:09.3233786Z steps_per_epoch (int): The number of steps per epoch to train for. This is 2025-08-26T19:56:09.3234014Z used along with epochs in order to infer the total number of steps in the 2025-08-26T19:56:09.3234167Z cycle if a value for total_steps is not provided. 2025-08-26T19:56:09.3234298Z Default: None 2025-08-26T19:56:09.3234528Z pct_start (float): The percentage of the cycle (in number of steps) spent 2025-08-26T19:56:09.3234648Z increasing the learning rate. 2025-08-26T19:56:09.3234737Z Default: 0.3 2025-08-26T19:56:09.3234865Z anneal_strategy (str): {'cos', 'linear'} 2025-08-26T19:56:09.3235123Z Specifies the annealing strategy: "cos" for cosine annealing, "linear" for 2025-08-26T19:56:09.3235220Z linear annealing. 2025-08-26T19:56:09.3235350Z Default: 'cos' 2025-08-26T19:56:09.3235548Z cycle_momentum (bool): If ``True``, momentum is cycled inversely 2025-08-26T19:56:09.3235735Z to learning rate between 'base_momentum' and 'max_momentum'. 2025-08-26T19:56:09.3235838Z Default: True 2025-08-26T19:56:09.3236082Z base_momentum (float or list): Lower momentum boundaries in the cycle 2025-08-26T19:56:09.3236300Z for each parameter group. Note that momentum is cycled inversely 2025-08-26T19:56:09.3236459Z to learning rate; at the peak of a cycle, momentum is 2025-08-26T19:56:09.3236602Z 'base_momentum' and learning rate is 'max_lr'. 2025-08-26T19:56:09.3236705Z Default: 0.85 2025-08-26T19:56:09.3236922Z max_momentum (float or list): Upper momentum boundaries in the cycle 2025-08-26T19:56:09.3237059Z for each parameter group. Functionally, 2025-08-26T19:56:09.3237259Z it defines the cycle amplitude (max_momentum - base_momentum). 2025-08-26T19:56:09.3237549Z Note that momentum is cycled inversely 2025-08-26T19:56:09.3237767Z to learning rate; at the start of a cycle, momentum is 'max_momentum' 2025-08-26T19:56:09.3237880Z and learning rate is 'base_lr' 2025-08-26T19:56:09.3237984Z Default: 0.95 2025-08-26T19:56:09.3238172Z div_factor (float): Determines the initial learning rate via 2025-08-26T19:56:09.3238285Z initial_lr = max_lr/div_factor 2025-08-26T19:56:09.3238382Z Default: 25 2025-08-26T19:56:09.3238589Z final_div_factor (float): Determines the minimum learning rate via 2025-08-26T19:56:09.3238719Z min_lr = initial_lr/final_div_factor 2025-08-26T19:56:09.3238810Z Default: 1e4 2025-08-26T19:56:09.3239057Z three_phase (bool): If ``True``, use a third phase of the schedule to annihilate the 2025-08-26T19:56:09.3239325Z learning rate according to 'final_div_factor' instead of modifying the second 2025-08-26T19:56:09.3239562Z phase (the first two phases will be symmetrical about the step indicated by 2025-08-26T19:56:09.3239663Z 'pct_start'). 2025-08-26T19:56:09.3239886Z last_epoch (int): The index of the last batch. This parameter is used when 2025-08-26T19:56:09.3240178Z resuming a training job. Since `step()` should be invoked after each 2025-08-26T19:56:09.3240401Z batch instead of after each epoch, this number represents the total 2025-08-26T19:56:09.3240625Z number of *batches* computed, not the total number of epochs computed. 2025-08-26T19:56:09.3240827Z When last_epoch=-1, the schedule is started from the beginning. 2025-08-26T19:56:09.3240920Z Default: -1 2025-08-26T19:56:09.3241010Z 2025-08-26T19:56:09.3241091Z Example: 2025-08-26T19:56:09.3241189Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3241349Z >>> data_loader = torch.utils.data.DataLoader(...) 2025-08-26T19:56:09.3241576Z >>> optimizer = torch.optim.SGD(model.parameters(), lr=1e-4, momentum=0.9) 2025-08-26T19:56:09.3241737Z >>> scheduler = torch.optim.lr_scheduler.OneCycleLR( 2025-08-26T19:56:09.3241959Z ... optimizer, max_lr=0.01, steps_per_epoch=len(data_loader), epochs=10 2025-08-26T19:56:09.3242080Z ... ) 2025-08-26T19:56:09.3242196Z >>> for epoch in range(10): 2025-08-26T19:56:09.3242303Z >>> for batch in data_loader: 2025-08-26T19:56:09.3242403Z >>> train_batch(...) 2025-08-26T19:56:09.3242516Z >>> optimizer.step() 2025-08-26T19:56:09.3242616Z >>> scheduler.step() 2025-08-26T19:56:09.3242702Z 2025-08-26T19:56:09.3242871Z .. image:: ../scripts/lr_scheduler_images/OneCycleLR.png 2025-08-26T19:56:09.3242948Z 2025-08-26T19:56:09.3243288Z .. _Super-Convergence\: Very Fast Training of Neural Networks Using Large Learning Rates: 2025-08-26T19:56:09.3243412Z https://arxiv.org/abs/1708.07120 2025-08-26T19:56:09.3243502Z 2025-08-26T19:56:09.3243757Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3243837Z 2025-08-26T19:56:09.3243976Z warnings.warn(msg) 2025-08-26T19:56:09.3244057Z 2025-08-26T19:56:09.3244280Z --- Parse Warning: 125 / 146 --- 2025-08-26T19:56:09.3245234Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=Optimizer.load_state_dict in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/optimizer.py line=867. 2025-08-26T19:56:09.3245502Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3245616Z Load the optimizer state. 2025-08-26T19:56:09.3245694Z 2025-08-26T19:56:09.3245793Z Args: 2025-08-26T19:56:09.3245993Z state_dict (dict): optimizer state. Should be an object returned 2025-08-26T19:56:09.3246117Z from a call to :meth:`state_dict`. 2025-08-26T19:56:09.3246206Z 2025-08-26T19:56:09.3246298Z .. warning:: 2025-08-26T19:56:09.3246648Z Make sure this method is called after initializing :class:`torch.optim.lr_scheduler.LRScheduler`, 2025-08-26T19:56:09.3246864Z as calling it beforehand will overwrite the loaded learning rates. 2025-08-26T19:56:09.3246944Z 2025-08-26T19:56:09.3247039Z .. note:: 2025-08-26T19:56:09.3247334Z The names of the parameters (if they exist under the "param_names" key of each param group 2025-08-26T19:56:09.3247517Z in :meth:`state_dict`) will not affect the loading process. 2025-08-26T19:56:09.3247845Z To use the parameters' names for custom cases (such as when the parameters in the loaded state dict 2025-08-26T19:56:09.3248001Z differ from those initialized in the optimizer), 2025-08-26T19:56:09.3248315Z a custom ``register_load_state_dict_pre_hook`` should be implemented to adapt the loaded dict 2025-08-26T19:56:09.3248407Z accordingly. 2025-08-26T19:56:09.3248710Z If ``param_names`` exist in loaded state dict ``param_groups`` they will be saved and override 2025-08-26T19:56:09.3249141Z the current names, if present, in the optimizer state. If they do not exist in loaded state dict, 2025-08-26T19:56:09.3249318Z the optimizer ``param_names`` will remain unchanged. 2025-08-26T19:56:09.3249395Z 2025-08-26T19:56:09.3249480Z Example: 2025-08-26T19:56:09.3249592Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3249711Z >>> model = torch.nn.Linear(10, 10) 2025-08-26T19:56:09.3249887Z >>> optim = torch.optim.SGD(model.parameters(), lr=3e-4) 2025-08-26T19:56:09.3250058Z >>> scheduler1 = torch.optim.lr_scheduler.LinearLR( 2025-08-26T19:56:09.3250146Z ... optim, 2025-08-26T19:56:09.3250258Z ... start_factor=0.1, 2025-08-26T19:56:09.3250351Z ... end_factor=1, 2025-08-26T19:56:09.3250448Z ... total_iters=20, 2025-08-26T19:56:09.3250542Z ... ) 2025-08-26T19:56:09.3250764Z >>> scheduler2 = torch.optim.lr_scheduler.CosineAnnealingLR( 2025-08-26T19:56:09.3250864Z ... optim, 2025-08-26T19:56:09.3250953Z ... T_max=80, 2025-08-26T19:56:09.3251048Z ... eta_min=3e-5, 2025-08-26T19:56:09.3251134Z ... ) 2025-08-26T19:56:09.3251278Z >>> lr = torch.optim.lr_scheduler.SequentialLR( 2025-08-26T19:56:09.3251380Z ... optim, 2025-08-26T19:56:09.3251512Z ... schedulers=[scheduler1, scheduler2], 2025-08-26T19:56:09.3251641Z ... milestones=[20], 2025-08-26T19:56:09.3251733Z ... ) 2025-08-26T19:56:09.3251879Z >>> lr.load_state_dict(torch.load("./save_seq.pt")) 2025-08-26T19:56:09.3252094Z >>> # now load the optimizer checkpoint after loading the LRScheduler 2025-08-26T19:56:09.3252287Z >>> optim.load_state_dict(torch.load("./save_optim.pt")) 2025-08-26T19:56:09.3252370Z 2025-08-26T19:56:09.3252462Z 2025-08-26T19:56:09.3252718Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3252808Z 2025-08-26T19:56:09.3252902Z warnings.warn(msg) 2025-08-26T19:56:09.3252979Z 2025-08-26T19:56:09.3253195Z --- Parse Warning: 126 / 146 --- 2025-08-26T19:56:09.3254103Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=AveragedModel in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=120. 2025-08-26T19:56:09.3254374Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3254742Z Implements averaged model for Stochastic Weight Averaging (SWA) and Exponential Moving Average (EMA). 2025-08-26T19:56:09.3254818Z 2025-08-26T19:56:09.3255076Z Stochastic Weight Averaging was proposed in `Averaging Weights Leads to 2025-08-26T19:56:09.3255297Z Wider Optima and Better Generalization`_ by Pavel Izmailov, Dmitrii 2025-08-26T19:56:09.3255527Z Podoprikhin, Timur Garipov, Dmitry Vetrov and Andrew Gordon Wilson 2025-08-26T19:56:09.3255609Z (UAI 2018). 2025-08-26T19:56:09.3255687Z 2025-08-26T19:56:09.3255911Z Exponential Moving Average is a variation of `Polyak averaging`_, 2025-08-26T19:56:09.3256155Z but using exponential weights instead of equal weights across iterations. 2025-08-26T19:56:09.3256241Z 2025-08-26T19:56:09.3256480Z AveragedModel class creates a copy of the provided module :attr:`model` 2025-08-26T19:56:09.3256703Z on the device :attr:`device` and allows to compute running averages of the 2025-08-26T19:56:09.3256817Z parameters of the :attr:`model`. 2025-08-26T19:56:09.3256893Z 2025-08-26T19:56:09.3256981Z Args: 2025-08-26T19:56:09.3257134Z model (torch.nn.Module): model to use with SWA/EMA 2025-08-26T19:56:09.3257405Z device (torch.device, optional): if provided, the averaged model will be 2025-08-26T19:56:09.3257524Z stored on the :attr:`device` 2025-08-26T19:56:09.3257726Z avg_fn (function, optional): the averaging function used to update 2025-08-26T19:56:09.3257936Z parameters; the function must take in the current value of the 2025-08-26T19:56:09.3258156Z :class:`AveragedModel` parameter, the current value of :attr:`model` 2025-08-26T19:56:09.3258355Z parameter, and the number of models already averaged; if None, 2025-08-26T19:56:09.3258522Z an equally weighted average is used (default: None) 2025-08-26T19:56:09.3258750Z multi_avg_fn (function, optional): the averaging function used to update 2025-08-26T19:56:09.3258999Z parameters inplace; the function must take in the current values of the 2025-08-26T19:56:09.3259270Z :class:`AveragedModel` parameters as a list, the current values of :attr:`model` 2025-08-26T19:56:09.3259527Z parameters as a list, and the number of models already averaged; if None, 2025-08-26T19:56:09.3259695Z an equally weighted average is used (default: None) 2025-08-26T19:56:09.3259900Z use_buffers (bool): if ``True``, it will compute running averages for 2025-08-26T19:56:09.3260133Z both the parameters and the buffers of the model. (default: ``False``) 2025-08-26T19:56:09.3260210Z 2025-08-26T19:56:09.3260296Z Example: 2025-08-26T19:56:09.3260473Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.3260602Z >>> loader, optimizer, model, loss_fn = ... 2025-08-26T19:56:09.3260778Z >>> swa_model = torch.optim.swa_utils.AveragedModel(model) 2025-08-26T19:56:09.3261003Z >>> scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, 2025-08-26T19:56:09.3261152Z >>> T_max=300) 2025-08-26T19:56:09.3261251Z >>> swa_start = 160 2025-08-26T19:56:09.3261391Z >>> swa_scheduler = SWALR(optimizer, swa_lr=0.05) 2025-08-26T19:56:09.3261500Z >>> for i in range(300): 2025-08-26T19:56:09.3261613Z >>> for input, target in loader: 2025-08-26T19:56:09.3261725Z >>> optimizer.zero_grad() 2025-08-26T19:56:09.3261868Z >>> loss_fn(model(input), target).backward() 2025-08-26T19:56:09.3261974Z >>> optimizer.step() 2025-08-26T19:56:09.3262083Z >>> if i > swa_start: 2025-08-26T19:56:09.3262211Z >>> swa_model.update_parameters(model) 2025-08-26T19:56:09.3262323Z >>> swa_scheduler.step() 2025-08-26T19:56:09.3262417Z >>> else: 2025-08-26T19:56:09.3262520Z >>> scheduler.step() 2025-08-26T19:56:09.3262611Z >>> 2025-08-26T19:56:09.3262769Z >>> # Update bn statistics for the swa_model at the end 2025-08-26T19:56:09.3262934Z >>> torch.optim.swa_utils.update_bn(loader, swa_model) 2025-08-26T19:56:09.3263024Z 2025-08-26T19:56:09.3263327Z You can also use custom averaging functions with the `avg_fn` or `multi_avg_fn` parameters. 2025-08-26T19:56:09.3263536Z If no averaging function is provided, the default is to compute 2025-08-26T19:56:09.3263683Z equally-weighted average of the weights (SWA). 2025-08-26T19:56:09.3263764Z 2025-08-26T19:56:09.3263853Z Example: 2025-08-26T19:56:09.3263985Z >>> # xdoctest: +SKIP("undefined variables") 2025-08-26T19:56:09.3264201Z >>> # Compute exponential moving averages of the weights and buffers 2025-08-26T19:56:09.3264370Z >>> ema_model = torch.optim.swa_utils.AveragedModel(model, 2025-08-26T19:56:09.3264590Z >>> torch.optim.swa_utils.get_ema_multi_avg_fn(0.9), use_buffers=True) 2025-08-26T19:56:09.3264704Z 2025-08-26T19:56:09.3264798Z .. note:: 2025-08-26T19:56:09.3265029Z When using SWA/EMA with models containing Batch Normalization you may 2025-08-26T19:56:09.3265232Z need to update the activation statistics for Batch Normalization. 2025-08-26T19:56:09.3265464Z This can be done either by using the :meth:`torch.optim.swa_utils.update_bn` 2025-08-26T19:56:09.3265702Z or by setting :attr:`use_buffers` to `True`. The first approach updates the 2025-08-26T19:56:09.3265942Z statistics in a post-training step by passing data through the model. The 2025-08-26T19:56:09.3266196Z second does it during the parameter update phase by averaging all buffers. 2025-08-26T19:56:09.3266440Z Empirical evidence has shown that updating the statistics in normalization 2025-08-26T19:56:09.3266675Z layers increases accuracy, but you may wish to empirically test which 2025-08-26T19:56:09.3266829Z approach yields the best results in your problem. 2025-08-26T19:56:09.3266935Z 2025-08-26T19:56:09.3267025Z .. note:: 2025-08-26T19:56:09.3267277Z :attr:`avg_fn` and `multi_avg_fn` are not saved in the :meth:`state_dict` of the model. 2025-08-26T19:56:09.3267351Z 2025-08-26T19:56:09.3267442Z .. note:: 2025-08-26T19:56:09.3267639Z When :meth:`update_parameters` is called for the first time (i.e. 2025-08-26T19:56:09.3267831Z :attr:`n_averaged` is `0`) the parameters of `model` are copied 2025-08-26T19:56:09.3268056Z to the parameters of :class:`AveragedModel`. For every subsequent 2025-08-26T19:56:09.3268257Z call of :meth:`update_parameters` the function `avg_fn` is used 2025-08-26T19:56:09.3268362Z to update the parameters. 2025-08-26T19:56:09.3268438Z 2025-08-26T19:56:09.3268670Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T19:56:09.3268814Z https://arxiv.org/abs/1803.05407 2025-08-26T19:56:09.3269057Z .. _There Are Many Consistent Explanations of Unlabeled Data: Why You Should 2025-08-26T19:56:09.3269153Z Average: 2025-08-26T19:56:09.3269270Z https://arxiv.org/abs/1806.05594 2025-08-26T19:56:09.3269478Z .. _SWALP: Stochastic Weight Averaging in Low-Precision Training: 2025-08-26T19:56:09.3269588Z https://arxiv.org/abs/1904.11943 2025-08-26T19:56:09.3269811Z .. _Stochastic Weight Averaging in Parallel: Large-Batch Training That 2025-08-26T19:56:09.3269913Z Generalizes Well: 2025-08-26T19:56:09.3270025Z https://arxiv.org/abs/2001.02312 2025-08-26T19:56:09.3270129Z .. _Polyak averaging: 2025-08-26T19:56:09.3270297Z https://paperswithcode.com/method/polyak-averaging 2025-08-26T19:56:09.3270379Z 2025-08-26T19:56:09.3270637Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3270714Z 2025-08-26T19:56:09.3270821Z warnings.warn(msg) 2025-08-26T19:56:09.3270900Z 2025-08-26T19:56:09.3271103Z --- Parse Warning: 127 / 146 --- 2025-08-26T19:56:09.3271973Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SWALR in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/optim/swa_utils.py line=375. 2025-08-26T19:56:09.3272239Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3272464Z Anneals the learning rate in each parameter group to a fixed value. 2025-08-26T19:56:09.3272544Z 2025-08-26T19:56:09.3272778Z This learning rate scheduler is meant to be used with Stochastic Weight 2025-08-26T19:56:09.3273001Z Averaging (SWA) method (see `torch.optim.swa_utils.AveragedModel`). 2025-08-26T19:56:09.3273079Z 2025-08-26T19:56:09.3273174Z Args: 2025-08-26T19:56:09.3273347Z optimizer (torch.optim.Optimizer): wrapped optimizer 2025-08-26T19:56:09.3273580Z swa_lrs (float or list): the learning rate value for all param groups 2025-08-26T19:56:09.3273721Z together or separately for each group. 2025-08-26T19:56:09.3273924Z annealing_epochs (int): number of epochs in the annealing phase 2025-08-26T19:56:09.3274026Z (default: 10) 2025-08-26T19:56:09.3274239Z annealing_strategy (str): "cos" or "linear"; specifies the annealing 2025-08-26T19:56:09.3274451Z strategy: "cos" for cosine annealing, "linear" for linear annealing 2025-08-26T19:56:09.3274558Z (default: "cos") 2025-08-26T19:56:09.3274739Z last_epoch (int): the index of the last epoch (default: -1) 2025-08-26T19:56:09.3274828Z 2025-08-26T19:56:09.3275007Z The :class:`SWALR` scheduler can be used together with other 2025-08-26T19:56:09.3275228Z schedulers to switch to a constant learning rate late in the training 2025-08-26T19:56:09.3275343Z as in the example below. 2025-08-26T19:56:09.3275446Z 2025-08-26T19:56:09.3275539Z Example: 2025-08-26T19:56:09.3275671Z >>> # xdoctest: +SKIP("Undefined variables") 2025-08-26T19:56:09.3275788Z >>> loader, optimizer, model = ... 2025-08-26T19:56:09.3275905Z >>> lr_lambda = lambda epoch: 0.9 2025-08-26T19:56:09.3276128Z >>> scheduler = torch.optim.lr_scheduler.MultiplicativeLR(optimizer, 2025-08-26T19:56:09.3276237Z >>> lr_lambda=lr_lambda) 2025-08-26T19:56:09.3276405Z >>> swa_scheduler = torch.optim.swa_utils.SWALR(optimizer, 2025-08-26T19:56:09.3276610Z >>> anneal_strategy="linear", anneal_epochs=20, swa_lr=0.05) 2025-08-26T19:56:09.3276714Z >>> swa_start = 160 2025-08-26T19:56:09.3276812Z >>> for i in range(300): 2025-08-26T19:56:09.3276935Z >>> for input, target in loader: 2025-08-26T19:56:09.3277071Z >>> optimizer.zero_grad() 2025-08-26T19:56:09.3277209Z >>> loss_fn(model(input), target).backward() 2025-08-26T19:56:09.3277324Z >>> optimizer.step() 2025-08-26T19:56:09.3277420Z >>> if i > swa_start: 2025-08-26T19:56:09.3277536Z >>> swa_scheduler.step() 2025-08-26T19:56:09.3277620Z >>> else: 2025-08-26T19:56:09.3277722Z >>> scheduler.step() 2025-08-26T19:56:09.3277805Z 2025-08-26T19:56:09.3278026Z .. _Averaging Weights Leads to Wider Optima and Better Generalization: 2025-08-26T19:56:09.3278150Z https://arxiv.org/abs/1803.05407 2025-08-26T19:56:09.3278229Z 2025-08-26T19:56:09.3278481Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3278568Z 2025-08-26T19:56:09.3278662Z warnings.warn(msg) 2025-08-26T19:56:09.3278741Z 2025-08-26T19:56:09.3278938Z --- Parse Warning: 128 / 146 --- 2025-08-26T19:56:09.3279865Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=assert_close in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/testing/_comparison.py line=1331. 2025-08-26T19:56:09.3280142Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3280292Z Asserts that ``actual`` and ``expected`` are close. 2025-08-26T19:56:09.3280379Z 2025-08-26T19:56:09.3280749Z If ``actual`` and ``expected`` are strided, non-quantized, real-valued, and finite, they are considered close if 2025-08-26T19:56:09.3280834Z 2025-08-26T19:56:09.3280929Z .. math:: 2025-08-26T19:56:09.3281007Z 2025-08-26T19:56:09.3281382Z \lvert \text{actual} - \text{expected} \rvert \le \texttt{atol} + \texttt{rtol} \cdot \lvert \text{expected} \rvert 2025-08-26T19:56:09.3281460Z 2025-08-26T19:56:09.3281810Z Non-finite values (``-inf`` and ``inf``) are only considered close if and only if they are equal. ``NaN``'s are 2025-08-26T19:56:09.3282056Z only considered equal to each other if ``equal_nan`` is ``True``. 2025-08-26T19:56:09.3282137Z 2025-08-26T19:56:09.3282347Z In addition, they are only considered close if they have the same 2025-08-26T19:56:09.3282423Z 2025-08-26T19:56:09.3282616Z - :attr:`~torch.Tensor.device` (if ``check_device`` is ``True``), 2025-08-26T19:56:09.3282753Z - ``dtype`` (if ``check_dtype`` is ``True``), 2025-08-26T19:56:09.3282894Z - ``layout`` (if ``check_layout`` is ``True``), and 2025-08-26T19:56:09.3283030Z - stride (if ``check_stride`` is ``True``). 2025-08-26T19:56:09.3283104Z 2025-08-26T19:56:09.3283404Z If either ``actual`` or ``expected`` is a meta tensor, only the attribute checks will be performed. 2025-08-26T19:56:09.3283491Z 2025-08-26T19:56:09.3283855Z If ``actual`` and ``expected`` are sparse (either having COO, CSR, CSC, BSR, or BSC layout), their strided members are 2025-08-26T19:56:09.3284249Z checked individually. Indices, namely ``indices`` for COO, ``crow_indices`` and ``col_indices`` for CSR and BSR, 2025-08-26T19:56:09.3284502Z or ``ccol_indices`` and ``row_indices`` for CSC and BSC layouts, respectively, 2025-08-26T19:56:09.3284896Z are always checked for equality whereas the values are checked for closeness according to the definition above. 2025-08-26T19:56:09.3284982Z 2025-08-26T19:56:09.3285262Z If ``actual`` and ``expected`` are quantized, they are considered close if they have the same 2025-08-26T19:56:09.3285654Z :meth:`~torch.Tensor.qscheme` and the result of :meth:`~torch.Tensor.dequantize` is close according to the 2025-08-26T19:56:09.3285751Z definition above. 2025-08-26T19:56:09.3285829Z 2025-08-26T19:56:09.3286142Z ``actual`` and ``expected`` can be :class:`~torch.Tensor`'s or any tensor-or-scalar-likes from which 2025-08-26T19:56:09.3286548Z :class:`torch.Tensor`'s can be constructed with :func:`torch.as_tensor`. Except for Python scalars the input types 2025-08-26T19:56:09.3286932Z have to be directly related. In addition, ``actual`` and ``expected`` can be :class:`~collections.abc.Sequence`'s 2025-08-26T19:56:09.3287312Z or :class:`~collections.abc.Mapping`'s in which case they are considered close if their structure matches and all 2025-08-26T19:56:09.3287551Z their elements are considered close according to the above definition. 2025-08-26T19:56:09.3287629Z 2025-08-26T19:56:09.3287715Z .. note:: 2025-08-26T19:56:09.3287803Z 2025-08-26T19:56:09.3288138Z Python scalars are an exception to the type relation requirement, because their :func:`type`, i.e. 2025-08-26T19:56:09.3288467Z :class:`int`, :class:`float`, and :class:`complex`, is equivalent to the ``dtype`` of a tensor-like. Thus, 2025-08-26T19:56:09.3288746Z Python scalars of different types can be checked, but require ``check_dtype=False``. 2025-08-26T19:56:09.3288901Z 2025-08-26T19:56:09.3288998Z Args: 2025-08-26T19:56:09.3289103Z actual (Any): Actual input. 2025-08-26T19:56:09.3289225Z expected (Any): Expected input. 2025-08-26T19:56:09.3289584Z allow_subclasses (bool): If ``True`` (default) and except for Python scalars, inputs of directly related types 2025-08-26T19:56:09.3289742Z are allowed. Otherwise type equality is required. 2025-08-26T19:56:09.3290116Z rtol (Optional[float]): Relative tolerance. If specified ``atol`` must also be specified. If omitted, default 2025-08-26T19:56:09.3290381Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T19:56:09.3290753Z atol (Optional[float]): Absolute tolerance. If specified ``rtol`` must also be specified. If omitted, default 2025-08-26T19:56:09.3291022Z values based on the :attr:`~torch.Tensor.dtype` are selected with the below table. 2025-08-26T19:56:09.3291308Z equal_nan (Union[bool, str]): If ``True``, two ``NaN`` values will be considered equal. 2025-08-26T19:56:09.3291610Z check_device (bool): If ``True`` (default), asserts that corresponding tensors are on the same 2025-08-26T19:56:09.3291866Z :attr:`~torch.Tensor.device`. If this check is disabled, tensors on different 2025-08-26T19:56:09.3292119Z :attr:`~torch.Tensor.device`'s are moved to the CPU before being compared. 2025-08-26T19:56:09.3292480Z check_dtype (bool): If ``True`` (default), asserts that corresponding tensors have the same ``dtype``. If this 2025-08-26T19:56:09.3292843Z check is disabled, tensors with different ``dtype``'s are promoted to a common ``dtype`` (according to 2025-08-26T19:56:09.3293004Z :func:`torch.promote_types`) before being compared. 2025-08-26T19:56:09.3293367Z check_layout (bool): If ``True`` (default), asserts that corresponding tensors have the same ``layout``. If this 2025-08-26T19:56:09.3293764Z check is disabled, tensors with different ``layout``'s are converted to strided tensors before being 2025-08-26T19:56:09.3293857Z compared. 2025-08-26T19:56:09.3294238Z check_stride (bool): If ``True`` and corresponding tensors are strided, asserts that they have the same stride. 2025-08-26T19:56:09.3294597Z msg (Optional[Union[str, Callable[[str], str]]]): Optional error message to use in case a failure occurs during 2025-08-26T19:56:09.3295001Z the comparison. Can also passed as callable in which case it will be called with the generated message and 2025-08-26T19:56:09.3295120Z should return the new message. 2025-08-26T19:56:09.3295200Z 2025-08-26T19:56:09.3295295Z Raises: 2025-08-26T19:56:09.3295535Z ValueError: If no :class:`torch.Tensor` can be constructed from an input. 2025-08-26T19:56:09.3295744Z ValueError: If only ``rtol`` or ``atol`` is specified. 2025-08-26T19:56:09.3296081Z AssertionError: If corresponding inputs are not Python scalars and are not directly related. 2025-08-26T19:56:09.3296450Z AssertionError: If ``allow_subclasses`` is ``False``, but corresponding inputs are not Python scalars and have 2025-08-26T19:56:09.3296562Z different types. 2025-08-26T19:56:09.3296930Z AssertionError: If the inputs are :class:`~collections.abc.Sequence`'s, but their length does not match. 2025-08-26T19:56:09.3297318Z AssertionError: If the inputs are :class:`~collections.abc.Mapping`'s, but their set of keys do not match. 2025-08-26T19:56:09.3297638Z AssertionError: If corresponding tensors do not have the same :attr:`~torch.Tensor.shape`. 2025-08-26T19:56:09.3297940Z AssertionError: If ``check_layout`` is ``True``, but corresponding tensors do not have the same 2025-08-26T19:56:09.3298072Z :attr:`~torch.Tensor.layout`. 2025-08-26T19:56:09.3298298Z AssertionError: If only one of corresponding tensors is quantized. 2025-08-26T19:56:09.3298709Z AssertionError: If corresponding tensors are quantized, but have different :meth:`~torch.Tensor.qscheme`'s. 2025-08-26T19:56:09.3299009Z AssertionError: If ``check_device`` is ``True``, but corresponding tensors are not on the same 2025-08-26T19:56:09.3299137Z :attr:`~torch.Tensor.device`. 2025-08-26T19:56:09.3299473Z AssertionError: If ``check_dtype`` is ``True``, but corresponding tensors do not have the same ``dtype``. 2025-08-26T19:56:09.3299836Z AssertionError: If ``check_stride`` is ``True``, but corresponding strided tensors do not have the same stride. 2025-08-26T19:56:09.3300213Z AssertionError: If the values of corresponding tensors are not close according to the definition above. 2025-08-26T19:56:09.3300294Z 2025-08-26T19:56:09.3300676Z The following table displays the default ``rtol`` and ``atol`` for different ``dtype``'s. In case of mismatching 2025-08-26T19:56:09.3300858Z ``dtype``'s, the maximum of both tolerances is used. 2025-08-26T19:56:09.3300940Z 2025-08-26T19:56:09.3301086Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3301214Z | ``dtype`` | ``rtol`` | ``atol`` | 2025-08-26T19:56:09.3301333Z +===========================+============+==========+ 2025-08-26T19:56:09.3301468Z | :attr:`~torch.float16` | ``1e-3`` | ``1e-5`` | 2025-08-26T19:56:09.3301596Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3301745Z | :attr:`~torch.bfloat16` | ``1.6e-2`` | ``1e-5`` | 2025-08-26T19:56:09.3301863Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3302009Z | :attr:`~torch.float32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:09.3302132Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3302265Z | :attr:`~torch.float64` | ``1e-7`` | ``1e-7`` | 2025-08-26T19:56:09.3302426Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3302561Z | :attr:`~torch.complex32` | ``1e-3`` | ``1e-5`` | 2025-08-26T19:56:09.3302695Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3302835Z | :attr:`~torch.complex64` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:09.3302952Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3303103Z | :attr:`~torch.complex128` | ``1e-7`` | ``1e-7`` | 2025-08-26T19:56:09.3303251Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3303402Z | :attr:`~torch.quint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:09.3303527Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3303660Z | :attr:`~torch.quint2x4` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:09.3303824Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3303960Z | :attr:`~torch.quint4x2` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:09.3304092Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3304226Z | :attr:`~torch.qint8` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:09.3304358Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3304492Z | :attr:`~torch.qint32` | ``1.3e-6`` | ``1e-5`` | 2025-08-26T19:56:09.3304612Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3304742Z | other | ``0.0`` | ``0.0`` | 2025-08-26T19:56:09.3304864Z +---------------------------+------------+----------+ 2025-08-26T19:56:09.3304951Z 2025-08-26T19:56:09.3305041Z .. note:: 2025-08-26T19:56:09.3305122Z 2025-08-26T19:56:09.3305526Z :func:`~torch.testing.assert_close` is highly configurable with strict default settings. Users are encouraged 2025-08-26T19:56:09.3305886Z to :func:`~functools.partial` it to fit their use case. For example, if an equality check is needed, one might 2025-08-26T19:56:09.3306161Z define an ``assert_equal`` that uses zero tolerances for every ``dtype`` by default: 2025-08-26T19:56:09.3306240Z 2025-08-26T19:56:09.3306339Z >>> import functools 2025-08-26T19:56:09.3306611Z >>> assert_equal = functools.partial(torch.testing.assert_close, rtol=0, atol=0) 2025-08-26T19:56:09.3306721Z >>> assert_equal(1e-9, 1e-10) 2025-08-26T19:56:09.3306845Z Traceback (most recent call last): 2025-08-26T19:56:09.3306927Z ... 2025-08-26T19:56:09.3307048Z AssertionError: Scalars are not equal! 2025-08-26T19:56:09.3307148Z 2025-08-26T19:56:09.3307256Z Expected 1e-10 but got 1e-09. 2025-08-26T19:56:09.3307381Z Absolute difference: 9.000000000000001e-10 2025-08-26T19:56:09.3307527Z Relative difference: 9.0 2025-08-26T19:56:09.3307607Z 2025-08-26T19:56:09.3307701Z Examples: 2025-08-26T19:56:09.3307813Z >>> # tensor to tensor comparison 2025-08-26T19:56:09.3307943Z >>> expected = torch.tensor([1e0, 1e-1, 1e-2]) 2025-08-26T19:56:09.3308089Z >>> actual = torch.acos(torch.cos(expected)) 2025-08-26T19:56:09.3308235Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:09.3308325Z 2025-08-26T19:56:09.3308440Z >>> # scalar to scalar comparison 2025-08-26T19:56:09.3308535Z >>> import math 2025-08-26T19:56:09.3308656Z >>> expected = math.sqrt(2.0) 2025-08-26T19:56:09.3308766Z >>> actual = 2.0 / math.sqrt(2.0) 2025-08-26T19:56:09.3308919Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:09.3309000Z 2025-08-26T19:56:09.3309123Z >>> # numpy array to numpy array comparison 2025-08-26T19:56:09.3309240Z >>> import numpy as np 2025-08-26T19:56:09.3309389Z >>> expected = np.array([1e0, 1e-1, 1e-2]) 2025-08-26T19:56:09.3309525Z >>> actual = np.arccos(np.cos(expected)) 2025-08-26T19:56:09.3309672Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:09.3309752Z 2025-08-26T19:56:09.3309882Z >>> # sequence to sequence comparison 2025-08-26T19:56:09.3309984Z >>> import numpy as np 2025-08-26T19:56:09.3310249Z >>> # The types of the sequences do not have to match. They only have to have the same 2025-08-26T19:56:09.3310411Z >>> # length and their elements have to match. 2025-08-26T19:56:09.3310569Z >>> expected = [torch.tensor([1.0]), 2.0, np.array(3.0)] 2025-08-26T19:56:09.3310686Z >>> actual = tuple(expected) 2025-08-26T19:56:09.3310832Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:09.3310922Z 2025-08-26T19:56:09.3311068Z >>> # mapping to mapping comparison 2025-08-26T19:56:09.3311193Z >>> from collections import OrderedDict 2025-08-26T19:56:09.3311306Z >>> import numpy as np 2025-08-26T19:56:09.3311410Z >>> foo = torch.tensor(1.0) 2025-08-26T19:56:09.3311498Z >>> bar = 2.0 2025-08-26T19:56:09.3311610Z >>> baz = np.array(3.0) 2025-08-26T19:56:09.3311864Z >>> # The types and a possible ordering of mappings do not have to match. They only 2025-08-26T19:56:09.3312083Z >>> # have to have the same set of keys and their elements have to match. 2025-08-26T19:56:09.3312290Z >>> expected = OrderedDict([("foo", foo), ("bar", bar), ("baz", baz)]) 2025-08-26T19:56:09.3312439Z >>> actual = {"baz": baz, "bar": bar, "foo": foo} 2025-08-26T19:56:09.3312586Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:09.3312661Z 2025-08-26T19:56:09.3312798Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T19:56:09.3312912Z >>> actual = expected.clone() 2025-08-26T19:56:09.3313085Z >>> # By default, directly related instances can be compared 2025-08-26T19:56:09.3313316Z >>> torch.testing.assert_close(torch.nn.Parameter(actual), expected) 2025-08-26T19:56:09.3313506Z >>> # This check can be made more strict with allow_subclasses=False 2025-08-26T19:56:09.3313635Z >>> torch.testing.assert_close( 2025-08-26T19:56:09.3313837Z ... torch.nn.Parameter(actual), expected, allow_subclasses=False 2025-08-26T19:56:09.3313928Z ... ) 2025-08-26T19:56:09.3314047Z Traceback (most recent call last): 2025-08-26T19:56:09.3314125Z ... 2025-08-26T19:56:09.3314349Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T19:56:09.3314569Z and . 2025-08-26T19:56:09.3314810Z >>> # If the inputs are not directly related, they are never considered close 2025-08-26T19:56:09.3315014Z >>> torch.testing.assert_close(actual.numpy(), expected) 2025-08-26T19:56:09.3315130Z Traceback (most recent call last): 2025-08-26T19:56:09.3315224Z ... 2025-08-26T19:56:09.3315520Z TypeError: No comparison pair was able to handle inputs of type 2025-08-26T19:56:09.3315636Z and . 2025-08-26T19:56:09.3315904Z >>> # Exceptions to these rules are Python scalars. They can be checked regardless of 2025-08-26T19:56:09.3316025Z >>> # their type if check_dtype=False. 2025-08-26T19:56:09.3316206Z >>> torch.testing.assert_close(1.0, 1, check_dtype=False) 2025-08-26T19:56:09.3316284Z 2025-08-26T19:56:09.3316396Z >>> # NaN != NaN by default. 2025-08-26T19:56:09.3316523Z >>> expected = torch.tensor(float("Nan")) 2025-08-26T19:56:09.3316631Z >>> actual = expected.clone() 2025-08-26T19:56:09.3316794Z >>> torch.testing.assert_close(actual, expected) 2025-08-26T19:56:09.3316975Z Traceback (most recent call last): 2025-08-26T19:56:09.3317054Z ... 2025-08-26T19:56:09.3317190Z AssertionError: Scalars are not close! 2025-08-26T19:56:09.3317279Z 2025-08-26T19:56:09.3317397Z Expected nan but got nan. 2025-08-26T19:56:09.3317542Z Absolute difference: nan (up to 1e-05 allowed) 2025-08-26T19:56:09.3317691Z Relative difference: nan (up to 1.3e-06 allowed) 2025-08-26T19:56:09.3317932Z >>> torch.testing.assert_close(actual, expected, equal_nan=True) 2025-08-26T19:56:09.3318010Z 2025-08-26T19:56:09.3318146Z >>> expected = torch.tensor([1.0, 2.0, 3.0]) 2025-08-26T19:56:09.3318268Z >>> actual = torch.tensor([1.0, 4.0, 5.0]) 2025-08-26T19:56:09.3318411Z >>> # The default error message can be overwritten. 2025-08-26T19:56:09.3318570Z >>> torch.testing.assert_close( 2025-08-26T19:56:09.3318755Z ... actual, expected, msg="Argh, the tensors are not close!" 2025-08-26T19:56:09.3318849Z ... ) 2025-08-26T19:56:09.3318967Z Traceback (most recent call last): 2025-08-26T19:56:09.3319048Z ... 2025-08-26T19:56:09.3319213Z AssertionError: Argh, the tensors are not close! 2025-08-26T19:56:09.3319439Z >>> # If msg is a callable, it can be used to augment the generated message with 2025-08-26T19:56:09.3319551Z >>> # extra information 2025-08-26T19:56:09.3319671Z >>> torch.testing.assert_close( 2025-08-26T19:56:09.3319870Z ... actual, expected, msg=lambda msg: f"Header\n\n{msg}\n\nFooter" 2025-08-26T19:56:09.3319963Z ... ) 2025-08-26T19:56:09.3320080Z Traceback (most recent call last): 2025-08-26T19:56:09.3320171Z ... 2025-08-26T19:56:09.3320276Z AssertionError: Header 2025-08-26T19:56:09.3320366Z 2025-08-26T19:56:09.3320488Z Tensor-likes are not close! 2025-08-26T19:56:09.3320574Z 2025-08-26T19:56:09.3320696Z Mismatched elements: 2 / 3 (66.7%) 2025-08-26T19:56:09.3320921Z Greatest absolute difference: 2.0 at index (1,) (up to 1e-05 allowed) 2025-08-26T19:56:09.3321151Z Greatest relative difference: 1.0 at index (1,) (up to 1.3e-06 allowed) 2025-08-26T19:56:09.3321252Z 2025-08-26T19:56:09.3321334Z Footer 2025-08-26T19:56:09.3321424Z 2025-08-26T19:56:09.3321684Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3321762Z 2025-08-26T19:56:09.3321874Z warnings.warn(msg) 2025-08-26T19:56:09.3321955Z 2025-08-26T19:56:09.3322179Z --- Parse Warning: 129 / 146 --- 2025-08-26T19:56:09.3323131Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=register_pytree_node in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/_cxx_pytree.py line=134. 2025-08-26T19:56:09.3323441Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3323598Z Register a container-like type as pytree node. 2025-08-26T19:56:09.3323677Z 2025-08-26T19:56:09.3323774Z Args: 2025-08-26T19:56:09.3323965Z cls (type): A Python type to treat as an internal pytree node. 2025-08-26T19:56:09.3324241Z flatten_fn (callable): A function to be used during flattening, taking an instance of 2025-08-26T19:56:09.3324500Z ``cls`` and returning a pair, with (1) an iterable for the children to be flattened 2025-08-26T19:56:09.3324796Z recursively, and (2) some hashable auxiliary data to be stored in the treespec and to be 2025-08-26T19:56:09.3324927Z passed to the ``unflatten_fn``. 2025-08-26T19:56:09.3325214Z unflatten_fn (callable): A function taking two arguments: the auxiliary data that was 2025-08-26T19:56:09.3325502Z returned by ``flatten_fn`` and stored in the treespec, and the unflattened children. 2025-08-26T19:56:09.3325672Z The function should return an instance of ``cls``. 2025-08-26T19:56:09.3325942Z serialized_type_name (str, optional): A keyword argument used to specify the fully 2025-08-26T19:56:09.3326122Z qualified name used when serializing the tree spec. 2025-08-26T19:56:09.3326463Z to_dumpable_context (callable, optional): An optional keyword argument to custom specify how 2025-08-26T19:56:09.3326748Z to convert the context of the pytree to a custom json dumpable representation. This is 2025-08-26T19:56:09.3327036Z used for json serialization, which is being used in :mod:`torch.export` right now. 2025-08-26T19:56:09.3327367Z from_dumpable_context (callable, optional): An optional keyword argument to custom specify 2025-08-26T19:56:09.3327650Z how to convert the custom json dumpable representation of the context back to the 2025-08-26T19:56:09.3327914Z original context. This is used for json deserialization, which is being used in 2025-08-26T19:56:09.3328041Z :mod:`torch.export` right now. 2025-08-26T19:56:09.3328122Z 2025-08-26T19:56:09.3328215Z Example:: 2025-08-26T19:56:09.3328307Z 2025-08-26T19:56:09.3328407Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3328562Z >>> # Registry a Python type with lambda functions 2025-08-26T19:56:09.3328673Z >>> register_pytree_node( 2025-08-26T19:56:09.3328757Z ... set, 2025-08-26T19:56:09.3328970Z ... lambda s: (sorted(s), None, None), 2025-08-26T19:56:09.3329097Z ... lambda children, _: set(children), 2025-08-26T19:56:09.3329178Z ... ) 2025-08-26T19:56:09.3329269Z 2025-08-26T19:56:09.3329532Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3329624Z 2025-08-26T19:56:09.3329718Z warnings.warn(msg) 2025-08-26T19:56:09.3329798Z 2025-08-26T19:56:09.3330011Z --- Parse Warning: 130 / 146 --- 2025-08-26T19:56:09.3331011Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SelectiveCheckpointContext in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1218. 2025-08-26T19:56:09.3331294Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3331373Z 2025-08-26T19:56:09.3331589Z Context passed to policy function during selective checkpointing. 2025-08-26T19:56:09.3331674Z 2025-08-26T19:56:09.3331902Z This class is used to pass relevant metadata to the policy function during 2025-08-26T19:56:09.3332185Z selective checkpointing. The metadata includes whether the current invocation 2025-08-26T19:56:09.3332381Z of the policy function is during recomputation or not. 2025-08-26T19:56:09.3332463Z 2025-08-26T19:56:09.3332557Z Example: 2025-08-26T19:56:09.3332659Z >>> # xdoctest: +SKIP(stub) 2025-08-26T19:56:09.3332750Z >>> 2025-08-26T19:56:09.3332877Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T19:56:09.3332985Z >>> print(ctx.is_recompute) 2025-08-26T19:56:09.3333075Z >>> 2025-08-26T19:56:09.3333353Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T19:56:09.3333448Z >>> 2025-08-26T19:56:09.3333590Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T19:56:09.3333683Z >>> fn, x, y, 2025-08-26T19:56:09.3333792Z >>> use_reentrant=False, 2025-08-26T19:56:09.3333896Z >>> context_fn=context_fn, 2025-08-26T19:56:09.3333994Z >>> ) 2025-08-26T19:56:09.3334080Z 2025-08-26T19:56:09.3334338Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3334448Z 2025-08-26T19:56:09.3334543Z warnings.warn(msg) 2025-08-26T19:56:09.3334624Z 2025-08-26T19:56:09.3334823Z --- Parse Warning: 131 / 146 --- 2025-08-26T19:56:09.3335841Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=create_selective_checkpoint_contexts in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/checkpoint.py line=1358. 2025-08-26T19:56:09.3336142Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3336222Z 2025-08-26T19:56:09.3336472Z Helper to avoid recomputing certain ops during activation checkpointing. 2025-08-26T19:56:09.3336551Z 2025-08-26T19:56:09.3336766Z Use this with `torch.utils.checkpoint.checkpoint` to control which 2025-08-26T19:56:09.3336966Z operations are recomputed during the backward pass. 2025-08-26T19:56:09.3337048Z 2025-08-26T19:56:09.3337129Z Args: 2025-08-26T19:56:09.3337256Z policy_fn_or_list (Callable or List): 2025-08-26T19:56:09.3337611Z - If a policy function is provided, it should accept a 2025-08-26T19:56:09.3337868Z :class:`SelectiveCheckpointContext`, the :class:`OpOverload`, args and 2025-08-26T19:56:09.3338077Z kwargs to the op, and return a :class:`CheckpointPolicy` enum value 2025-08-26T19:56:09.3338323Z indicating whether the execution of the op should be recomputed or not. 2025-08-26T19:56:09.3338538Z - If a list of operations is provided, it is equivalent to a policy 2025-08-26T19:56:09.3338725Z returning `CheckpointPolicy.MUST_SAVE` for the specified 2025-08-26T19:56:09.3338955Z operations and `CheckpointPolicy.PREFER_RECOMPUTE` for all other 2025-08-26T19:56:09.3339048Z operations. 2025-08-26T19:56:09.3339281Z allow_cache_entry_mutation (bool, optional): By default, an error is 2025-08-26T19:56:09.3339500Z raised if any tensors cached by selective activation checkpoint are 2025-08-26T19:56:09.3339714Z mutated in order to ensure correctness. If set to `True`, this check 2025-08-26T19:56:09.3339817Z is disabled. 2025-08-26T19:56:09.3339902Z Returns: 2025-08-26T19:56:09.3340016Z A tuple of two context managers. 2025-08-26T19:56:09.3340107Z 2025-08-26T19:56:09.3340193Z Example: 2025-08-26T19:56:09.3340310Z >>> # xdoctest: +REQUIRES(LINUX) 2025-08-26T19:56:09.3340409Z >>> import functools 2025-08-26T19:56:09.3340490Z >>> 2025-08-26T19:56:09.3340625Z >>> x = torch.rand(10, 10, requires_grad=True) 2025-08-26T19:56:09.3340751Z >>> y = torch.rand(10, 10, requires_grad=True) 2025-08-26T19:56:09.3340845Z >>> 2025-08-26T19:56:09.3340935Z >>> ops_to_save = [ 2025-08-26T19:56:09.3341049Z >>> torch.ops.aten.mm.default, 2025-08-26T19:56:09.3341199Z >>> ] 2025-08-26T19:56:09.3341283Z >>> 2025-08-26T19:56:09.3341430Z >>> def policy_fn(ctx, op, *args, **kwargs): 2025-08-26T19:56:09.3341533Z >>> if op in ops_to_save: 2025-08-26T19:56:09.3341665Z >>> return CheckpointPolicy.MUST_SAVE 2025-08-26T19:56:09.3341760Z >>> else: 2025-08-26T19:56:09.3341907Z >>> return CheckpointPolicy.PREFER_RECOMPUTE 2025-08-26T19:56:09.3341989Z >>> 2025-08-26T19:56:09.3342277Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, policy_fn) 2025-08-26T19:56:09.3342361Z >>> 2025-08-26T19:56:09.3342465Z >>> # or equivalently 2025-08-26T19:56:09.3342742Z >>> context_fn = functools.partial(create_selective_checkpoint_contexts, ops_to_save) 2025-08-26T19:56:09.3342822Z >>> 2025-08-26T19:56:09.3342920Z >>> def fn(x, y): 2025-08-26T19:56:09.3343127Z >>> return torch.sigmoid(torch.matmul(torch.matmul(x, y), y)) * y 2025-08-26T19:56:09.3343219Z >>> 2025-08-26T19:56:09.3343401Z >>> out = torch.utils.checkpoint.checkpoint( 2025-08-26T19:56:09.3343490Z >>> fn, x, y, 2025-08-26T19:56:09.3343598Z >>> use_reentrant=False, 2025-08-26T19:56:09.3343703Z >>> context_fn=context_fn, 2025-08-26T19:56:09.3343791Z >>> ) 2025-08-26T19:56:09.3343870Z 2025-08-26T19:56:09.3344126Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3344215Z 2025-08-26T19:56:09.3344314Z warnings.warn(msg) 2025-08-26T19:56:09.3344404Z 2025-08-26T19:56:09.3344641Z --- Parse Warning: 132 / 146 --- 2025-08-26T19:56:09.3345577Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CppExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1159. 2025-08-26T19:56:09.3345892Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3345975Z 2025-08-26T19:56:09.3346129Z Create a :class:`setuptools.Extension` for C++. 2025-08-26T19:56:09.3346209Z 2025-08-26T19:56:09.3346457Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T19:56:09.3346692Z bare minimum (but often sufficient) arguments to build a C++ extension. 2025-08-26T19:56:09.3346770Z 2025-08-26T19:56:09.3346985Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T19:56:09.3347138Z constructor. Full list arguments can be found at 2025-08-26T19:56:09.3347474Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T19:56:09.3347560Z 2025-08-26T19:56:09.3347652Z .. warning:: 2025-08-26T19:56:09.3347891Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T19:56:09.3348107Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T19:56:09.3348310Z the user's responsibility in their library to not use APIs from 2025-08-26T19:56:09.3348553Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T19:56:09.3348774Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T19:56:09.3348997Z example, to give access to custom ops from python, the library should 2025-08-26T19:56:09.3349128Z register the ops through the dispatcher. 2025-08-26T19:56:09.3349204Z 2025-08-26T19:56:09.3349441Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T19:56:09.3349648Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T19:56:09.3349867Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T19:56:09.3350085Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T19:56:09.3350328Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T19:56:09.3350556Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T19:56:09.3350661Z CPython version of choice. 2025-08-26T19:56:09.3350747Z 2025-08-26T19:56:09.3350831Z Example: 2025-08-26T19:56:09.3350925Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3351089Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:09.3351201Z >>> from setuptools import setup 2025-08-26T19:56:09.3351434Z >>> from torch.utils.cpp_extension import BuildExtension, CppExtension 2025-08-26T19:56:09.3351521Z >>> setup( 2025-08-26T19:56:09.3351622Z ... name='extension', 2025-08-26T19:56:09.3351722Z ... ext_modules=[ 2025-08-26T19:56:09.3351821Z ... CppExtension( 2025-08-26T19:56:09.3351923Z ... name='extension', 2025-08-26T19:56:09.3352058Z ... sources=['extension.cpp'], 2025-08-26T19:56:09.3352178Z ... extra_compile_args=['-g'], 2025-08-26T19:56:09.3352363Z ... extra_link_args=['-Wl,--no-as-needed', '-lm']) 2025-08-26T19:56:09.3352447Z ... ], 2025-08-26T19:56:09.3352533Z ... cmdclass={ 2025-08-26T19:56:09.3352657Z ... 'build_ext': BuildExtension 2025-08-26T19:56:09.3352736Z ... }) 2025-08-26T19:56:09.3352826Z 2025-08-26T19:56:09.3353081Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3353164Z 2025-08-26T19:56:09.3353307Z warnings.warn(msg) 2025-08-26T19:56:09.3353390Z 2025-08-26T19:56:09.3353605Z --- Parse Warning: 133 / 146 --- 2025-08-26T19:56:09.3354581Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=CUDAExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1229. 2025-08-26T19:56:09.3354856Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3354951Z 2025-08-26T19:56:09.3355118Z Create a :class:`setuptools.Extension` for CUDA/C++. 2025-08-26T19:56:09.3355215Z 2025-08-26T19:56:09.3355463Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T19:56:09.3355671Z bare minimum (but often sufficient) arguments to build a CUDA/C++ 2025-08-26T19:56:09.3355925Z extension. This includes the CUDA include path, library path and runtime 2025-08-26T19:56:09.3356012Z library. 2025-08-26T19:56:09.3356105Z 2025-08-26T19:56:09.3356319Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T19:56:09.3356473Z constructor. Full list arguments can be found at 2025-08-26T19:56:09.3356820Z https://setuptools.pypa.io/en/latest/userguide/ext_modules.html#extension-api-reference 2025-08-26T19:56:09.3356899Z 2025-08-26T19:56:09.3356995Z .. warning:: 2025-08-26T19:56:09.3357228Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T19:56:09.3357444Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T19:56:09.3357661Z the user's responsibility in their library to not use APIs from 2025-08-26T19:56:09.3357899Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T19:56:09.3358137Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T19:56:09.3358361Z example, to give access to custom ops from python, the library should 2025-08-26T19:56:09.3358494Z register the ops through the dispatcher. 2025-08-26T19:56:09.3358592Z 2025-08-26T19:56:09.3358820Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T19:56:09.3359043Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T19:56:09.3359259Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T19:56:09.3359508Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T19:56:09.3359741Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T19:56:09.3359959Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T19:56:09.3360086Z CPython version of choice. 2025-08-26T19:56:09.3360168Z 2025-08-26T19:56:09.3360254Z Example: 2025-08-26T19:56:09.3360366Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3360523Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:09.3360655Z >>> from setuptools import setup 2025-08-26T19:56:09.3360886Z >>> from torch.utils.cpp_extension import BuildExtension, CUDAExtension 2025-08-26T19:56:09.3360974Z >>> setup( 2025-08-26T19:56:09.3361093Z ... name='cuda_extension', 2025-08-26T19:56:09.3361187Z ... ext_modules=[ 2025-08-26T19:56:09.3361305Z ... CUDAExtension( 2025-08-26T19:56:09.3361449Z ... name='cuda_extension', 2025-08-26T19:56:09.3361616Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T19:56:09.3361758Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T19:56:09.3361878Z ... 'nvcc': ['-O2']}, 2025-08-26T19:56:09.3362051Z ... extra_link_args=['-Wl,--no-as-needed', '-lcuda']) 2025-08-26T19:56:09.3362135Z ... ], 2025-08-26T19:56:09.3362228Z ... cmdclass={ 2025-08-26T19:56:09.3362384Z ... 'build_ext': BuildExtension 2025-08-26T19:56:09.3362468Z ... }) 2025-08-26T19:56:09.3362560Z 2025-08-26T19:56:09.3362660Z Compute capabilities: 2025-08-26T19:56:09.3362741Z 2025-08-26T19:56:09.3363061Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T19:56:09.3363387Z building process of the extension, plus PTX. If down the road a new card is installed the 2025-08-26T19:56:09.3363703Z extension may need to be recompiled. If a visible card has a compute capability (CC) that's 2025-08-26T19:56:09.3364013Z newer than the newest version for which your nvcc can build fully-compiled binaries, PyTorch 2025-08-26T19:56:09.3364305Z will make nvcc fall back to building kernels with the newest version of PTX your nvcc does 2025-08-26T19:56:09.3364447Z support (see below for details on PTX). 2025-08-26T19:56:09.3364526Z 2025-08-26T19:56:09.3364855Z You can override the default behavior using `TORCH_CUDA_ARCH_LIST` to explicitly specify which 2025-08-26T19:56:09.3364974Z CCs you want the extension to support: 2025-08-26T19:56:09.3365052Z 2025-08-26T19:56:09.3365257Z ``TORCH_CUDA_ARCH_LIST="6.1 8.6" python build_my_extension.py`` 2025-08-26T19:56:09.3365498Z ``TORCH_CUDA_ARCH_LIST="5.2 6.0 6.1 7.0 7.5 8.0 8.6+PTX" python build_my_extension.py`` 2025-08-26T19:56:09.3365596Z 2025-08-26T19:56:09.3365922Z The +PTX option causes extension kernel binaries to include PTX instructions for the specified 2025-08-26T19:56:09.3366244Z CC. PTX is an intermediate representation that allows kernels to runtime-compile for any CC >= 2025-08-26T19:56:09.3366569Z the specified CC (for example, 8.6+PTX generates PTX that can runtime-compile for any GPU with 2025-08-26T19:56:09.3366868Z CC >= 8.6). This improves your binary's forward compatibility. However, relying on older PTX to 2025-08-26T19:56:09.3367215Z provide forward compat by runtime-compiling for newer CCs can modestly reduce performance on 2025-08-26T19:56:09.3367498Z those newer CCs. If you know exact CC(s) of the GPUs you want to target, you're always better 2025-08-26T19:56:09.3367830Z off specifying them individually. For example, if you want your extension to run on 8.0 and 8.6, 2025-08-26T19:56:09.3368166Z "8.0+PTX" would work functionally because it includes PTX that can runtime-compile for 8.6, but 2025-08-26T19:56:09.3368293Z "8.0 8.6" would be better. 2025-08-26T19:56:09.3368385Z 2025-08-26T19:56:09.3368688Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T19:56:09.3369090Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T19:56:09.3369172Z 2025-08-26T19:56:09.3369511Z Note that CUDA-11.5 nvcc will hit internal compiler error while parsing torch/extension.h on Windows. 2025-08-26T19:56:09.3369746Z To workaround the issue, move python binding logic to pure C++ file. 2025-08-26T19:56:09.3369823Z 2025-08-26T19:56:09.3369913Z Example use: 2025-08-26T19:56:09.3370028Z #include 2025-08-26T19:56:09.3370187Z at::Tensor SigmoidAlphaBlendForwardCuda(....) 2025-08-26T19:56:09.3370279Z 2025-08-26T19:56:09.3370369Z Instead of: 2025-08-26T19:56:09.3370484Z #include 2025-08-26T19:56:09.3370664Z torch::Tensor SigmoidAlphaBlendForwardCuda(...) 2025-08-26T19:56:09.3370777Z 2025-08-26T19:56:09.3371071Z Currently open issue for nvcc bug: https://github.com/pytorch/pytorch/issues/69460 2025-08-26T19:56:09.3371589Z Complete workaround code example: https://github.com/facebookresearch/pytorch3d/commit/cb170ac024a949f1f9614ffe6af1c38d972f7d48 2025-08-26T19:56:09.3371671Z 2025-08-26T19:56:09.3371793Z Relocatable device code linking: 2025-08-26T19:56:09.3371872Z 2025-08-26T19:56:09.3372197Z If you want to reference device symbols across compilation units (across object files), 2025-08-26T19:56:09.3372458Z the object files need to be built with `relocatable device code` (-rdc=true or -dc). 2025-08-26T19:56:09.3372827Z An exception to this rule is "dynamic parallelism" (nested kernel launches) which is not used a lot anymore. 2025-08-26T19:56:09.3373202Z `Relocatable device code` is less optimized so it needs to be used only on object files that need it. 2025-08-26T19:56:09.3373536Z Using `-dlto` (Device Link Time Optimization) at the device code compilation step and `dlink` step 2025-08-26T19:56:09.3373735Z helps reduce the protentional perf degradation of `-rdc`. 2025-08-26T19:56:09.3373904Z Note that it needs to be used at both steps to be useful. 2025-08-26T19:56:09.3373999Z 2025-08-26T19:56:09.3374376Z If you have `rdc` objects you need to have an extra `-dlink` (device linking) step before the CPU symbol linking step. 2025-08-26T19:56:09.3374554Z There is also a case where `-dlink` is used without `-rdc`: 2025-08-26T19:56:09.3374829Z when an extension is linked against a static lib containing rdc-compiled objects 2025-08-26T19:56:09.3375045Z like the [NVSHMEM library](https://developer.nvidia.com/nvshmem). 2025-08-26T19:56:09.3375139Z 2025-08-26T19:56:09.3375346Z Note: Ninja is required to build a CUDA Extension with RDC linking. 2025-08-26T19:56:09.3375427Z 2025-08-26T19:56:09.3375530Z Example: 2025-08-26T19:56:09.3375632Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3375785Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:09.3375896Z >>> CUDAExtension( 2025-08-26T19:56:09.3376004Z ... name='cuda_extension', 2025-08-26T19:56:09.3376180Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T19:56:09.3376274Z ... dlink=True, 2025-08-26T19:56:09.3376395Z ... dlink_libraries=["dlink_lib"], 2025-08-26T19:56:09.3376532Z ... extra_compile_args={'cxx': ['-g'], 2025-08-26T19:56:09.3376657Z ... 'nvcc': ['-O2', '-rdc=true']}) 2025-08-26T19:56:09.3376751Z 2025-08-26T19:56:09.3377009Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3377092Z 2025-08-26T19:56:09.3377203Z warnings.warn(msg) 2025-08-26T19:56:09.3377284Z 2025-08-26T19:56:09.3377544Z --- Parse Warning: 134 / 146 --- 2025-08-26T19:56:09.3378493Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=SyclExtension in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1420. 2025-08-26T19:56:09.3378763Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3378857Z 2025-08-26T19:56:09.3379027Z Creates a :class:`setuptools.Extension` for SYCL/C++. 2025-08-26T19:56:09.3379123Z 2025-08-26T19:56:09.3379373Z Convenience method that creates a :class:`setuptools.Extension` with the 2025-08-26T19:56:09.3379577Z bare minimum (but often sufficient) arguments to build a SYCL/C++ 2025-08-26T19:56:09.3379680Z extension. 2025-08-26T19:56:09.3379760Z 2025-08-26T19:56:09.3379984Z All arguments are forwarded to the :class:`setuptools.Extension` 2025-08-26T19:56:09.3380073Z constructor. 2025-08-26T19:56:09.3380157Z 2025-08-26T19:56:09.3380258Z .. warning:: 2025-08-26T19:56:09.3380521Z The PyTorch python API (as provided in libtorch_python) cannot be built 2025-08-26T19:56:09.3380749Z with the flag ``py_limited_api=True``. When this flag is passed, it is 2025-08-26T19:56:09.3380948Z the user's responsibility in their library to not use APIs from 2025-08-26T19:56:09.3381183Z libtorch_python (in particular pytorch/python bindings) and to only use 2025-08-26T19:56:09.3381415Z APIs from libtorch (aten objects, operators and the dispatcher). For 2025-08-26T19:56:09.3381656Z example, to give access to custom ops from python, the library should 2025-08-26T19:56:09.3381802Z register the ops through the dispatcher. 2025-08-26T19:56:09.3381882Z 2025-08-26T19:56:09.3382108Z Contrary to CPython setuptools, who does not define -DPy_LIMITED_API 2025-08-26T19:56:09.3382353Z as a compile flag when py_limited_api is specified as an option for 2025-08-26T19:56:09.3382570Z the "bdist_wheel" command in ``setup``, PyTorch does! We will specify 2025-08-26T19:56:09.3382802Z -DPy_LIMITED_API=min_supported_cpython to best enforce consistency, 2025-08-26T19:56:09.3383019Z safety, and sanity in order to encourage best practices. To target a 2025-08-26T19:56:09.3383239Z different version, set min_supported_cpython to the hexcode of the 2025-08-26T19:56:09.3383358Z CPython version of choice. 2025-08-26T19:56:09.3383440Z 2025-08-26T19:56:09.3383537Z Example: 2025-08-26T19:56:09.3383634Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3383786Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:09.3384029Z >>> from torch.utils.cpp_extension import BuildExtension, SyclExtension 2025-08-26T19:56:09.3384117Z >>> setup( 2025-08-26T19:56:09.3384242Z ... name='xpu_extension', 2025-08-26T19:56:09.3384336Z ... ext_modules=[ 2025-08-26T19:56:09.3384437Z ... SyclExtension( 2025-08-26T19:56:09.3384570Z ... name='xpu_extension', 2025-08-26T19:56:09.3384741Z ... sources=['extension.cpp', 'extension_kernel.cpp'], 2025-08-26T19:56:09.3384937Z ... extra_compile_args={'cxx': ['-g', '-std=c++20', '-fPIC']}) 2025-08-26T19:56:09.3385020Z ... ], 2025-08-26T19:56:09.3385112Z ... cmdclass={ 2025-08-26T19:56:09.3385240Z ... 'build_ext': BuildExtension 2025-08-26T19:56:09.3385323Z ... }) 2025-08-26T19:56:09.3385403Z 2025-08-26T19:56:09.3385723Z By default the extension will be compiled to run on all archs of the cards visible during the 2025-08-26T19:56:09.3385981Z building process of the extension. If down the road a new card is installed the 2025-08-26T19:56:09.3386249Z extension may need to be recompiled. You can override the default behavior using 2025-08-26T19:56:09.3386561Z `TORCH_XPU_ARCH_LIST` to explicitly specify which device architectures you want the extension 2025-08-26T19:56:09.3386693Z to support: 2025-08-26T19:56:09.3386772Z 2025-08-26T19:56:09.3386973Z ``TORCH_XPU_ARCH_LIST="pvc,xe-lpg" python build_my_extension.py`` 2025-08-26T19:56:09.3387065Z 2025-08-26T19:56:09.3387368Z Note that while it's possible to include all supported archs, the more archs get included the 2025-08-26T19:56:09.3387678Z slower the building process will be, as it will build a separate kernel image for each arch. 2025-08-26T19:56:09.3387760Z 2025-08-26T19:56:09.3387904Z Note: Ninja is required to build SyclExtension. 2025-08-26T19:56:09.3387997Z 2025-08-26T19:56:09.3388252Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3388334Z 2025-08-26T19:56:09.3388449Z warnings.warn(msg) 2025-08-26T19:56:09.3388532Z 2025-08-26T19:56:09.3388749Z --- Parse Warning: 135 / 146 --- 2025-08-26T19:56:09.3389638Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1597. 2025-08-26T19:56:09.3389964Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3390044Z 2025-08-26T19:56:09.3390194Z Load a PyTorch C++ extension just-in-time (JIT). 2025-08-26T19:56:09.3390289Z 2025-08-26T19:56:09.3390501Z To load an extension, a Ninja build file is emitted, which is used to 2025-08-26T19:56:09.3390751Z compile the given sources into a dynamic library. This library is 2025-08-26T19:56:09.3390995Z subsequently loaded into the current Python process as a module and 2025-08-26T19:56:09.3391127Z returned from this function, ready for use. 2025-08-26T19:56:09.3391223Z 2025-08-26T19:56:09.3391437Z By default, the directory to which the build file is emitted and the 2025-08-26T19:56:09.3391704Z resulting library compiled to is ``/torch_extensions/``, where 2025-08-26T19:56:09.3391928Z ```` is the temporary folder on the current platform and ```` 2025-08-26T19:56:09.3392148Z the name of the extension. This location can be overridden in two ways. 2025-08-26T19:56:09.3392374Z First, if the ``TORCH_EXTENSIONS_DIR`` environment variable is set, it 2025-08-26T19:56:09.3392597Z replaces ``/torch_extensions`` and all extensions will be compiled 2025-08-26T19:56:09.3392838Z into subfolders of this directory. Second, if the ``build_directory`` 2025-08-26T19:56:09.3393079Z argument to this function is supplied, it overrides the entire path, i.e. 2025-08-26T19:56:09.3393246Z the library will be compiled into that folder directly. 2025-08-26T19:56:09.3393345Z 2025-08-26T19:56:09.3393563Z To compile the sources, the default system compiler (``c++``) is used, 2025-08-26T19:56:09.3393821Z which can be overridden by setting the ``CXX`` environment variable. To pass 2025-08-26T19:56:09.3394050Z additional arguments to the compilation process, ``extra_cflags`` or 2025-08-26T19:56:09.3394277Z ``extra_ldflags`` can be provided. For example, to compile your extension 2025-08-26T19:56:09.3394503Z with optimizations, pass ``extra_cflags=['-O3']``. You can also use 2025-08-26T19:56:09.3394660Z ``extra_cflags`` to pass further include directories. 2025-08-26T19:56:09.3394755Z 2025-08-26T19:56:09.3394993Z CUDA support with mixed compilation is provided. Simply pass CUDA source 2025-08-26T19:56:09.3395182Z files (``.cu`` or ``.cuh``) along with other sources. Such files will be 2025-08-26T19:56:09.3395445Z detected and compiled with nvcc rather than the C++ compiler. This includes 2025-08-26T19:56:09.3395658Z passing the CUDA lib64 directory as a library directory, and linking 2025-08-26T19:56:09.3395825Z ``cudart``. You can pass additional flags to nvcc via 2025-08-26T19:56:09.3396034Z ``extra_cuda_cflags``, just like with ``extra_cflags`` for C++. Various 2025-08-26T19:56:09.3396299Z heuristics for finding the CUDA install directory are used, which usually 2025-08-26T19:56:09.3396525Z work fine. If not, setting the ``CUDA_HOME`` environment variable is the 2025-08-26T19:56:09.3396618Z safest option. 2025-08-26T19:56:09.3396712Z 2025-08-26T19:56:09.3396950Z SYCL support with mixed compilation is provided. Simply pass SYCL source 2025-08-26T19:56:09.3397153Z files (``.sycl``) along with other sources. Such files will be detected 2025-08-26T19:56:09.3397383Z and compiled with SYCL compiler (such as Intel DPC++ Compiler) rather 2025-08-26T19:56:09.3397593Z than the C++ compiler. You can pass additional flags to SYCL compiler 2025-08-26T19:56:09.3397800Z via ``extra_sycl_cflags``, just like with ``extra_cflags`` for C++. 2025-08-26T19:56:09.3398010Z SYCL compiler is expected to be found via system PATH environment 2025-08-26T19:56:09.3398098Z variable. 2025-08-26T19:56:09.3398195Z 2025-08-26T19:56:09.3398279Z Args: 2025-08-26T19:56:09.3398531Z name: The name of the extension to build. This MUST be the same as the 2025-08-26T19:56:09.3398642Z name of the pybind11 module! 2025-08-26T19:56:09.3398849Z sources: A list of relative or absolute paths to C++ source files. 2025-08-26T19:56:09.3399092Z extra_cflags: optional list of compiler flags to forward to the build. 2025-08-26T19:56:09.3399315Z extra_cuda_cflags: optional list of compiler flags to forward to nvcc 2025-08-26T19:56:09.3399437Z when building CUDA sources. 2025-08-26T19:56:09.3399683Z extra_sycl_cflags: optional list of compiler flags to forward to SYCL 2025-08-26T19:56:09.3399807Z compiler when building SYCL sources. 2025-08-26T19:56:09.3400041Z extra_ldflags: optional list of linker flags to forward to the build. 2025-08-26T19:56:09.3400262Z extra_include_paths: optional list of include directories to forward 2025-08-26T19:56:09.3400396Z to the build. 2025-08-26T19:56:09.3400582Z build_directory: optional path to use as build workspace. 2025-08-26T19:56:09.3400762Z verbose: If ``True``, turns on verbose logging of load steps. 2025-08-26T19:56:09.3400999Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T19:56:09.3401161Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:09.3401384Z automatically determined based on the existence of ``.cu`` or 2025-08-26T19:56:09.3401557Z ``.cuh`` in ``sources``. Set it to `True`` to force CUDA headers 2025-08-26T19:56:09.3401672Z and libraries to be included. 2025-08-26T19:56:09.3401910Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T19:56:09.3402073Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:09.3402304Z automatically determined based on the existence of ``.sycl`` in 2025-08-26T19:56:09.3402475Z ``sources``. Set it to `True`` to force SYCL headers and 2025-08-26T19:56:09.3402587Z libraries to be included. 2025-08-26T19:56:09.3402806Z is_python_module: If ``True`` (default), imports the produced shared 2025-08-26T19:56:09.3402993Z library as a Python module. If ``False``, behavior depends on 2025-08-26T19:56:09.3403105Z ``is_standalone``. 2025-08-26T19:56:09.3403314Z is_standalone: If ``False`` (default) loads the constructed extension 2025-08-26T19:56:09.3403522Z into the process as a plain dynamic library. If ``True``, build a 2025-08-26T19:56:09.3403629Z standalone executable. 2025-08-26T19:56:09.3403708Z 2025-08-26T19:56:09.3403803Z Returns: 2025-08-26T19:56:09.3403919Z If ``is_python_module`` is ``True``: 2025-08-26T19:56:09.3404098Z Returns the loaded PyTorch extension as a Python module. 2025-08-26T19:56:09.3404188Z 2025-08-26T19:56:09.3404424Z If ``is_python_module`` is ``False`` and ``is_standalone`` is ``False``: 2025-08-26T19:56:09.3404652Z Returns nothing. (The shared library is loaded into the process as 2025-08-26T19:56:09.3404747Z a side effect.) 2025-08-26T19:56:09.3404829Z 2025-08-26T19:56:09.3404953Z If ``is_standalone`` is ``True``. 2025-08-26T19:56:09.3405154Z Return the path to the executable. (On Windows, TORCH_LIB_PATH is 2025-08-26T19:56:09.3405344Z added to the PATH environment variable as a side effect.) 2025-08-26T19:56:09.3405426Z 2025-08-26T19:56:09.3405512Z Example: 2025-08-26T19:56:09.3405625Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3405767Z >>> from torch.utils.cpp_extension import load 2025-08-26T19:56:09.3405872Z >>> module = load( 2025-08-26T19:56:09.3405971Z ... name='extension', 2025-08-26T19:56:09.3406133Z ... sources=['extension.cpp', 'extension_kernel.cu'], 2025-08-26T19:56:09.3406252Z ... extra_cflags=['-O2'], 2025-08-26T19:56:09.3406373Z ... verbose=True) 2025-08-26T19:56:09.3406466Z 2025-08-26T19:56:09.3406726Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3406804Z 2025-08-26T19:56:09.3406912Z warnings.warn(msg) 2025-08-26T19:56:09.3406992Z 2025-08-26T19:56:09.3407198Z --- Parse Warning: 136 / 146 --- 2025-08-26T19:56:09.3408159Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=load_inline in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/cpp_extension.py line=1882. 2025-08-26T19:56:09.3408426Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3408524Z 2025-08-26T19:56:09.3408738Z Load a PyTorch C++ extension just-in-time (JIT) from string sources. 2025-08-26T19:56:09.3408916Z 2025-08-26T19:56:09.3409196Z This function behaves exactly like :func:`load`, but takes its sources as 2025-08-26T19:56:09.3409436Z strings rather than filenames. These strings are stored to files in the 2025-08-26T19:56:09.3409666Z build directory, after which the behavior of :func:`load_inline` is 2025-08-26T19:56:09.3409769Z identical to :func:`load`. 2025-08-26T19:56:09.3409863Z 2025-08-26T19:56:09.3409948Z See `the 2025-08-26T19:56:09.3410284Z tests `_ 2025-08-26T19:56:09.3410424Z for good examples of using this function. 2025-08-26T19:56:09.3410502Z 2025-08-26T19:56:09.3410742Z Sources may omit two required parts of a typical non-inline C++ extension: 2025-08-26T19:56:09.3411001Z the necessary header includes, as well as the (pybind11) binding code. More 2025-08-26T19:56:09.3411242Z precisely, strings passed to ``cpp_sources`` are first concatenated into a 2025-08-26T19:56:09.3411448Z single ``.cpp`` file. This file is then prepended with ``#include 2025-08-26T19:56:09.3411550Z `` 2025-08-26T19:56:09.3411631Z 2025-08-26T19:56:09.3411871Z Furthermore, if the ``functions`` argument is supplied, bindings will be 2025-08-26T19:56:09.3412109Z automatically generated for each function specified. ``functions`` can 2025-08-26T19:56:09.3412344Z either be a list of function names, or a dictionary mapping from function 2025-08-26T19:56:09.3412571Z names to docstrings. If a list is given, the name of each function is used 2025-08-26T19:56:09.3412679Z as its docstring. 2025-08-26T19:56:09.3412759Z 2025-08-26T19:56:09.3412977Z The sources in ``cuda_sources`` are concatenated into a separate ``.cu`` 2025-08-26T19:56:09.3413169Z file and prepended with ``torch/types.h``, ``cuda.h`` and 2025-08-26T19:56:09.3413379Z ``cuda_runtime.h`` includes. The ``.cpp`` and ``.cu`` files are compiled 2025-08-26T19:56:09.3413605Z separately, but ultimately linked into a single library. Note that no 2025-08-26T19:56:09.3413902Z bindings are generated for functions in ``cuda_sources`` per se. To bind 2025-08-26T19:56:09.3414123Z to a CUDA kernel, you must create a C++ function that calls it, and either 2025-08-26T19:56:09.3414354Z declare or define this C++ function in one of the ``cpp_sources`` (and 2025-08-26T19:56:09.3414464Z include its name in ``functions``). 2025-08-26T19:56:09.3414556Z 2025-08-26T19:56:09.3414778Z The sources in ``sycl_sources`` are concatenated into a separate ``.sycl`` 2025-08-26T19:56:09.3415000Z file and prepended with ``torch/types.h``, ``sycl/sycl.hpp`` includes. 2025-08-26T19:56:09.3415210Z The ``.cpp`` and ``.sycl`` files are compiled separately, but ultimately 2025-08-26T19:56:09.3415430Z linked into a single library. Note that no bindings are generated for 2025-08-26T19:56:09.3415662Z functions in ``sycl_sources`` per se. To bind to a SYCL kernel, you must 2025-08-26T19:56:09.3415873Z create a C++ function that calls it, and either declare or define this 2025-08-26T19:56:09.3416095Z C++ function in one of the ``cpp_sources`` (and include its name 2025-08-26T19:56:09.3416203Z in ``functions``). 2025-08-26T19:56:09.3416284Z 2025-08-26T19:56:09.3416376Z 2025-08-26T19:56:09.3416454Z 2025-08-26T19:56:09.3416639Z See :func:`load` for a description of arguments omitted below. 2025-08-26T19:56:09.3416732Z 2025-08-26T19:56:09.3416817Z Args: 2025-08-26T19:56:09.3417037Z cpp_sources: A string, or list of strings, containing C++ source code. 2025-08-26T19:56:09.3417300Z cuda_sources: A string, or list of strings, containing CUDA source code. 2025-08-26T19:56:09.3417525Z sycl_sources: A string, or list of strings, containing SYCL source code. 2025-08-26T19:56:09.3417747Z functions: A list of function names for which to generate function 2025-08-26T19:56:09.3417966Z bindings. If a dictionary is given, it should map function names to 2025-08-26T19:56:09.3418180Z docstrings (which are otherwise just the function names). 2025-08-26T19:56:09.3418420Z with_cuda: Determines whether CUDA headers and libraries are added to 2025-08-26T19:56:09.3418581Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:09.3418804Z automatically determined based on whether ``cuda_sources`` is 2025-08-26T19:56:09.3418958Z provided. Set it to ``True`` to force CUDA headers 2025-08-26T19:56:09.3419083Z and libraries to be included. 2025-08-26T19:56:09.3419308Z with_sycl: Determines whether SYCL headers and libraries are added to 2025-08-26T19:56:09.3419463Z the build. If set to ``None`` (default), this value is 2025-08-26T19:56:09.3419681Z automatically determined based on whether ``sycl_sources`` is 2025-08-26T19:56:09.3419836Z provided. Set it to ``True`` to force SYCL headers 2025-08-26T19:56:09.3419960Z and libraries to be included. 2025-08-26T19:56:09.3420174Z with_pytorch_error_handling: Determines whether pytorch error and 2025-08-26T19:56:09.3420376Z warning macros are handled by pytorch instead of pybind. To do 2025-08-26T19:56:09.3420611Z this, each function ``foo`` is called via an intermediary ``_safe_foo`` 2025-08-26T19:56:09.3420812Z function. This redirection might cause issues in obscure cases 2025-08-26T19:56:09.3421011Z of cpp. This flag should be set to ``False`` when this redirect 2025-08-26T19:56:09.3421102Z causes issues. 2025-08-26T19:56:09.3421363Z no_implicit_headers: If ``True``, skips automatically adding headers, most notably 2025-08-26T19:56:09.3421604Z ``#include `` and ``#include `` lines. 2025-08-26T19:56:09.3421764Z Use this option to improve cold start times when you 2025-08-26T19:56:09.3422038Z already include the necessary headers in your source code. Default: ``False``. 2025-08-26T19:56:09.3422147Z 2025-08-26T19:56:09.3422233Z Example: 2025-08-26T19:56:09.3422395Z >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_CPP_EXT) 2025-08-26T19:56:09.3422556Z >>> from torch.utils.cpp_extension import load_inline 2025-08-26T19:56:09.3422657Z >>> source = """ 2025-08-26T19:56:09.3422804Z at::Tensor sin_add(at::Tensor x, at::Tensor y) { 2025-08-26T19:56:09.3422904Z return x.sin() + y.sin(); 2025-08-26T19:56:09.3423003Z } 2025-08-26T19:56:09.3423083Z """ 2025-08-26T19:56:09.3423235Z >>> module = load_inline(name='inline_extension', 2025-08-26T19:56:09.3423361Z ... cpp_sources=[source], 2025-08-26T19:56:09.3423477Z ... functions=['sin_add']) 2025-08-26T19:56:09.3423568Z 2025-08-26T19:56:09.3423655Z .. note:: 2025-08-26T19:56:09.3423908Z Since load_inline will just-in-time compile the source code, please ensure 2025-08-26T19:56:09.3424146Z that you have the right toolchains installed in the runtime. For example, 2025-08-26T19:56:09.3424413Z when loading C++, make sure a C++ compiler is available. If you're loading 2025-08-26T19:56:09.3424673Z a CUDA extension, you will need to additionally install the corresponding CUDA 2025-08-26T19:56:09.3424923Z toolkit (nvcc and any other dependencies your code has). Compiling toolchains 2025-08-26T19:56:09.3425175Z are not included when you install torch and must be additionally installed. 2025-08-26T19:56:09.3425258Z 2025-08-26T19:56:09.3425541Z During compiling, by default, the Ninja backend uses #CPUS + 2 workers to build 2025-08-26T19:56:09.3425777Z the extension. This may use up too many resources on some systems. One 2025-08-26T19:56:09.3426000Z can control the number of workers by setting the `MAX_JOBS` environment 2025-08-26T19:56:09.3426127Z variable to a non-negative number. 2025-08-26T19:56:09.3426209Z 2025-08-26T19:56:09.3426489Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3426582Z 2025-08-26T19:56:09.3426682Z warnings.warn(msg) 2025-08-26T19:56:09.3426769Z 2025-08-26T19:56:09.3426984Z --- Parse Warning: 137 / 146 --- 2025-08-26T19:56:09.3427985Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ThroughputBenchmark in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/throughput_benchmark.py line=61. 2025-08-26T19:56:09.3428269Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3428349Z 2025-08-26T19:56:09.3428656Z This class is a wrapper around a c++ component throughput_benchmark::ThroughputBenchmark. 2025-08-26T19:56:09.3428736Z 2025-08-26T19:56:09.3429033Z This wrapper on the throughput_benchmark::ThroughputBenchmark component is responsible 2025-08-26T19:56:09.3429295Z for executing a PyTorch module (nn.Module or ScriptModule) under an inference 2025-08-26T19:56:09.3429534Z server like load. It can emulate multiple calling threads to a single module 2025-08-26T19:56:09.3429790Z provided. In the future we plan to enhance this component to support inter and 2025-08-26T19:56:09.3430035Z intra-op parallelism as well as multiple models running in a single process. 2025-08-26T19:56:09.3430111Z 2025-08-26T19:56:09.3430380Z Please note that even though nn.Module is supported, it might incur an overhead 2025-08-26T19:56:09.3430606Z from the need to hold GIL every time we execute Python code or pass around 2025-08-26T19:56:09.3430858Z inputs as Python objects. As soon as you have a ScriptModule version of your 2025-08-26T19:56:09.3431099Z model for inference deployment it is better to switch to using it in this 2025-08-26T19:56:09.3431193Z benchmark. 2025-08-26T19:56:09.3431271Z 2025-08-26T19:56:09.3431360Z Example:: 2025-08-26T19:56:09.3431474Z 2025-08-26T19:56:09.3431597Z >>> # xdoctest: +SKIP("undefined vars") 2025-08-26T19:56:09.3431741Z >>> from torch.utils import ThroughputBenchmark 2025-08-26T19:56:09.3431878Z >>> bench = ThroughputBenchmark(my_module) 2025-08-26T19:56:09.3432038Z >>> # Pre-populate benchmark's data set with the inputs 2025-08-26T19:56:09.3432146Z >>> for input in inputs: 2025-08-26T19:56:09.3432370Z ... # Both args and kwargs work, same as any PyTorch Module / ScriptModule 2025-08-26T19:56:09.3432502Z ... bench.add_input(input[0], x2=input[1]) 2025-08-26T19:56:09.3432712Z >>> # Inputs supplied above are randomly used during the execution 2025-08-26T19:56:09.3432820Z >>> stats = bench.benchmark( 2025-08-26T19:56:09.3432929Z ... num_calling_threads=4, 2025-08-26T19:56:09.3433033Z ... num_warmup_iters = 100, 2025-08-26T19:56:09.3433129Z ... num_iters = 1000, 2025-08-26T19:56:09.3433217Z ... ) 2025-08-26T19:56:09.3433407Z >>> print("Avg latency (ms): {}".format(stats.latency_avg_ms)) 2025-08-26T19:56:09.3433621Z >>> print("Number of iterations: {}".format(stats.num_iters)) 2025-08-26T19:56:09.3433705Z 2025-08-26T19:56:09.3433958Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3434047Z 2025-08-26T19:56:09.3434146Z warnings.warn(msg) 2025-08-26T19:56:09.3434232Z 2025-08-26T19:56:09.3434425Z --- Parse Warning: 138 / 146 --- 2025-08-26T19:56:09.3435422Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DistributedSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/distributed.py line=18. 2025-08-26T19:56:09.3435697Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3435904Z Sampler that restricts data loading to a subset of the dataset. 2025-08-26T19:56:09.3436015Z 2025-08-26T19:56:09.3436153Z It is especially useful in conjunction with 2025-08-26T19:56:09.3436405Z :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each 2025-08-26T19:56:09.3436673Z process can pass a :class:`~torch.utils.data.DistributedSampler` instance as a 2025-08-26T19:56:09.3436904Z :class:`~torch.utils.data.DataLoader` sampler, and load a subset of the 2025-08-26T19:56:09.3437045Z original dataset that is exclusive to it. 2025-08-26T19:56:09.3437125Z 2025-08-26T19:56:09.3437211Z .. note:: 2025-08-26T19:56:09.3437635Z Dataset is assumed to be of constant size and that any instance of it always 2025-08-26T19:56:09.3437778Z returns the same elements in the same order. 2025-08-26T19:56:09.3437866Z 2025-08-26T19:56:09.3437950Z Args: 2025-08-26T19:56:09.3438071Z dataset: Dataset used for sampling. 2025-08-26T19:56:09.3438304Z num_replicas (int, optional): Number of processes participating in 2025-08-26T19:56:09.3438566Z distributed training. By default, :attr:`world_size` is retrieved from the 2025-08-26T19:56:09.3438690Z current distributed group. 2025-08-26T19:56:09.3438933Z rank (int, optional): Rank of the current process within :attr:`num_replicas`. 2025-08-26T19:56:09.3439134Z By default, :attr:`rank` is retrieved from the current distributed 2025-08-26T19:56:09.3439233Z group. 2025-08-26T19:56:09.3439460Z shuffle (bool, optional): If ``True`` (default), sampler will shuffle the 2025-08-26T19:56:09.3439561Z indices. 2025-08-26T19:56:09.3439755Z seed (int, optional): random seed used to shuffle the sampler if 2025-08-26T19:56:09.3439952Z :attr:`shuffle=True`. This number should be identical across all 2025-08-26T19:56:09.3440126Z processes in the distributed group. Default: ``0``. 2025-08-26T19:56:09.3440405Z drop_last (bool, optional): if ``True``, then the sampler will drop the 2025-08-26T19:56:09.3440615Z tail of the data to make it evenly divisible across the number of 2025-08-26T19:56:09.3440817Z replicas. If ``False``, the sampler will add extra indices to make 2025-08-26T19:56:09.3441042Z the data evenly divisible across the replicas. Default: ``False``. 2025-08-26T19:56:09.3441124Z 2025-08-26T19:56:09.3441215Z .. warning:: 2025-08-26T19:56:09.3441416Z In distributed mode, calling the :meth:`set_epoch` method at 2025-08-26T19:56:09.3441673Z the beginning of each epoch **before** creating the :class:`DataLoader` iterator 2025-08-26T19:56:09.3441947Z is necessary to make shuffling work properly across multiple epochs. Otherwise, 2025-08-26T19:56:09.3442071Z the same ordering will be always used. 2025-08-26T19:56:09.3442150Z 2025-08-26T19:56:09.3442245Z Example:: 2025-08-26T19:56:09.3442332Z 2025-08-26T19:56:09.3442432Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3442700Z >>> sampler = DistributedSampler(dataset) if is_distributed else None 2025-08-26T19:56:09.3442874Z >>> loader = DataLoader(dataset, shuffle=(sampler is None), 2025-08-26T19:56:09.3443006Z ... sampler=sampler) 2025-08-26T19:56:09.3443142Z >>> for epoch in range(start_epoch, n_epochs): 2025-08-26T19:56:09.3443243Z ... if is_distributed: 2025-08-26T19:56:09.3443369Z ... sampler.set_epoch(epoch) 2025-08-26T19:56:09.3443497Z ... train(loader) 2025-08-26T19:56:09.3443588Z 2025-08-26T19:56:09.3443847Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3443925Z 2025-08-26T19:56:09.3444033Z warnings.warn(msg) 2025-08-26T19:56:09.3444112Z 2025-08-26T19:56:09.3444362Z --- Parse Warning: 139 / 146 --- 2025-08-26T19:56:09.3445336Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=WeightedRandomSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=227. 2025-08-26T19:56:09.3445602Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3445868Z Samples elements from ``[0,..,len(weights)-1]`` with given probabilities (weights). 2025-08-26T19:56:09.3445950Z 2025-08-26T19:56:09.3446040Z Args: 2025-08-26T19:56:09.3446293Z weights (sequence) : a sequence of weights, not necessary summing up to one 2025-08-26T19:56:09.3446433Z num_samples (int): number of samples to draw 2025-08-26T19:56:09.3446658Z replacement (bool): if ``True``, samples are drawn with replacement. 2025-08-26T19:56:09.3446867Z If not, they are drawn without replacement, which means that when a 2025-08-26T19:56:09.3447100Z sample index is drawn for a row, it cannot be drawn again for that row. 2025-08-26T19:56:09.3447264Z generator (Generator): Generator used in sampling. 2025-08-26T19:56:09.3447340Z 2025-08-26T19:56:09.3447435Z Example: 2025-08-26T19:56:09.3447578Z >>> # xdoctest: +IGNORE_WANT("non-deterministic") 2025-08-26T19:56:09.3447669Z >>> list( 2025-08-26T19:56:09.3447783Z ... WeightedRandomSampler( 2025-08-26T19:56:09.3447923Z ... [0.1, 0.9, 0.4, 0.7, 3.0, 0.6], 5, replacement=True 2025-08-26T19:56:09.3448017Z ... ) 2025-08-26T19:56:09.3448103Z ... ) 2025-08-26T19:56:09.3448200Z [4, 4, 1, 4, 5] 2025-08-26T19:56:09.3448285Z >>> list( 2025-08-26T19:56:09.3448397Z ... WeightedRandomSampler( 2025-08-26T19:56:09.3448549Z ... [0.9, 0.4, 0.05, 0.2, 0.3, 0.1], 5, replacement=False 2025-08-26T19:56:09.3448637Z ... ) 2025-08-26T19:56:09.3448751Z ... ) 2025-08-26T19:56:09.3448900Z [0, 1, 4, 3, 2] 2025-08-26T19:56:09.3448986Z 2025-08-26T19:56:09.3449255Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3449337Z 2025-08-26T19:56:09.3449434Z warnings.warn(msg) 2025-08-26T19:56:09.3449527Z 2025-08-26T19:56:09.3449725Z --- Parse Warning: 140 / 146 --- 2025-08-26T19:56:09.3450656Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=BatchSampler in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/sampler.py line=300. 2025-08-26T19:56:09.3450925Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3451108Z Wraps another sampler to yield a mini-batch of indices. 2025-08-26T19:56:09.3451188Z 2025-08-26T19:56:09.3451271Z Args: 2025-08-26T19:56:09.3451512Z sampler (Sampler or Iterable): Base sampler. Can be any iterable object 2025-08-26T19:56:09.3451671Z batch_size (int): Size of mini-batch. 2025-08-26T19:56:09.3451883Z drop_last (bool): If ``True``, the sampler will drop the last batch if 2025-08-26T19:56:09.3452016Z its size would be less than ``batch_size`` 2025-08-26T19:56:09.3452097Z 2025-08-26T19:56:09.3456334Z Example: 2025-08-26T19:56:09.3456447Z >>> list( 2025-08-26T19:56:09.3456552Z ... BatchSampler( 2025-08-26T19:56:09.3456839Z ... SequentialSampler(range(10)), batch_size=3, drop_last=False 2025-08-26T19:56:09.3456926Z ... ) 2025-08-26T19:56:09.3457017Z ... ) 2025-08-26T19:56:09.3457125Z [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9]] 2025-08-26T19:56:09.3457215Z >>> list( 2025-08-26T19:56:09.3457493Z ... BatchSampler(SequentialSampler(range(10)), batch_size=3, drop_last=True) 2025-08-26T19:56:09.3457614Z ... ) 2025-08-26T19:56:09.3457728Z [[0, 1, 2], [3, 4, 5], [6, 7, 8]] 2025-08-26T19:56:09.3457812Z 2025-08-26T19:56:09.3458072Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3458160Z 2025-08-26T19:56:09.3458258Z warnings.warn(msg) 2025-08-26T19:56:09.3458337Z 2025-08-26T19:56:09.3458577Z --- Parse Warning: 141 / 146 --- 2025-08-26T19:56:09.3459569Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=IterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/datapipe.py line=56. 2025-08-26T19:56:09.3459850Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3459931Z 2025-08-26T19:56:09.3460047Z Iterable-style DataPipe. 2025-08-26T19:56:09.3460125Z 2025-08-26T19:56:09.3460390Z All DataPipes that represent an iterable of data samples should subclass this. 2025-08-26T19:56:09.3460661Z This style of DataPipes is particularly useful when data come from a stream, or 2025-08-26T19:56:09.3461030Z when the number of samples is too large to fit them all in memory. ``IterDataPipe`` is lazily initialized and its 2025-08-26T19:56:09.3461335Z elements are computed only when ``next()`` is called on the iterator of an ``IterDataPipe``. 2025-08-26T19:56:09.3461412Z 2025-08-26T19:56:09.3461645Z All subclasses should overwrite :meth:`__iter__`, which would return an 2025-08-26T19:56:09.3462008Z iterator of samples in this DataPipe. Calling ``__iter__`` of an ``IterDataPipe`` automatically invokes its 2025-08-26T19:56:09.3462383Z method ``reset()``, which by default performs no operation. When writing a custom ``IterDataPipe``, users should 2025-08-26T19:56:09.3462677Z override ``reset()`` if necessary. The common usages include resetting buffers, pointers, 2025-08-26T19:56:09.3462965Z and various state variables within the custom ``IterDataPipe``. 2025-08-26T19:56:09.3463048Z 2025-08-26T19:56:09.3463139Z Note: 2025-08-26T19:56:09.3463356Z Only `one` iterator can be valid for each ``IterDataPipe`` at a time, 2025-08-26T19:56:09.3463724Z and the creation a second iterator will invalidate the first one. This constraint is necessary because 2025-08-26T19:56:09.3464104Z some ``IterDataPipe`` have internal buffers, whose states can become invalid if there are multiple iterators. 2025-08-26T19:56:09.3464383Z The code example below presents details on how this constraint looks in practice. 2025-08-26T19:56:09.3464765Z If you have any feedback related to this constraint, please see `GitHub IterDataPipe Single Iterator Issue`_. 2025-08-26T19:56:09.3464846Z 2025-08-26T19:56:09.3465144Z These DataPipes can be invoked in two ways, using the class constructor or applying their 2025-08-26T19:56:09.3465513Z functional form onto an existing ``IterDataPipe`` (recommended, available to most but not all DataPipes). 2025-08-26T19:56:09.3465873Z You can chain multiple `IterDataPipe` together to form a pipeline that will perform multiple 2025-08-26T19:56:09.3465977Z operations in succession. 2025-08-26T19:56:09.3466057Z 2025-08-26T19:56:09.3466208Z .. _GitHub IterDataPipe Single Iterator Issue: 2025-08-26T19:56:09.3466351Z https://github.com/pytorch/data/issues/45 2025-08-26T19:56:09.3466430Z 2025-08-26T19:56:09.3466521Z Note: 2025-08-26T19:56:09.3466755Z When a subclass is used with :class:`~torch.utils.data.DataLoader`, each 2025-08-26T19:56:09.3467060Z item in the DataPipe will be yielded from the :class:`~torch.utils.data.DataLoader` 2025-08-26T19:56:09.3467285Z iterator. When :attr:`num_workers > 0`, each worker process will have a 2025-08-26T19:56:09.3467527Z different copy of the DataPipe object, so it is often desired to configure 2025-08-26T19:56:09.3467806Z each copy independently to avoid having duplicate data returned from the 2025-08-26T19:56:09.3468055Z workers. :func:`~torch.utils.data.get_worker_info`, when called in a worker 2025-08-26T19:56:09.3468316Z process, returns information about the worker. It can be used in either the 2025-08-26T19:56:09.3468564Z dataset's :meth:`__iter__` method or the :class:`~torch.utils.data.DataLoader` 's 2025-08-26T19:56:09.3468759Z :attr:`worker_init_fn` option to modify each copy's behavior. 2025-08-26T19:56:09.3468837Z 2025-08-26T19:56:09.3468924Z Examples: 2025-08-26T19:56:09.3469022Z General Usage: 2025-08-26T19:56:09.3469122Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3469349Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T19:56:09.3469472Z >>> dp = IterableWrapper(range(10)) 2025-08-26T19:56:09.3469660Z >>> map_dp_1 = Mapper(dp, lambda x: x + 1) # Using class constructor 2025-08-26T19:56:09.3469769Z >>> map_dp_2 = dp.map( 2025-08-26T19:56:09.3469873Z ... lambda x: x + 1 2025-08-26T19:56:09.3470023Z ... ) # Using functional form (recommended) 2025-08-26T19:56:09.3470119Z >>> list(map_dp_1) 2025-08-26T19:56:09.3470218Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T19:56:09.3470321Z >>> list(map_dp_2) 2025-08-26T19:56:09.3470417Z [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 2025-08-26T19:56:09.3470574Z >>> filter_dp = map_dp_1.filter(lambda x: x % 2 == 0) 2025-08-26T19:56:09.3470681Z >>> list(filter_dp) 2025-08-26T19:56:09.3470774Z [2, 4, 6, 8, 10] 2025-08-26T19:56:09.3470896Z Single Iterator Constraint Example: 2025-08-26T19:56:09.3471110Z >>> from torchdata.datapipes.iter import IterableWrapper, Mapper 2025-08-26T19:56:09.3471246Z >>> source_dp = IterableWrapper(range(10)) 2025-08-26T19:56:09.3471357Z >>> it1 = iter(source_dp) 2025-08-26T19:56:09.3471448Z >>> list(it1) 2025-08-26T19:56:09.3471585Z [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] 2025-08-26T19:56:09.3471691Z >>> it1 = iter(source_dp) 2025-08-26T19:56:09.3471784Z >>> it2 = iter( 2025-08-26T19:56:09.3471888Z ... source_dp 2025-08-26T19:56:09.3472047Z ... ) # The creation of a new iterator invalidates `it1` 2025-08-26T19:56:09.3472147Z >>> next(it2) 2025-08-26T19:56:09.3472229Z 0 2025-08-26T19:56:09.3472418Z >>> next(it1) # Further usage of `it1` will raise a `RunTimeError` 2025-08-26T19:56:09.3472507Z 2025-08-26T19:56:09.3472764Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3472850Z 2025-08-26T19:56:09.3472945Z warnings.warn(msg) 2025-08-26T19:56:09.3473023Z 2025-08-26T19:56:09.3473235Z --- Parse Warning: 142 / 146 --- 2025-08-26T19:56:09.3474337Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=DemultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=375. 2025-08-26T19:56:09.3474648Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3474726Z 2025-08-26T19:56:09.3475195Z Splits the input DataPipe into multiple child DataPipes, using the given classification function (functional name: ``demux``). 2025-08-26T19:56:09.3475284Z 2025-08-26T19:56:09.3475471Z A list of the child DataPipes is returned from this operation. 2025-08-26T19:56:09.3475588Z 2025-08-26T19:56:09.3475673Z Args: 2025-08-26T19:56:09.3475811Z datapipe: Iterable DataPipe being filtered 2025-08-26T19:56:09.3476017Z num_instances: number of instances of the DataPipe to create 2025-08-26T19:56:09.3476419Z classifier_fn: a function that maps values to an integer within the range ``[0, num_instances - 1]`` or ``None`` 2025-08-26T19:56:09.3476764Z drop_none: defaults to ``False``, if ``True``, the function will skip over elements classified as ``None`` 2025-08-26T19:56:09.3477090Z buffer_size: this defines the maximum number of inputs that the buffer can hold across all child 2025-08-26T19:56:09.3477274Z DataPipes while waiting for their values to be yielded. 2025-08-26T19:56:09.3477457Z Defaults to ``1000``. Use ``-1`` for the unlimited buffer. 2025-08-26T19:56:09.3477539Z 2025-08-26T19:56:09.3477634Z Examples: 2025-08-26T19:56:09.3477758Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T19:56:09.3477937Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:09.3478042Z >>> def odd_or_even(n): 2025-08-26T19:56:09.3478135Z ... return n % 2 2025-08-26T19:56:09.3478268Z >>> source_dp = IterableWrapper(range(5)) 2025-08-26T19:56:09.3478480Z >>> dp1, dp2 = source_dp.demux(num_instances=2, classifier_fn=odd_or_even) 2025-08-26T19:56:09.3478570Z >>> list(dp1) 2025-08-26T19:56:09.3478660Z [0, 2, 4] 2025-08-26T19:56:09.3478745Z >>> list(dp2) 2025-08-26T19:56:09.3478834Z [1, 3] 2025-08-26T19:56:09.3479074Z >>> # It can also filter out any element that gets `None` from the `classifier_fn` 2025-08-26T19:56:09.3479181Z >>> def odd_or_even_no_zero(n): 2025-08-26T19:56:09.3479300Z ... return n % 2 if n != 0 else None 2025-08-26T19:56:09.3479407Z >>> dp1, dp2 = source_dp.demux( 2025-08-26T19:56:09.3479635Z ... num_instances=2, classifier_fn=odd_or_even_no_zero, drop_none=True 2025-08-26T19:56:09.3479718Z ... ) 2025-08-26T19:56:09.3479804Z >>> list(dp1) 2025-08-26T19:56:09.3479894Z [2, 4] 2025-08-26T19:56:09.3479981Z >>> list(dp2) 2025-08-26T19:56:09.3480062Z [1, 3] 2025-08-26T19:56:09.3480150Z 2025-08-26T19:56:09.3480411Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3480528Z 2025-08-26T19:56:09.3480626Z warnings.warn(msg) 2025-08-26T19:56:09.3480704Z 2025-08-26T19:56:09.3480908Z --- Parse Warning: 143 / 146 --- 2025-08-26T19:56:09.3481988Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=MultiplexerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=594. 2025-08-26T19:56:09.3482265Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3482344Z 2025-08-26T19:56:09.3482663Z Yields one element at a time from each of the input Iterable DataPipes (functional name: ``mux``). 2025-08-26T19:56:09.3482750Z 2025-08-26T19:56:09.3483105Z As in, one element from the 1st input DataPipe, then one element from the 2nd DataPipe in the next iteration, 2025-08-26T19:56:09.3483307Z and so on. It ends when the shortest input DataPipe is exhausted. 2025-08-26T19:56:09.3483418Z 2025-08-26T19:56:09.3483502Z Args: 2025-08-26T19:56:09.3483924Z datapipes: Iterable DataPipes that will take turn to yield their elements, until the shortest DataPipe is exhausted 2025-08-26T19:56:09.3484005Z 2025-08-26T19:56:09.3484101Z Example: 2025-08-26T19:56:09.3484230Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T19:56:09.3484410Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:09.3484516Z >>> dp1, dp2, dp3 = ( 2025-08-26T19:56:09.3484632Z ... IterableWrapper(range(3)), 2025-08-26T19:56:09.3484790Z ... IterableWrapper(range(10, 15)), 2025-08-26T19:56:09.3484911Z ... IterableWrapper(range(20, 25)), 2025-08-26T19:56:09.3484994Z ... ) 2025-08-26T19:56:09.3485105Z >>> list(dp1.mux(dp2, dp3)) 2025-08-26T19:56:09.3485201Z [0, 10, 20, 1, 11, 21, 2, 12, 22] 2025-08-26T19:56:09.3485288Z 2025-08-26T19:56:09.3485573Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3485657Z 2025-08-26T19:56:09.3485764Z warnings.warn(msg) 2025-08-26T19:56:09.3485844Z 2025-08-26T19:56:09.3486037Z --- Parse Warning: 144 / 146 --- 2025-08-26T19:56:09.3487098Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=ZipperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/combining.py line=665. 2025-08-26T19:56:09.3487367Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3487449Z 2025-08-26T19:56:09.3487763Z Aggregates elements into a tuple from each of the input DataPipes (functional name: ``zip``). 2025-08-26T19:56:09.3487850Z 2025-08-26T19:56:09.3488082Z The output is stopped as soon as the shortest input DataPipe is exhausted. 2025-08-26T19:56:09.3488160Z 2025-08-26T19:56:09.3488255Z Args: 2025-08-26T19:56:09.3488409Z *datapipes: Iterable DataPipes being aggregated 2025-08-26T19:56:09.3488498Z 2025-08-26T19:56:09.3488584Z Example: 2025-08-26T19:56:09.3488712Z >>> # xdoctest: +REQUIRES(module:torchdata) 2025-08-26T19:56:09.3488989Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:09.3489089Z >>> dp1, dp2, dp3 = ( 2025-08-26T19:56:09.3489206Z ... IterableWrapper(range(5)), 2025-08-26T19:56:09.3489338Z ... IterableWrapper(range(10, 15)), 2025-08-26T19:56:09.3489461Z ... IterableWrapper(range(20, 25)), 2025-08-26T19:56:09.3489554Z ... ) 2025-08-26T19:56:09.3489658Z >>> list(dp1.zip(dp2, dp3)) 2025-08-26T19:56:09.3489792Z [(0, 10, 20), (1, 11, 21), (2, 12, 22), (3, 13, 23), (4, 14, 24)] 2025-08-26T19:56:09.3489884Z 2025-08-26T19:56:09.3490142Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3490267Z 2025-08-26T19:56:09.3490365Z warnings.warn(msg) 2025-08-26T19:56:09.3490445Z 2025-08-26T19:56:09.3490653Z --- Parse Warning: 145 / 146 --- 2025-08-26T19:56:09.3491724Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=FileOpenerIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/fileopener.py line=18. 2025-08-26T19:56:09.3492000Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3492080Z 2025-08-26T19:56:09.3492464Z Given pathnames, opens files and yield pathname and file stream in a tuple (functional name: ``open_files``). 2025-08-26T19:56:09.3492555Z 2025-08-26T19:56:09.3492637Z Args: 2025-08-26T19:56:09.3492814Z datapipe: Iterable datapipe that provides pathnames 2025-08-26T19:56:09.3492995Z mode: An optional string that specifies the mode in which 2025-08-26T19:56:09.3493212Z the file is opened by ``open()``. It defaults to ``r``, other options are 2025-08-26T19:56:09.3493411Z ``b`` for reading in binary mode and ``t`` for text mode. 2025-08-26T19:56:09.3493617Z encoding: An optional string that specifies the encoding of the 2025-08-26T19:56:09.3493888Z underlying file. It defaults to ``None`` to match the default encoding of ``open``. 2025-08-26T19:56:09.3494011Z length: Nominal length of the datapipe 2025-08-26T19:56:09.3494088Z 2025-08-26T19:56:09.3494179Z Note: 2025-08-26T19:56:09.3494478Z The opened file handles will be closed by Python's GC periodically. Users can choose 2025-08-26T19:56:09.3494595Z to close them explicitly. 2025-08-26T19:56:09.3494678Z 2025-08-26T19:56:09.3494759Z Example: 2025-08-26T19:56:09.3494866Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3495003Z >>> from torchdata.datapipes.iter import ( 2025-08-26T19:56:09.3495144Z ... FileLister, 2025-08-26T19:56:09.3495240Z ... FileOpener, 2025-08-26T19:56:09.3495336Z ... StreamReader, 2025-08-26T19:56:09.3495426Z ... ) 2025-08-26T19:56:09.3495646Z >>> dp = FileLister(root=".").filter(lambda fname: fname.endswith(".txt")) 2025-08-26T19:56:09.3495752Z >>> dp = FileOpener(dp) 2025-08-26T19:56:09.3495856Z >>> dp = StreamReader(dp) 2025-08-26T19:56:09.3495938Z >>> list(dp) 2025-08-26T19:56:09.3496041Z [('./abc.txt', 'abc')] 2025-08-26T19:56:09.3496123Z 2025-08-26T19:56:09.3496378Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3496469Z 2025-08-26T19:56:09.3496564Z warnings.warn(msg) 2025-08-26T19:56:09.3496657Z 2025-08-26T19:56:09.3496847Z --- Parse Warning: 146 / 146 --- 2025-08-26T19:56:09.3497902Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/xdoctest/core.py:423: UserWarning: Cannot scrape callname=GrouperIterDataPipe in modpath=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/utils/data/datapipes/iter/grouping.py line=155. 2025-08-26T19:56:09.3498178Z Caused by: DoctestParseError('Failed to parse doctest in _label_docsrc_lines') 2025-08-26T19:56:09.3498252Z 2025-08-26T19:56:09.3498677Z Groups data from IterDataPipe by keys from ``group_key_fn``, yielding a ``DataChunk`` with batch size up to ``group_size``. 2025-08-26T19:56:09.3498756Z 2025-08-26T19:56:09.3498861Z (functional name: ``groupby``). 2025-08-26T19:56:09.3498951Z 2025-08-26T19:56:09.3499344Z The samples are read sequentially from the source ``datapipe``, and a batch of samples belonging to the same group 2025-08-26T19:56:09.3499652Z will be yielded as soon as the size of the batch reaches ``group_size``. When the buffer is full, 2025-08-26T19:56:09.3499959Z the DataPipe will yield the largest batch with the same key, provided that its size is larger 2025-08-26T19:56:09.3500291Z than ``guaranteed_group_size``. If its size is smaller, it will be dropped if ``drop_remaining=True``. 2025-08-26T19:56:09.3500400Z 2025-08-26T19:56:09.3500783Z After iterating through the entirety of source ``datapipe``, everything not dropped due to the buffer capacity 2025-08-26T19:56:09.3501113Z will be yielded from the buffer, even if the group sizes are smaller than ``guaranteed_group_size``. 2025-08-26T19:56:09.3501195Z 2025-08-26T19:56:09.3501285Z Args: 2025-08-26T19:56:09.3501420Z datapipe: Iterable datapipe to be grouped 2025-08-26T19:56:09.3501702Z group_key_fn: Function used to generate group key from the data of the source datapipe 2025-08-26T19:56:09.3501946Z keep_key: Option to yield the matching key along with the items in a tuple, 2025-08-26T19:56:09.3502126Z resulting in `(key, [items])` otherwise returning [items] 2025-08-26T19:56:09.3502288Z buffer_size: The size of buffer for ungrouped data 2025-08-26T19:56:09.3502572Z group_size: The max size of each group, a batch is yielded as soon as it reaches this size 2025-08-26T19:56:09.3502946Z guaranteed_group_size: The guaranteed minimum group size to be yielded in case the buffer is full 2025-08-26T19:56:09.3503319Z drop_remaining: Specifies if the group smaller than ``guaranteed_group_size`` will be dropped from buffer 2025-08-26T19:56:09.3503422Z when the buffer is full 2025-08-26T19:56:09.3503513Z 2025-08-26T19:56:09.3503599Z Example: 2025-08-26T19:56:09.3503685Z >>> import os 2025-08-26T19:56:09.3503791Z >>> # xdoctest: +SKIP 2025-08-26T19:56:09.3503997Z >>> from torchdata.datapipes.iter import IterableWrapper 2025-08-26T19:56:09.3504106Z >>> def group_fn(file): 2025-08-26T19:56:09.3504252Z ... return os.path.basename(file).split(".")[0] 2025-08-26T19:56:09.3504364Z >>> source_dp = IterableWrapper( 2025-08-26T19:56:09.3504536Z ... ["a.png", "b.png", "a.json", "b.json", "a.jpg", "c.json"] 2025-08-26T19:56:09.3504646Z ... ) 2025-08-26T19:56:09.3504801Z >>> dp0 = source_dp.groupby(group_key_fn=group_fn) 2025-08-26T19:56:09.3504887Z >>> list(dp0) 2025-08-26T19:56:09.3505048Z [['a.png', 'a.json', 'a.jpg'], ['b.png', 'b.json'], ['c.json']] 2025-08-26T19:56:09.3505248Z >>> # A group is yielded as soon as its size equals to `group_size` 2025-08-26T19:56:09.3505437Z >>> dp1 = source_dp.groupby(group_key_fn=group_fn, group_size=2) 2025-08-26T19:56:09.3505532Z >>> list(dp1) 2025-08-26T19:56:09.3505694Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T19:56:09.3506050Z >>> # Scenario where `buffer` is full, and group 'a' needs to be yielded since its size > `guaranteed_group_size` 2025-08-26T19:56:09.3506170Z >>> dp2 = source_dp.groupby( 2025-08-26T19:56:09.3506275Z ... group_key_fn=group_fn, 2025-08-26T19:56:09.3506380Z ... buffer_size=3, 2025-08-26T19:56:09.3506476Z ... group_size=3, 2025-08-26T19:56:09.3506585Z ... guaranteed_group_size=2, 2025-08-26T19:56:09.3506678Z ... ) 2025-08-26T19:56:09.3506767Z >>> list(dp2) 2025-08-26T19:56:09.3506936Z [['a.png', 'a.json'], ['b.png', 'b.json'], ['a.jpg'], ['c.json']] 2025-08-26T19:56:09.3507016Z 2025-08-26T19:56:09.3507271Z Original Error: TokenError('unexpected EOF in multi-line statement', (1, 0)) 2025-08-26T19:56:09.3507360Z 2025-08-26T19:56:09.3507457Z warnings.warn(msg) 2025-08-26T19:56:09.3507536Z 2025-08-26T19:56:09.3507658Z  2025-08-26T19:56:09.3507833Z === Found 8 run-time warnings === 2025-08-26T19:56:09.3508021Z --- Runtime Warning: 1 / 8 --- 2025-08-26T19:56:09.3508286Z example = 2025-08-26T19:56:09.3509680Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/_tensor.py:1351: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /var/lib/jenkins/workspace/c10/core/TensorImpl.h:1974.) 2025-08-26T19:56:09.3509838Z return super().refine_names(names) 2025-08-26T19:56:09.3509916Z 2025-08-26T19:56:09.3510106Z --- Runtime Warning: 2 / 8 --- 2025-08-26T19:56:09.3510418Z example = 2025-08-26T19:56:09.3511077Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/library.py:282: UserWarning: Warning only once for all operators, other operators may also be overridden. 2025-08-26T19:56:09.3511395Z Overriding a previously registered kernel for the same operator and the same dispatch key 2025-08-26T19:56:09.3511600Z operator: aten::div.Tensor(Tensor self, Tensor other) -> Tensor 2025-08-26T19:56:09.3511912Z registered at /var/lib/jenkins/workspace/build/aten/src/ATen/RegisterSchema.cpp:6 2025-08-26T19:56:09.3512011Z dispatch key: CPU 2025-08-26T19:56:09.3512486Z previous kernel: registered at /var/lib/jenkins/workspace/aten/src/ATen/LegacyBatchingRegistrations.cpp:1079 2025-08-26T19:56:09.3513050Z new kernel: registered at /dev/null:811 (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/core/dispatch/OperatorEntry.cpp:225.) 2025-08-26T19:56:09.3513222Z impl_fn(self.ns, name.split("::")[-1], dispatch_key) 2025-08-26T19:56:09.3513302Z 2025-08-26T19:56:09.3513481Z --- Runtime Warning: 3 / 8 --- 2025-08-26T19:56:09.3513767Z example = 2025-08-26T19:56:09.3515686Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nested/__init__.py:117: UserWarning: The PyTorch API of nested tensors is in prototype stage and will change in the near future. We recommend specifying layout=torch.jagged when constructing a nested tensor, as this layout receives active development, has better operator coverage, and works with torch.compile. (Triggered internally at /var/lib/jenkins/workspace/aten/src/ATen/NestedTensorImpl.cpp:182.) 2025-08-26T19:56:09.3515948Z return torch._nested_tensor_from_tensor_list(ts, dtype, None, device, None) 2025-08-26T19:56:09.3516028Z 2025-08-26T19:56:09.3516216Z --- Runtime Warning: 4 / 8 --- 2025-08-26T19:56:09.3516529Z example = 2025-08-26T19:56:09.3518073Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/fx/experimental/const_fold.py:271: UserWarning: Attempted to insert a get_attr Node with no underlying reference in the owning GraphModule! Call GraphModule.add_submodule to add the necessary submodule, GraphModule.add_parameter to add the necessary Parameter, or nn.Module.register_buffer to add the necessary buffer 2025-08-26T19:56:09.3518251Z new_node = root_const_gm.graph.get_attr(in_node.target) 2025-08-26T19:56:09.3518334Z 2025-08-26T19:56:09.3518523Z --- Runtime Warning: 5 / 8 --- 2025-08-26T19:56:09.3518820Z example = 2025-08-26T19:56:09.3519941Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) 2025-08-26T19:56:09.3520034Z warnings.warn( 2025-08-26T19:56:09.3520113Z 2025-08-26T19:56:09.3520299Z --- Runtime Warning: 6 / 8 --- 2025-08-26T19:56:09.3520634Z example = 2025-08-26T19:56:09.3521744Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/modules/transformer.py:392: UserWarning: enable_nested_tensor is True, but self.use_nested_tensor is False because encoder_layer.self_attn.batch_first was not True(use batch_first for better inference performance) 2025-08-26T19:56:09.3521866Z warnings.warn( 2025-08-26T19:56:09.3521946Z 2025-08-26T19:56:09.3522133Z --- Runtime Warning: 7 / 8 --- 2025-08-26T19:56:09.3522413Z example = 2025-08-26T19:56:09.3523255Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`. 2025-08-26T19:56:09.3523380Z WeightNorm.apply(module, name, dim) 2025-08-26T19:56:09.3523461Z 2025-08-26T19:56:09.3523650Z --- Runtime Warning: 8 / 8 --- 2025-08-26T19:56:09.3523959Z example = 2025-08-26T19:56:09.3524795Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/nn/utils/weight_norm.py:144: FutureWarning: `torch.nn.utils.weight_norm` is deprecated in favor of `torch.nn.utils.parametrizations.weight_norm`. 2025-08-26T19:56:09.3525220Z WeightNorm.apply(module, name, dim) 2025-08-26T19:56:09.3525312Z 2025-08-26T19:56:09.3525639Z === 338 passed, 393 skipped, 154 warnings in 14.87 seconds === 2025-08-26T19:56:09.3525864Z Running inductor/test_max_autotune 1/1 ... [2025-08-26 19:56:09.096050] 2025-08-26T19:56:09.3525989Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:56:09.3526915Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_max_autotune.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:56:09.096403] 2025-08-26T19:56:19.0187824Z 2025-08-26T19:56:19.0188991Z inductor/test_max_autotune 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_max_autotune_1.1_6203e0c55a5eb33a_.log 2025-08-26T19:56:19.0189791Z 2025-08-26T19:56:19.0192466Z Running inductor/test_benchmark_fusion 1/1 ... [2025-08-26 19:56:19.019105] 2025-08-26T19:56:19.0192954Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:56:19.0196274Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_benchmark_fusion.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:56:19.019431] 2025-08-26T19:56:35.8556100Z 2025-08-26T19:56:35.8557632Z inductor/test_benchmark_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_benchmark_fusion_1.1_deb087b67ba2bf88_.log 2025-08-26T19:56:35.8563346Z Running 6 items in this shard: test/inductor/test_benchmark_fusion.py::BenchmarkFusionCpuTest::test_avoid_register_spilling_cpu, test/inductor/test_benchmark_fusion.py::BenchmarkFusionCpuTest::test_foreach_kernel_cpu, test/inductor/test_benchmark_fusion.py::BenchmarkFusionCpuTest::test_register_spills_cpu, test/inductor/test_benchmark_fusion.py::BenchmarkFusionCpuTest::test_resnet18_cpu, test/inductor/test_benchmark_fusion.py::BenchmarkFusionCpuTest::test_softmax_cpu, test/inductor/test_benchmark_fusion.py::BenchmarkFusionCpuTest::test_tield_kernel_fusion_cpu 2025-08-26T19:56:35.8567818Z 2025-08-26T19:56:35.8568111Z Running inductor/test_cutlass_backend 1/1 ... [2025-08-26 19:56:35.855979] 2025-08-26T19:56:35.8568601Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:56:35.8570034Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cutlass_backend.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:56:35.856406] 2025-08-26T19:56:42.3578059Z 2025-08-26T19:56:42.3579099Z inductor/test_cutlass_backend 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cutlass_backend_1.1_ced2ddf0660de863_.log 2025-08-26T19:56:42.3580169Z 2025-08-26T19:56:42.3583149Z Running inductor/test_distributed_patterns 1/1 ... [2025-08-26 19:56:42.358114] 2025-08-26T19:56:42.3583667Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:56:42.3587448Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_distributed_patterns.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:56:42.358538] 2025-08-26T19:57:06.8555459Z 2025-08-26T19:57:06.8556521Z inductor/test_distributed_patterns 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_distributed_patterns_1.1_f55df52c89a16650_.log 2025-08-26T19:57:06.8567310Z Running 20 items in this shard: test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_fake_distributed_aot_eager, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_fake_distributed_inductor, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_intermediate_hook_with_closure, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_intermediate_hook_with_nested_closure, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_aot, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_eager, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_inductor, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_module_backward_hooks_multi_layers, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return1, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return2, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return3, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_nn_param_return4, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_nonzero_cpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_nonzero_gpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_zero_cpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_storage_resize_zero_gpu, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_preserve_version_counter1, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_preserve_version_counter2, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_set_version_counter1, test/inductor/test_distributed_patterns.py::DistributedPatternTests::test_unsafe_set_version_counter2 2025-08-26T19:57:06.8577025Z 2025-08-26T19:57:06.8577283Z Running dynamo/test_fake_distributed 1/1 ... [2025-08-26 19:57:06.855880] 2025-08-26T19:57:06.8577754Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:57:06.8578890Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_fake_distributed.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:57:06.856255] 2025-08-26T19:57:15.8821331Z 2025-08-26T19:57:15.8822396Z dynamo/test_fake_distributed 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_fake_distributed_1.1_35aebba99a290f05_.log 2025-08-26T19:57:15.8824033Z Running 2 items in this shard: test/dynamo/test_fake_distributed.py::TestFakeDistributed::test_all_to_all_single_autograd, test/dynamo/test_fake_distributed.py::TestFakeDistributed::test_device_mesh_get_local_rank 2025-08-26T19:57:15.8825113Z 2025-08-26T19:57:15.8825390Z Running test_utils 1/1 ... [2025-08-26 19:57:15.882399] 2025-08-26T19:57:15.8825792Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T19:57:15.8829269Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 19:57:15.882738] 2025-08-26T20:00:31.4490082Z 2025-08-26T20:00:31.4492452Z test_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_1.1_ace957bb24590943_.log 2025-08-26T20:00:31.6694266Z Running 6049 items in this shard: test/test_utils.py::TestCheckpoint::test_checkpoint, test/test_utils.py::TestCheckpoint::test_checkpoint_module_list, test/test_utils.py::TestCheckpoint::test_checkpoint_no_tensors, test/test_utils.py::TestCheckpoint::test_checkpoint_non_tensor, test/test_utils.py::TestCheckpoint::test_checkpoint_non_tensor_inputs_outputs, test/test_utils.py::TestCheckpoint::test_checkpoint_not_preserve_rng_state_and_without_reentrant, test/test_utils.py::TestCheckpoint::test_checkpoint_partial_grad, test/test_utils.py::TestCheckpoint::test_checkpoint_rng_cpu, test/test_utils.py::TestCheckpoint::test_checkpoint_rng_cuda, test/test_utils.py::TestCheckpoint::test_checkpoint_sequential_deprecated_multiple_args, test/test_utils.py::TestCheckpoint::test_checkpoint_sequential_deprecated_no_args, test/test_utils.py::TestCheckpoint::test_checkpoint_trigger, test/test_utils.py::TestCheckpoint::test_checkpoint_valid, test/test_utils.py::TestCheckpoint::test_checkpointing_without_reentrant_early_free, test/test_utils.py::TestCheckpoint::test_get_device_states_recursive, test/test_utils.py::TestCheckpoint::test_infer_device_state_recursive_meta, test/test_utils.py::TestCheckpoint::test_infer_device_state_recursive_multi_cuda, test/test_utils.py::TestDataLoaderUtils::test_multi_drop, test/test_utils.py::TestDataLoaderUtils::test_multi_keep, test/test_utils.py::TestDataLoaderUtils::test_random_seed, test/test_utils.py::TestDataLoaderUtils::test_single_drop, test/test_utils.py::TestDataLoaderUtils::test_single_keep, test/test_utils.py::TestBottleneck::test_bottleneck_cpu_only, test/test_utils.py::TestBottleneck::test_bottleneck_cuda, test/test_utils.py::TestCollectEnv::test_smoke, test/test_utils.py::TestONNXUtils::test_check_onnx_broadcast, test/test_utils.py::TestONNXUtils::test_prepare_onnx_paddings, test/test_utils.py::TestHipify::test_import_hipify, test/test_utils.py::TestHipifyTrie::test_add_and_search_trie, test/test_utils.py::TestHipifyTrie::test_add_multiple_and_search_trie, test/test_utils.py::TestHipifyTrie::test_char_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_prefix_words_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_quote_escape, test/test_utils.py::TestHipifyTrie::test_single_export_trie_to_regex, test/test_utils.py::TestHipifyTrie::test_special_char_export_trie_to_regex, test/test_utils.py::TestAssert::test_assert_scriptable, test/test_utils.py::TestAssert::test_assert_true, test/test_utils.py::TestStandaloneCPPJIT::test_load_standalone, test/test_utils.py::TestRenderUtils::test_basic, test/test_utils.py::TestDeviceUtilsCPU::test_basic_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_decorator_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_decorator_generator_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_H_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_T_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___getitem___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___radd___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rand___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rdiv___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmatmul___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmod___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rmul___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___ror___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rpow___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rsub___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops___rxor___cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__batch_norm_with_update_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__chunk_cat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__native_batch_norm_legit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_lengths_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__segment_reduce_offsets_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__softmax_backward_data_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__unsafe_masked_index_put_accumulate_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__upsample_bilinear2d_aa_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__upsample_bilinear2d_aa_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops__upsample_bilinear2d_aa_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_abs_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acos_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_acosh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addbmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcdiv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addcmul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmm_decomposed_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addmv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_addr_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_alias_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_all_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_allclose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_aminmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_angle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_any_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_arange_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argmin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argsort_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_argwhere_cpu_float64, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_as_strided_cpu_complex32, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_left_shift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bitwise_not_cpu_uint8, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bmm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bool_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_shapes_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_broadcast_to_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_bucketize_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_byte_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cartesian_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cauchy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cdouble_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ceil_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cfloat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chalf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_char_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_inverse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cholesky_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_chunk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_max_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clamp_min_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_clone_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_column_stack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_combinations_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_complex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_conj_physical_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_constant_pad_nd_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_contiguous_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_copysign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_corrcoef_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cos_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cosh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_count_nonzero_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cov_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cross_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cummin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumprod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_cumulative_trapezoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_deg2rad_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diag_embed_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagflat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diagonal_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_diff_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_digamma_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_floor_rounding_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_no_rounding_mode_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_div_trunc_rounding_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_double_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_dstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_einsum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_permuted_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_empty_strided_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eq_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_equal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_erfinv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expand_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_expm1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_exponential_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e4m3fn, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e4m3fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e5m2, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_float8_e5m2fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_eye_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_fftshift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_hfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ifftshift_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_ihfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_irfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfft_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fft_rfftn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flatten_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flip_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fliplr_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_flipud_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_float_power_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_floor_divide_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_fmod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frac_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_frexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_full_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gather_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gcd_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ge_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geometric_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_geqrf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gradient_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_grid_sampler_3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_gt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_half_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hash_tensor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_heaviside_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogram_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogram_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogramdd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_histogramdd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_hypot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_i0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_igammac_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_imag_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_fill_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_put_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_mean_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_reduce_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_index_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_inner_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_int_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isclose_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isfinite_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isinf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isnan_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isneginf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isposinf_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_isreal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_istft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_istft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_item_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_2inputs_2outputs_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_4inputs_with_extra_args_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_binary_return_by_ref_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_jiterator_unary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kron_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_kthvalue_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lcm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ldexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_le_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lerp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lgamma_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cholesky_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cond_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_cross_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_det_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_diagonal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eig_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvals_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_eigvalsh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_householder_product_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_inv_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_factor_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_ldl_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lstsq_grad_oriented_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_factor_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_lu_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_power_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_matrix_rank_hermitian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_multi_dot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_norm_subgradients_at_zero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_hermitian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_pinv_singular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_qr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_slogdet_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_ex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_solve_triangular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_svdvals_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorinv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_tensorsolve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vander_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vecdot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linalg_vector_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_linspace_tensor_overload_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log10_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log1p_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_normal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_log_softmax_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logaddexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logcumsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logdet_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_and_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_not_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_or_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logical_xor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logspace_tensor_overload_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_logsumexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_long_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_lu_unpack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mH_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mT_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_amax_cpu_uint8, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logaddexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_logsumexp_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_mean_cpu_float64, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_normalize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_prod_cpu_int16, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_select_cpu_float32, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_masked_var_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matmul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_matrix_exp_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_pool2d_with_indices_backward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_no_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_max_reduction_with_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_maximum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_median_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_list_of_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_meshgrid_variadic_tensors_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_binary_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_no_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_min_reduction_with_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_minimum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mm_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mode_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_movedim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_msort_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mul_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_multinomial_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mv_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_3_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_mvlgamma_mvlgamma_p_5_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nan_to_num_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanmedian_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanquantile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nanquantile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nansum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_narrow_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_batch_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_dropout_backward_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_native_layer_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ne_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_neg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_empty_strided_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_full_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_ones_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_new_zeros_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nextafter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_avg_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_adaptive_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_alpha_dropout_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_avg_pool3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_batch_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_binary_cross_entropy_with_logits_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_celu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_channel_shuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose1d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_conv_transpose3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_embedding_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cosine_similarity_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_cross_entropy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_ctc_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_ctc_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_dropout_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_elu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_bag_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_embedding_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_feature_alpha_dropout_without_train_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_fractional_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gaussian_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_gelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_glu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_grid_sample_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_group_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardsigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardswish_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hardtanh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_hinge_embedding_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_huber_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_instance_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_area_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bicubic_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_linear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest-exact_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_nearest_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_interpolate_trilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_kl_div_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_l1_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_layer_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_leaky_relu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_linear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_local_response_norm_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_logsigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_margin_ranking_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool2d_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_pool3d_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool1d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool2d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_max_unpool3d_grad_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mish_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_mse_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_head_attention_forward_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multi_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_multilabel_soft_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_normalize_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_one_hot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_circular_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_constant_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_reflect_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pad_replicate_negative_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pairwise_distance_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pdist_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pdist_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_shuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_pixel_unshuffle_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_poisson_nll_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_prelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu6_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_relu_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rms_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_rrelu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_scaled_dot_product_attention_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_selu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_complex_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_complex_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_silu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_smooth_l1_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_soft_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softmin_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softplus_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_softsign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_tanhshrink_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_threshold_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_triplet_margin_with_distance_loss_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_unfold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_bilinear_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nn_functional_upsample_nearest_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_nonzero_static_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_fro_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_inf_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_norm_nuc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_in_place_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_normal_number_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ones_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ormqr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_outer_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pca_lowrank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_permute_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pinverse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polar_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polar_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_2_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_3_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_polygamma_polygamma_n_4_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_positive_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_pow_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_put_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_qr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_quantile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_quantile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rad2deg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rand_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randint_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_randn_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_ravel_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_real_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reciprocal_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_remainder_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_renorm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_repeat_interleave_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_reshape_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resize_as__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_conj_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_resolve_neg_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_roll_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rot90_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_round_decimals_neg_3_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsqrt_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_rsub_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scalar_tensor_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_add_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amax_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_amin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_mean_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_prod_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_scatter_reduce_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_searchsorted_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_select_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sgn_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_short_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sigmoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sign_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_bartlett_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_bartlett_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_blackman_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_blackman_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_cosine_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_cosine_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_exponential_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_exponential_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_gaussian_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_gaussian_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_cosine_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_cosine_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_hamming_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_general_hamming_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hamming_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hamming_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hann_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_hann_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_kaiser_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_kaiser_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_nuttall_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signal_windows_nuttall_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_signbit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sin_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sinh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_slice_scatter_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_softmax_with_dtype_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sort_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_mm_reduce_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sparse_sampled_addmm_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_airy_ai_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_j1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y0_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_bessel_y1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_t_cpu_int16, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_u_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_v_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_chebyshev_polynomial_w_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_entr_cpu_uint8, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_h_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_hermite_polynomial_he_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i0e_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_i1e_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_laguerre_polynomial_l_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_legendre_polynomial_p_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_log_ndtr_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_special_log_ndtr_cpu_float32, 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test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_squeeze_multiple_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_mean_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_std_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_stft_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sub_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_sum_to_size_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_svd_lowrank_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_t_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_along_dim_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_take_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tan_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tanh_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensor_split_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tensordot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tile_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_to_sparse_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_topk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e4m3fn, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e4m3fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e5m2, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch__scaled_mm_cpu_float8_e5m2fnuz, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_torch_ops_aten__safe_softmax_default_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trace_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_transpose_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapezoid_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trapz_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triangular_solve_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_indices_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_tril_indices_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_indices_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_triu_indices_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_true_divide_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_trunc_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unbind_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unflatten_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unfold_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_uniform_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_consecutive_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unique_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unravel_index_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_chunk_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsafe_split_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_unsqueeze_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_mean_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_var_unbiased_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vdot_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_complex_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_real_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_as_real_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_copy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_view_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vsplit_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_vstack_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_where_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_xlogy_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zero__cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_bfloat16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_bool, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex128, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_complex64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_float64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int16, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int32, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int64, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_int8, test/test_utils.py::TestDeviceUtilsCPU::test_device_mode_ops_zeros_like_cpu_uint8, test/test_utils.py::TestDeviceUtilsCPU::test_get_default_device_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_get_default_device_more_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_nn_module_cpu, test/test_utils.py::TestDeviceUtilsCPU::test_set_default_device_cpu, test/test_utils.py::TestCppExtensionUtils::test_cc_compiler_is_ok, test/test_utils.py::TestCppExtensionUtils::test_cpp_compiler_is_ok, test/test_utils.py::TestTraceback::test_basic, test/test_utils.py::TestTraceback::test_captured_traceback, test/test_utils.py::TestTraceback::test_captured_traceback_format_all, test/test_utils.py::TestTraceback::test_captured_traceback_format_all_cached, test/test_utils.py::TestTraceback::test_format_traceback_short, test/test_utils.py::TestTryImport::test_import_existing, test/test_utils.py::TestTryImport::test_import_imported, test/test_utils.py::TestTryImport::test_import_missing, test/test_utils.py::TestDeprecate::test_deprecated 2025-08-26T20:00:31.9330719Z 2025-08-26T20:00:31.9330919Z Running test_fx 1/1 ... [2025-08-26 20:00:31.456470] 2025-08-26T20:00:31.9331307Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:00:31.9332377Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:00:31.456787] 2025-08-26T20:04:23.9474635Z 2025-08-26T20:04:23.9475755Z test_fx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_1.1_fb4ae9aedb0b109c_.log 2025-08-26T20:04:23.9982842Z Running 1261 items in this shard: test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationInput_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationMetadata_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_MutationTorchTensorCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_Mutation_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_ReturnList_cpu, test/test_fx.py::TestCommonPass::test_correctness_CSEPass_TakeList_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_FactoryFunctionCall_cpu, test/test_fx.py::TestCommonPass::test_correctness_factory_CSEPass_MutationFactory_cpu, test/test_fx.py::TestCSEPass::test_banned_list, test/test_fx.py::TestCSEPass::test_empty, test/test_fx.py::TestCSEPass::test_immutable_list_multiple_entries, test/test_fx.py::TestCSEPass::test_immutable_list_type, test/test_fx.py::TestCSEPass::test_kwarg, test/test_fx.py::TestCSEPass::test_nested_immutable_list_type, test/test_fx.py::TestCSEPass::test_nochange, test/test_fx.py::TestCSEPass::test_rand_like, test/test_fx.py::TestCSEPass::test_rand_n, test/test_fx.py::TestCSEPass::test_random, test/test_fx.py::TestCSEPass::test_simple, test/test_fx.py::TestCSEPass::test_simple_2, test/test_fx.py::TestCSEPass::test_simple_multiple_same_ops, test/test_fx.py::TestCSEPass::test_two_args, test/test_fx.py::TestCSEPass::test_two_args_default, test/test_fx.py::TestDCE::test_dead_chain, test/test_fx.py::TestDCE::test_dead_getattr, test/test_fx.py::TestDCE::test_dead_placeholder, test/test_fx.py::TestDCE::test_dead_placeholder_with_user, test/test_fx.py::TestDCE::test_impure_custom, test/test_fx.py::TestDCE::test_impure_kwargs, test/test_fx.py::TestDCE::test_impure_nodes_args, test/test_fx.py::TestDCE::test_impure_random, test/test_fx.py::TestDCE::test_keep_collectives, test/test_fx.py::TestDCE::test_keep_collectives_no_overload, test/test_fx.py::TestDCE::test_keep_module_with_side_effects, test/test_fx.py::TestDCE::test_keep_setitem, test/test_fx.py::TestDCE::test_keep_torch_assert, test/test_fx.py::TestDCE::test_simple, test/test_fx.py::TestConstFold::test_check_inline_non_const, test/test_fx.py::TestConstFold::test_check_inline_non_const_mult_return, test/test_fx.py::TestConstFold::test_check_skip_folding_quant_dequant_pattern, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_one_attr_no_name_collision, test/test_fx.py::TestConstFold::test_const_fold_basic_placeholder_reordered, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr, test/test_fx.py::TestConstFold::test_const_fold_basic_two_attr_three_input, test/test_fx.py::TestConstFold::test_const_fold_has_inlined_call_module_node, test/test_fx.py::TestConstFold::test_const_fold_module_attr, test/test_fx.py::TestConstFold::test_const_fold_multi_const_folded_attrs, test/test_fx.py::TestConstFold::test_const_fold_noop, test/test_fx.py::TestConstFold::test_const_fold_submod_hierarchy, test/test_fx.py::TestConstFold::test_const_fold_tensor_meta, test/test_fx.py::TestConstFold::test_const_fold_unused_placeholder, test/test_fx.py::TestConstFold::test_dict_output, test/test_fx.py::TestConstFold::test_fold_module, test/test_fx.py::TestConstFold::test_retain_node_meta, test/test_fx.py::TestConstFold::test_three_outputs, test/test_fx.py::TestConstFold::test_two_outputs, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_dim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_ndim_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_nelement_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_numel_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_shape_const, test/test_fx.py::TestConstParamShapeInControlFlow::test_param_size_const, test/test_fx.py::AnnotationsTest::test_annotate, test/test_fx.py::AnnotationsTest::test_annotations, test/test_fx.py::AnnotationsTest::test_broadcasting1, test/test_fx.py::AnnotationsTest::test_broadcasting2, test/test_fx.py::AnnotationsTest::test_broadcasting3, test/test_fx.py::AnnotationsTest::test_consistency, test/test_fx.py::AnnotationsTest::test_precision, test/test_fx.py::TypeCheckerTest::test_flatten_fully_static, test/test_fx.py::TypeCheckerTest::test_resnet50, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_symbolic_add_with_broadcast_2, test/test_fx.py::TypeCheckerTest::test_type_check_add_false, test/test_fx.py::TypeCheckerTest::test_type_check_add_true, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_add_with_scalar, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_broadcast, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_2D_false, test/test_fx.py::TypeCheckerTest::test_type_check_batch_norm_symbolic, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_2_fully_static, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_conv2D_types, test/test_fx.py::TypeCheckerTest::test_type_check_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_flatten3, test/test_fx.py::TypeCheckerTest::test_type_check_flatten_2, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_dyn_true_param_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_false, test/test_fx.py::TypeCheckerTest::test_type_check_reshape_true, test/test_fx.py::TypeCheckerTest::test_type_check_symbolic_inferenceconv2D_maxpool2d_flatten, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_False, test/test_fx.py::TypeCheckerTest::test_type_check_transpose_true, test/test_fx.py::TypeCheckerTest::test_type_maxpool2d_fully_static, test/test_fx.py::TypeCheckerTest::test_type_typechecl_maxpool2d_3dinput, test/test_fx.py::TypeCheckerTest::test_typecheck_basicblock, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_function, test/test_fx.py::TestMatcher::test_matcher_with_name_node_map_module, test/test_fx.py::TestMatcher::test_split_to_graph_and_name_node_map, test/test_fx.py::TestMatcher::test_subgraph_matcher_ignore_literals, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_attributes, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list, test/test_fx.py::TestMatcher::test_subgraph_matcher_with_list_bad, test/test_fx.py::TestMatcher::test_variatic_arg_matching, test/test_fx.py::TestPassManager::test_pass_manager, test/test_fx.py::TestPassManager::test_pass_manager_bad_checks, test/test_fx.py::TestPassManager::test_pass_manager_checks, test/test_fx.py::TestPassManager::test_pass_manager_error, test/test_fx.py::TestPassManager::test_this_before_that_pass_constraint, test/test_fx.py::TestPassManager::test_topological_sort, test/test_fx.py::TestSourceMatcher::test_legalize_slice, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_conv_relu_maxpool_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_conv_relu_conv_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_functional_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_linear_relu_linear_torch_fn_export_strict_True, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_False, test/test_fx.py::TestSourceMatcher::test_module_partitioner_weight_tied_strict_True, test/test_fx.py::TestSubgraphRewriter::test_matching_pattern_with_list_type_arg, test/test_fx.py::TestSubgraphRewriter::test_matching_variable_arguments, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_callback, test/test_fx.py::TestSubgraphRewriter::test_replace_pattern_with_filters, test/test_fx.py::TestSubgraphRewriter::test_replaced_nodes, test/test_fx.py::TestSubgraphRewriter::test_replacement_with_attrs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_annotations_int, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_call_method, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_correct_output_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_internal_pattern_nodes_cannot_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_local_revert, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_multiple_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_nodes_with_kwargs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_output_pattern_node_can_have_users_that_are_not_matched, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_consecutive_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_duplicated_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replace_with_multiple_outputs, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_replaces_referenced_submodules, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_single_pattern_match, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_traced_as_callable, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_oneliner_pattern, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_overlapping_matches, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_trivial_replacement, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_args, test/test_fx.py::TestSubgraphRewriter::test_subgraph_rewriter_with_unused_results, test/test_fx.py::TestFX::test_all_input_nodes, test/test_fx.py::TestFX::test_annotation_with_future, test/test_fx.py::TestFX::test_annotations_empty_tuple, test/test_fx.py::TestFX::test_annotations_with_forward_references, test/test_fx.py::TestFX::test_annotations_with_no_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_internal_forward_references, test/test_fx.py::TestFX::test_annotations_with_non_torch_reference_and_no_internal_forward_references, test/test_fx.py::TestFX::test_args_kwargs, test/test_fx.py::TestFX::test_args_kwargs_no_self, test/test_fx.py::TestFX::test_assert, test/test_fx.py::TestFX::test_ast_rewriter_reassigns_submodules, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert, test/test_fx.py::TestFX::test_ast_rewriter_rewrites_assert_with_message, test/test_fx.py::TestFX::test_ast_rewriter_wrap, test/test_fx.py::TestFX::test_ast_rewriter_wrap_fn_directly, test/test_fx.py::TestFX::test_ast_rewriter_wrap_with_submodule, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator, test/test_fx.py::TestFX::test_ast_rewriter_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_autowrap_functions, test/test_fx.py::TestFX::test_concrete_arg_none_assert, test/test_fx.py::TestFX::test_construct_root_dict, test/test_fx.py::TestFX::test_control_flow_tracing, test/test_fx.py::TestFX::test_copy_it, test/test_fx.py::TestFX::test_copy_no_remap, test/test_fx.py::TestFX::test_ctx_mgr, test/test_fx.py::TestFX::test_custom_codegen, test/test_fx.py::TestFX::test_custom_codegen_with_transformer, test/test_fx.py::TestFX::test_custom_import, test/test_fx.py::TestFX::test_custom_proxy_dynamic_value, test/test_fx.py::TestFX::test_custom_proxy_input_dependent_control_flow, test/test_fx.py::TestFX::test_custom_proxy_type, test/test_fx.py::TestFX::test_custom_proxy_type_literal, test/test_fx.py::TestFX::test_custom_traceback_not_raised_when_exception_source_is_submodule, test/test_fx.py::TestFX::test_custom_traceback_raised_when_exception_source_is_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graph_with_tracer_cls, test/test_fx.py::TestFX::test_deepcopy_graphmodule, test/test_fx.py::TestFX::test_deepcopy_graphmodule_with_transform, test/test_fx.py::TestFX::test_deepcopy_no_recursion, test/test_fx.py::TestFX::test_deepcopy_recursion_depth, test/test_fx.py::TestFX::test_deepcopy_tracer, test/test_fx.py::TestFX::test_deepcopy_with_submods_params, test/test_fx.py::TestFX::test_delete_unused_submodules_leaf, test/test_fx.py::TestFX::test_delete_unused_values, test/test_fx.py::TestFX::test_dict, test/test_fx.py::TestFX::test_direct_param_use, test/test_fx.py::TestFX::test_disallow_override, test/test_fx.py::TestFX::test_ellipsis, test/test_fx.py::TestFX::test_empty_graph_codegen, test/test_fx.py::TestFX::test_enum, test/test_fx.py::TestFX::test_erase_node_error, test/test_fx.py::TestFX::test_example_shape_prop, test/test_fx.py::TestFX::test_find_uses, test/test_fx.py::TestFX::test_fn_type_annotation_empty, test/test_fx.py::TestFX::test_fn_type_annotations, test/test_fx.py::TestFX::test_fx_and_or, test/test_fx.py::TestFX::test_fx_create_arg, test/test_fx.py::TestFX::test_fx_shifts, test/test_fx.py::TestFX::test_fx_stateless, test/test_fx.py::TestFX::test_get_torch_func_signature, test/test_fx.py::TestFX::test_getitem, test/test_fx.py::TestFX::test_getitem_subproc, test/test_fx.py::TestFX::test_graph_edit_with_proxy, test/test_fx.py::TestFX::test_graph_fns, test/test_fx.py::TestFX::test_graph_module, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_dict_init, test/test_fx.py::TestFX::test_graph_module_init_buffer_param_copied_mod_init, test/test_fx.py::TestFX::test_graph_module_replicate_for_dp, test/test_fx.py::TestFX::test_graph_unique_names, test/test_fx.py::TestFX::test_graph_unique_names_manual, test/test_fx.py::TestFX::test_immutable_dict_pytree_ops, test/test_fx.py::TestFX::test_immutable_list_pytree_ops, test/test_fx.py::TestFX::test_imul_code_print, test/test_fx.py::TestFX::test_inf_nan, test/test_fx.py::TestFX::test_inf_nan_kwds, test/test_fx.py::TestFX::test_informative_co_filename, test/test_fx.py::TestFX::test_inline_graph, test/test_fx.py::TestFX::test_insert_arg, test/test_fx.py::TestFX::test_insertion_point, test/test_fx.py::TestFX::test_interpreter, test/test_fx.py::TestFX::test_interpreter_default_args, test/test_fx.py::TestFX::test_interpreter_gc_values, test/test_fx.py::TestFX::test_interpreter_noop_resnet18, test/test_fx.py::TestFX::test_interpreter_not_enough_args, test/test_fx.py::TestFX::test_interpreter_onthefly_swap, test/test_fx.py::TestFX::test_interpreter_other_graph, test/test_fx.py::TestFX::test_interpreter_partial_eval, test/test_fx.py::TestFX::test_interpreter_run_node_override, test/test_fx.py::TestFX::test_interpreter_star_args, test/test_fx.py::TestFX::test_interpreter_with_codegen, test/test_fx.py::TestFX::test_layout, test/test_fx.py::TestFX::test_leaf_module, test/test_fx.py::TestFX::test_lineno_map, test/test_fx.py::TestFX::test_matmul_tracing, test/test_fx.py::TestFX::test_metadata_on_ph, test/test_fx.py::TestFX::test_module_deepcopy_edit_nodes, test/test_fx.py::TestFX::test_move_before, test/test_fx.py::TestFX::test_multi_insert_point, test/test_fx.py::TestFX::test_multiple_default_args, test/test_fx.py::TestFX::test_named_tuple_inlined, test/test_fx.py::TestFX::test_namedtuple_return_qualname, test/test_fx.py::TestFX::test_namedtuple_return_trace, test/test_fx.py::TestFX::test_native_callable, test/test_fx.py::TestFX::test_nn_module_stack, test/test_fx.py::TestFX::test_no_mutation, test/test_fx.py::TestFX::test_node_tagging, test/test_fx.py::TestFX::test_nonetype_annotation, test/test_fx.py::TestFX::test_partial_trace, test/test_fx.py::TestFX::test_pickle_custom_import, test/test_fx.py::TestFX::test_pickle_graphmodule, test/test_fx.py::TestFX::test_pickle_nonetype_annotation, test/test_fx.py::TestFX::test_pickle_torch_custom_ops, test/test_fx.py::TestFX::test_prepend_self, test/test_fx.py::TestFX::test_pretty_print, test/test_fx.py::TestFX::test_pretty_print_graph, test/test_fx.py::TestFX::test_pretty_print_node, test/test_fx.py::TestFX::test_pretty_print_targets, test/test_fx.py::TestFX::test_print_graph, test/test_fx.py::TestFX::test_profiler_ranges_side_effect, test/test_fx.py::TestFX::test_proxy_deepcopy_with_tracer, test/test_fx.py::TestFX::test_proxy_deepcopy_without_tracer, test/test_fx.py::TestFX::test_pytree, test/test_fx.py::TestFX::test_pytree_concrete, test/test_fx.py::TestFX::test_reassign_args_kwargs_uses, test/test_fx.py::TestFX::test_regular_and_default_args, test/test_fx.py::TestFX::test_remove_uses, test/test_fx.py::TestFX::test_remove_uses_with_custom_filter, test/test_fx.py::TestFX::test_replace_input, test/test_fx.py::TestFX::test_replace_uses, test/test_fx.py::TestFX::test_reserved_getattr, test/test_fx.py::TestFX::test_return_tuple, test/test_fx.py::TestFX::test_return_type_exists, test/test_fx.py::TestFX::test_return_type_exists_pre_pep585, test/test_fx.py::TestFX::test_script_method_trace, test/test_fx.py::TestFX::test_script_tensor_constant, test/test_fx.py::TestFX::test_sequential, test/test_fx.py::TestFX::test_shape_prop_aggregate, test/test_fx.py::TestFX::test_shape_prop_layout, test/test_fx.py::TestFX::test_shape_prop_layout_3d, test/test_fx.py::TestFX::test_shape_prop_unbacked_sym, test/test_fx.py::TestFX::test_single_default_arg, test/test_fx.py::TestFX::test_snake_case, test/test_fx.py::TestFX::test_sqrt, test/test_fx.py::TestFX::test_stack_traces, test/test_fx.py::TestFX::test_stack_traces_with_transformer, test/test_fx.py::TestFX::test_string_literal_return, test/test_fx.py::TestFX::test_submodule_manipulation_API, test/test_fx.py::TestFX::test_symbolic_trace_assert, test/test_fx.py::TestFX::test_symbolic_trace_sequential, test/test_fx.py::TestFX::test_tensor_attribute, test/test_fx.py::TestFX::test_tensor_attribute_coalseced, test/test_fx.py::TestFX::test_tensor_constant, test/test_fx.py::TestFX::test_throw_out_variant, test/test_fx.py::TestFX::test_torch_custom_ops, test/test_fx.py::TestFX::test_torch_fx_getattr, test/test_fx.py::TestFX::test_torch_fx_len, test/test_fx.py::TestFX::test_torch_op_overloads, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx, test/test_fx.py::TestFX::test_torchbind_class_attribute_in_fx_tensor_arg, test/test_fx.py::TestFX::test_trace_buffer_slice, test/test_fx.py::TestFX::test_trace_dict_int_keys, test/test_fx.py::TestFX::test_trace_dict_proxy_keys, test/test_fx.py::TestFX::test_trace_fn_constant, test/test_fx.py::TestFX::test_trace_function, test/test_fx.py::TestFX::test_trace_multiple_funcs, test/test_fx.py::TestFX::test_trace_return_dataclass, test/test_fx.py::TestFX::test_trace_return_dataclass_nested, test/test_fx.py::TestFX::test_trace_return_namedtuple, test/test_fx.py::TestFX::test_tracing_graphmodules_as_leaf_submodules, test/test_fx.py::TestFX::test_transformer_multi_outputs, test/test_fx.py::TestFX::test_transformer_noop, test/test_fx.py::TestFX::test_transformer_op_swap, test/test_fx.py::TestFX::test_transformer_preserves_nn_module_stack_for_get_attr, test/test_fx.py::TestFX::test_tuple_no_subscript, test/test_fx.py::TestFX::test_typename_print, test/test_fx.py::TestFX::test_typename_print_pre_pep585, test/test_fx.py::TestFX::test_unpack, test/test_fx.py::TestFX::test_unpack_dict_better_error, test/test_fx.py::TestFX::test_unpack_list_better_error, test/test_fx.py::TestFX::test_update_args_api, test/test_fx.py::TestFX::test_update_args_kwargs_yells_at_you, test/test_fx.py::TestFX::test_update_kwargs_api, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_function, test/test_fx.py::TestFX::test_user_friendly_call_provenance_with_module, test/test_fx.py::TestFX::test_varargs_concrete, test/test_fx.py::TestFX::test_wrap, test/test_fx.py::TestFX::test_wrap_decorated_function, test/test_fx.py::TestFX::test_wrap_fn_directly, test/test_fx.py::TestFX::test_wrap_with_submodule, test/test_fx.py::TestFX::test_wrapped_method, test/test_fx.py::TestFX::test_wrapped_retrace, test/test_fx.py::TestFX::test_wrapped_via_decorator, test/test_fx.py::TestFX::test_wrapped_via_decorator_and_transformed, test/test_fx.py::TestFX::test_wrong_target_type, test/test_fx.py::TestFX::test_wrong_topo, test/test_fx.py::TestFXAPIBackwardCompatibility::test_adding_side_effect_function, test/test_fx.py::TestFXAPIBackwardCompatibility::test_class_member_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_function_back_compat, test/test_fx.py::TestFXAPIBackwardCompatibility::test_preserve_unused_attr_after_unpickle, test/test_fx.py::TestFXAPIBackwardCompatibility::test_public_api_surface, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_adaptive_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_affine_grid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_avg_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_batch_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_binary_cross_entropy_with_logits, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_celu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_tbc, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_conv_transpose3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cosine_similarity, test/test_fx.py::TestFunctionalTracing::test_nn_functional_cross_entropy, test/test_fx.py::TestFunctionalTracing::test_nn_functional_ctc_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_dropout3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_elu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding, test/test_fx.py::TestFunctionalTracing::test_nn_functional_embedding_bag, test/test_fx.py::TestFunctionalTracing::test_nn_functional_feature_alpha_dropout, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_fractional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gaussian_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_glu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_grid_sample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_group_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_gumbel_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardswish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hardtanh_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_hinge_embedding_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_huber_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_instance_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_interpolate, test/test_fx.py::TestFunctionalTracing::test_nn_functional_kl_div, test/test_fx.py::TestFunctionalTracing::test_nn_functional_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_layer_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_leaky_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_linear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_local_response_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_log_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_logsigmoid, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_lp_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_margin_ranking_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool1d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool2d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_pool3d_with_indices, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool1d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool2d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_max_unpool3d, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mish, test/test_fx.py::TestFunctionalTracing::test_nn_functional_mse_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_head_attention_forward, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multi_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_multilabel_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_native_channel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_normalize, test/test_fx.py::TestFunctionalTracing::test_nn_functional_one_hot, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pad, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pairwise_distance, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pdist, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_shuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_pixel_unshuffle, test/test_fx.py::TestFunctionalTracing::test_nn_functional_poisson_nll_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_prelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu6, test/test_fx.py::TestFunctionalTracing::test_nn_functional_relu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rms_norm, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_rrelu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_scaled_dot_product_attention, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_selu_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_silu, test/test_fx.py::TestFunctionalTracing::test_nn_functional_smooth_l1_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_soft_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmax, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softmin, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softplus, test/test_fx.py::TestFunctionalTracing::test_nn_functional_softshrink, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_threshold_, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_triplet_margin_with_distance_loss, test/test_fx.py::TestFunctionalTracing::test_nn_functional_unfold, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_bilinear, test/test_fx.py::TestFunctionalTracing::test_nn_functional_upsample_nearest, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_H_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_T_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___getitem___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___radd___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rdiv___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmatmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmod___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rmul___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rpow___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive___rsub___cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__batch_norm_with_update_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__chunk_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__native_batch_norm_legit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_lengths_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__segment_reduce_offsets_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__softmax_backward_data_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__unsafe_masked_index_put_accumulate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive__upsample_bilinear2d_aa_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_abs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_acosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcdiv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addcmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmm_decomposed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addmv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_addr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_alias_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_all_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_allclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_aminmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_angle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_any_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_arange_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argsort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_argwhere_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_partial_views_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_as_strided_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_asinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_atleast_3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_baddbmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bernoulli_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bfloat16_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_block_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bool_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_shapes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_broadcast_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_bucketize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_byte_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cartesian_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cauchy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cdouble_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ceil_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cfloat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chalf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_char_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_inverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cholesky_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_max_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clamp_min_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_clone_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_column_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_combinations_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_conj_physical_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_constant_pad_nd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_contiguous_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_copysign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_corrcoef_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cos_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cosh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_count_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cov_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cummin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_cumulative_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_deg2rad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diag_embed_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagflat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diagonal_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_diff_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_digamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_floor_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_no_rounding_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_div_trunc_rounding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_double_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_dstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_einsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_permuted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_equal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_erfinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expand_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_expm1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_eye_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_fftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_hfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ifftshift_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_ihfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_irfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fft_rfftn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flip_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fliplr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_flipud_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_float_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_floor_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_fmod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_frexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_full_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gather_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ge_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geometric_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_geqrf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gradient_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_grid_sampler_2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_grid_sampler_3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_gt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_half_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hash_tensor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_heaviside_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogram_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_histogramdd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_hypot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_igammac_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_index_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_inner_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_int_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isclose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isfinite_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isnan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isneginf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isposinf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_isreal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_item_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_4inputs_with_extra_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_binary_return_by_ref_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_jiterator_unary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kron_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_kthvalue_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ldexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_le_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lerp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lgamma_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cholesky_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cond_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_cross_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_det_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_diagonal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eig_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_eigvalsh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_householder_product_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_inv_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_ldl_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lstsq_grad_oriented_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_factor_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_power_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_matrix_rank_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_multi_dot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_norm_subgradients_at_zero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_hermitian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_pinv_singular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_slogdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_ex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_solve_triangular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_svdvals_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorinv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_tensorsolve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vander_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vecdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linalg_vector_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_linspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log10_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log1p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_log_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logcumsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logdet_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_and_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_not_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_or_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logical_xor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logspace_tensor_overload_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_long_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_lu_unpack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mH_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mT_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_argmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumprod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_cumsum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_fill_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_log_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logaddexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_logsumexp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_masked_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matmul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_matrix_exp_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_pool2d_with_indices_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_max_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_maximum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_median_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_list_of_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_meshgrid_variadic_tensors_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_binary_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_no_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_min_reduction_with_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_minimum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mode_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_movedim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_msort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mul_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_multinomial_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mv_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nan_to_num_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanmedian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nanquantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nansum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_narrow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_dropout_backward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_native_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ne_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_empty_strided_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_full_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_new_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nextafter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_alpha_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_avg_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_batch_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_celu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_channel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_conv_transpose3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cosine_similarity_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_cross_entropy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_ctc_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_dropout_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_elu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_bag_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_embedding_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_fractional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gaussian_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_gelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_glu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_grid_sample_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_group_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardswish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hardtanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_hinge_embedding_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_huber_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_instance_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_area_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_interpolate_trilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_kl_div_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_layer_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_leaky_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_linear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_local_response_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_logsigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_margin_ranking_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_pool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool1d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool2d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_max_unpool3d_grad_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mish_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_mse_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_head_attention_forward_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multi_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_normalize_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_circular_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_constant_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_reflect_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pad_replicate_negative_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pairwise_distance_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pdist_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_shuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_pixel_unshuffle_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_poisson_nll_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_prelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu6_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_relu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rms_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_rrelu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_scaled_dot_product_attention_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_selu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_silu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_smooth_l1_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softplus_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_softsign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_tanhshrink_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_threshold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_bilinear_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nn_functional_upsample_nearest_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_nonzero_static_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_fro_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_inf_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_norm_nuc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_in_place_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_normal_number_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ones_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ormqr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_outer_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pca_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_permute_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pinverse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polar_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_2_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_polygamma_polygamma_n_4_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_positive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_pow_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_put_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_qr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_quantile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rad2deg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rand_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randint_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_randn_like_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_ravel_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_real_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reciprocal_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_remainder_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_renorm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_repeat_interleave_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_reshape_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resize_as__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_conj_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_resolve_neg_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_roll_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rot90_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_round_decimals_neg_3_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_rsub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scalar_tensor_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_add_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_amin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_prod_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_scatter_reduce_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_searchsorted_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_select_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sgn_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_short_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sigmoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sign_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_bartlett_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_blackman_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_exponential_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_gaussian_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_cosine_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_general_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hamming_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_hann_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_kaiser_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signal_windows_nuttall_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_signbit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sin_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sinh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_slice_scatter_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_softmax_with_dtype_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sort_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_mm_reduce_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sparse_sampled_addmm_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_airy_ai_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_j1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_bessel_y1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_entr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_erfcx_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_h_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_hermite_polynomial_he_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i0e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_i1e_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_laguerre_polynomial_l_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_legendre_polynomial_p_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_log_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_i1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtr_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_ndtri_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_scaled_modified_bessel_k1_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_u_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_spherical_bessel_j0_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_xlog1py_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_special_zeta_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_list_args_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_split_with_sizes_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sqrt_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_square_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_squeeze_multiple_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_std_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_stft_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sub_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_sum_to_size_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_svd_lowrank_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_t_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_along_dim_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_take_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tan_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tanh_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensor_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tensordot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tile_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_to_sparse_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_topk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trace_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_transpose_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapezoid_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trapz_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triangular_solve_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_tril_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_triu_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_true_divide_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_trunc_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unbind_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unflatten_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unfold_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_uniform_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_consecutive_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unique_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_chunk_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsafe_split_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_unsqueeze_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_mean_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_var_unbiased_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vdot_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_complex_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_as_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_copy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_view_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vsplit_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_vstack_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_where_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_xlogy_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zero__cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_cpu_float32, test/test_fx.py::TestOperatorSignaturesCPU::test_get_torch_func_signature_exhaustive_zeros_like_cpu_float32, test/test_fx.py::TestVisionTracing::test_torchvision_models_alexnet, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_base, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_convnext_tiny, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet121, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet161, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet169, test/test_fx.py::TestVisionTracing::test_torchvision_models_densenet201, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_320_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_mobilenet_v3_large_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fasterrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_fcos_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_keypointrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_maskrcnn_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_retinanet_resnet50_fpn_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssd300_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_detection_ssdlite320_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b0, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b1, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b2, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b3, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b4, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b5, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b6, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_b7, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_l, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_m, test/test_fx.py::TestVisionTracing::test_torchvision_models_efficientnet_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_googlenet, test/test_fx.py::TestVisionTracing::test_torchvision_models_inception_v3, test/test_fx.py::TestVisionTracing::test_torchvision_models_maxvit_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet0_75, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_mnasnet1_3, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v2, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_mobilenet_v3_small, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_x_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_128gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_16gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_1_6gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_32gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_3_2gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_400mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_800mf, test/test_fx.py::TestVisionTracing::test_torchvision_models_regnet_y_8gf, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet152, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet18, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet34, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_32x8d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext101_64x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_resnext50_32x4d, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_deeplabv3_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet101, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_fcn_resnet50, test/test_fx.py::TestVisionTracing::test_torchvision_models_segmentation_lraspp_mobilenet_v3_large, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x0_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x1_5, test/test_fx.py::TestVisionTracing::test_torchvision_models_shufflenet_v2_x2_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_0, test/test_fx.py::TestVisionTracing::test_torchvision_models_squeezenet1_1, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_swin_v2_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg11_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg13_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg16_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19, test/test_fx.py::TestVisionTracing::test_torchvision_models_vgg19_bn, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mc3_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v1_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_mvit_v2_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r2plus1d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_r3d_18, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_s3d, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_b, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_s, test/test_fx.py::TestVisionTracing::test_torchvision_models_video_swin3d_t, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_b_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_h_14, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_16, test/test_fx.py::TestVisionTracing::test_torchvision_models_vit_l_32, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet101_2, test/test_fx.py::TestVisionTracing::test_torchvision_models_wide_resnet50_2 2025-08-26T20:04:24.0465243Z 2025-08-26T20:04:24.0465519Z Running test_transformers_privateuse1 1/1 ... [2025-08-26 20:04:23.950041] 2025-08-26T20:04:25.4232658Z -- The CXX compiler identification is Clang 12.0.1 2025-08-26T20:04:25.5054661Z -- The C compiler identification is Clang 12.0.1 2025-08-26T20:04:25.5288941Z -- Detecting CXX compiler ABI info 2025-08-26T20:04:25.7327915Z -- Detecting CXX compiler ABI info - done 2025-08-26T20:04:25.7467371Z -- Check for working CXX compiler: /opt/cache/bin/c++ - skipped 2025-08-26T20:04:25.7476248Z -- Detecting CXX compile features 2025-08-26T20:04:25.7488050Z -- Detecting CXX compile features - done 2025-08-26T20:04:25.7680847Z -- Detecting C compiler ABI info 2025-08-26T20:04:25.8827902Z -- Detecting C compiler ABI info - done 2025-08-26T20:04:25.8958011Z -- Check for working C compiler: /opt/cache/bin/cc - skipped 2025-08-26T20:04:25.8962082Z -- Detecting C compile features 2025-08-26T20:04:25.8967819Z -- Detecting C compile features - done 2025-08-26T20:04:26.0237027Z CMake Warning at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message): 2025-08-26T20:04:26.0238787Z static library kineto_LIBRARY-NOTFOUND not found. 2025-08-26T20:04:26.0239520Z Call Stack (most recent call first): 2025-08-26T20:04:26.0240904Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found) 2025-08-26T20:04:26.0242334Z CMakeLists.txt:29 (find_package) 2025-08-26T20:04:26.0242754Z 2025-08-26T20:04:26.0243036Z  2025-08-26T20:04:26.0248224Z -- Found Torch: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so 2025-08-26T20:04:26.0308682Z -- Configuring done (0.8s) 2025-08-26T20:04:26.0449537Z -- Generating done (0.0s) 2025-08-26T20:04:26.0462675Z -- Build files have been written to: /var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/build 2025-08-26T20:04:26.1917148Z [ 5%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/device.cpp.o 2025-08-26T20:04:26.1918177Z [ 11%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/memory.cpp.o 2025-08-26T20:04:26.3044746Z [ 17%] Linking CXX shared library libopenreg.so 2025-08-26T20:04:26.3840464Z [ 17%] Built target openreg 2025-08-26T20:04:26.3930274Z [ 23%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegExtra.cpp.o 2025-08-26T20:04:26.3931955Z [ 29%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegMinimal.cpp.o 2025-08-26T20:04:26.3933093Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Extra.cpp.o 2025-08-26T20:04:26.3935227Z [ 41%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Minimal.cpp.o 2025-08-26T20:04:26.3938067Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegDeviceAllocator.cpp.o 2025-08-26T20:04:26.3941235Z [ 52%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegFunctions.cpp.o 2025-08-26T20:04:26.3943422Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGenerator.cpp.o 2025-08-26T20:04:26.3948472Z [ 64%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGuard.cpp.o 2025-08-26T20:04:26.3954217Z [ 70%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHooks.cpp.o 2025-08-26T20:04:26.3956370Z [ 76%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHostAllocator.cpp.o 2025-08-26T20:04:26.3959734Z [ 82%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegSerialization.cpp.o 2025-08-26T20:04:26.9309100Z [ 88%] Linking CXX shared library libtorch_openreg.so 2025-08-26T20:04:27.4033137Z [ 88%] Built target torch_openreg 2025-08-26T20:04:27.4118631Z [ 94%] Building CXX object torch_openreg/csrc/CMakeFiles/torch_bindings.dir/Module.cpp.o 2025-08-26T20:04:27.9863386Z [100%] Linking CXX shared library libtorch_bindings.so 2025-08-26T20:04:28.2699344Z [100%] Built target torch_bindings 2025-08-26T20:04:28.2764048Z Install the project... 2025-08-26T20:04:28.2788834Z -- Install configuration: "" 2025-08-26T20:04:28.3414565Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/config/_apply_pyprojecttoml.py:82: SetuptoolsDeprecationWarning: `project.license` as a TOML table is deprecated 2025-08-26T20:04:28.3415536Z !! 2025-08-26T20:04:28.3415680Z 2025-08-26T20:04:28.3415807Z ******************************************************************************** 2025-08-26T20:04:28.3416714Z Please use a simple string containing a SPDX expression for `project.license`. You can also use `project.license-files`. (Both options available on setuptools>=77.0.0). 2025-08-26T20:04:28.3417460Z 2025-08-26T20:04:28.3417713Z By 2026-Feb-18, you need to update your project and remove deprecated calls 2025-08-26T20:04:28.3418209Z or your builds will no longer be supported. 2025-08-26T20:04:28.3418476Z 2025-08-26T20:04:28.3418863Z See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. 2025-08-26T20:04:28.3419492Z ******************************************************************************** 2025-08-26T20:04:28.3419755Z 2025-08-26T20:04:28.3419841Z !! 2025-08-26T20:04:28.3420071Z corresp(dist, value, root_dir) 2025-08-26T20:04:28.3932165Z running install 2025-08-26T20:04:28.3946359Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:04:28.3947353Z !! 2025-08-26T20:04:28.3947485Z 2025-08-26T20:04:28.3947615Z ******************************************************************************** 2025-08-26T20:04:28.3948022Z Please avoid running ``setup.py`` directly. 2025-08-26T20:04:28.3948437Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:04:28.3948826Z standards-based tools. 2025-08-26T20:04:28.3949034Z 2025-08-26T20:04:28.3949326Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:04:28.3949828Z or your builds will no longer be supported. 2025-08-26T20:04:28.3950077Z 2025-08-26T20:04:28.3950394Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:04:28.3950978Z ******************************************************************************** 2025-08-26T20:04:28.3951240Z 2025-08-26T20:04:28.3951332Z !! 2025-08-26T20:04:28.3951562Z self.initialize_options() 2025-08-26T20:04:28.4076852Z running build 2025-08-26T20:04:28.4077116Z running build_py 2025-08-26T20:04:28.4154916Z creating build/lib.linux-x86_64-cpython-313/torch_openreg 2025-08-26T20:04:28.4156646Z copying torch_openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg 2025-08-26T20:04:28.4164692Z copying torch_openreg/_utils.py -> build/lib.linux-x86_64-cpython-313/torch_openreg 2025-08-26T20:04:28.4172784Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:28.4173763Z copying torch_openreg/openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:28.4181268Z copying torch_openreg/openreg/meta.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:28.4188388Z copying torch_openreg/openreg/random.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:28.4202154Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:28.4203199Z copying torch_openreg/lib/libopenreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:28.4217627Z copying torch_openreg/lib/libtorch_openreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:28.4317893Z copying torch_openreg/lib/libtorch_bindings.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:28.4356909Z running build_ext 2025-08-26T20:04:28.4467258Z building 'torch_openreg._C' extension 2025-08-26T20:04:28.4469002Z creating build/temp.linux-x86_64-cpython-313/torch_openreg/csrc 2025-08-26T20:04:28.4473003Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/include/python3.13 -c torch_openreg/csrc/stub.c -o build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -Wall -Wextra -Wno-strict-overflow -Wno-unused-parameter -Wno-missing-field-initializers -Wno-unknown-pragmas -fno-strict-aliasing 2025-08-26T20:04:28.5573964Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -L/var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/torch_openreg/lib -ltorch_bindings -o build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -Wl,-rpath,$ORIGIN/lib 2025-08-26T20:04:28.5817907Z running install_lib 2025-08-26T20:04:28.5897491Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages 2025-08-26T20:04:28.5900497Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-08-26T20:04:28.5901741Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-08-26T20:04:28.5903115Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_utils.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-08-26T20:04:28.5904632Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg 2025-08-26T20:04:28.5905952Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/openreg/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg 2025-08-26T20:04:28.5907469Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/openreg/meta.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg 2025-08-26T20:04:28.5909023Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/openreg/random.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg 2025-08-26T20:04:28.5910253Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-08-26T20:04:28.5911312Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libopenreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-08-26T20:04:28.5912870Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_openreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-08-26T20:04:28.5929237Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_bindings.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-08-26T20:04:28.5935327Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-08-26T20:04:28.5941864Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/__init__.py to __init__.cpython-313.pyc 2025-08-26T20:04:28.5945601Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/_utils.py to _utils.cpython-313.pyc 2025-08-26T20:04:28.5951431Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg/__init__.py to __init__.cpython-313.pyc 2025-08-26T20:04:28.5957121Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg/meta.py to meta.cpython-313.pyc 2025-08-26T20:04:28.5959759Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/openreg/random.py to random.cpython-313.pyc 2025-08-26T20:04:28.5964997Z running install_egg_info 2025-08-26T20:04:28.6117445Z running egg_info 2025-08-26T20:04:28.6191053Z creating torch_openreg.egg-info 2025-08-26T20:04:28.6192047Z writing torch_openreg.egg-info/PKG-INFO 2025-08-26T20:04:28.6196012Z writing dependency_links to torch_openreg.egg-info/dependency_links.txt 2025-08-26T20:04:28.6198003Z writing requirements to torch_openreg.egg-info/requires.txt 2025-08-26T20:04:28.6198887Z writing top-level names to torch_openreg.egg-info/top_level.txt 2025-08-26T20:04:28.6200010Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-08-26T20:04:28.6282788Z reading manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-08-26T20:04:28.6290758Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-08-26T20:04:28.6291995Z Copying torch_openreg.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info 2025-08-26T20:04:28.6298016Z running install_scripts 2025-08-26T20:04:28.9002486Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:04:28.9005687Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers_privateuse1.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:04:28.900349] 2025-08-26T20:04:32.0687835Z 2025-08-26T20:04:32.0689032Z test_transformers_privateuse1 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_privateuse1_1.1_4c150e3b0e01a84b_.log 2025-08-26T20:04:32.0691640Z Running 3 items in this shard: test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_fused_sdp_choice_privateuseone, test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_scaled_dot_product_fused_attention_overrideable, test/test_transformers_privateuse1.py::TestSDPAPrivateUse1Only::test_scaled_dot_product_fused_attention_overrideable_backward 2025-08-26T20:04:32.0693378Z 2025-08-26T20:04:32.0693602Z Running test_cpp_api_parity 1/1 ... [2025-08-26 20:04:32.069019] 2025-08-26T20:04:32.0694030Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:04:32.0695179Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_api_parity.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:04:32.069323] 2025-08-26T20:04:41.7967795Z 2025-08-26T20:04:41.7968676Z test_cpp_api_parity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_api_parity_1.1_fc25a545febb163f_.log 2025-08-26T20:04:41.8165927Z Running 488 items in this shard: test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_mean, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_mean_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_none, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_none_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_sum, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCELoss_no_batch_dim_sum_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_mean, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_mean_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_none, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_none_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_sum, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_BCEWithLogitsLoss_no_batch_dim_sum_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_circular_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_circular_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_dilated_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_groups, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_groups_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1size1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad1size1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2size1, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad2size1_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_same_dilated_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_valid, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_pad_valid_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_reflect_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_reflect_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_replicate_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_replicate_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_stride, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_stride_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zero_batch, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zero_batch_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zeros_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv1d_zeros_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_circular_stride2_pad2, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_circular_stride2_pad2_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_dilated_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_padded, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_padded_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_strided, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_strided_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_with_multiplier, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_depthwise_with_multiplier_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_dilated, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_dilated_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_Conv2d_groups, 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test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_nearest_tuple_2d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_nearest_tuple_2d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_nearest_tuple_3d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_nearest_tuple_3d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_3d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_3d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_3d_zero_dim, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_3d_zero_dim_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_scale_3d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_scale_3d_align_corners, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_scale_3d_align_corners_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_scale_3d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_tuple_3d, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_tuple_3d_align_corners, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_tuple_3d_align_corners_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_interpolate_trilinear_tuple_3d_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_dim0, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_dim0_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_dim3, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_dim3_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_lastdim, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_lastdim_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_scalar, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_scalar_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial_special, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_log_softmax_spatial_special_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_multimarginloss_1d_input_0d_target_no_reduce, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_multimarginloss_1d_input_0d_target_no_reduce_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_sample_functional_has_parity, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_sample_functional_has_parity_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_sample_functional_no_parity, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_sample_functional_no_parity_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_functional_dim0, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_functional_dim0_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_functional_dim3, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_functional_dim3_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_functional_scalar, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_functional_scalar_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_lastdim, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_lastdim_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_lastdim_dtype, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_lastdim_dtype_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_dtype, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_dtype_cuda, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_special, test/test_cpp_api_parity.py::TestCppApiParity::test_torch_nn_functional_softmax_spatial_special_cuda 2025-08-26T20:04:41.8359088Z 2025-08-26T20:04:41.8359301Z Running test_extension_utils 1/1 ... [2025-08-26 20:04:41.797690] 2025-08-26T20:04:41.8359747Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:04:41.8360844Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_extension_utils.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:04:41.797990] 2025-08-26T20:04:44.8661191Z 2025-08-26T20:04:44.8662094Z test_extension_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_extension_utils_1.1_f517db5628d9cb30_.log 2025-08-26T20:04:44.8663757Z Running 2 items in this shard: test/test_extension_utils.py::TestExtensionUtils::test_external_module_register, test/test_extension_utils.py::TestExtensionUtils::test_external_module_register_with_renamed_backend 2025-08-26T20:04:44.8664922Z 2025-08-26T20:04:44.8665109Z Running test_openreg 1/1 ... [2025-08-26 20:04:44.866314] 2025-08-26T20:04:46.2773791Z -- The CXX compiler identification is Clang 12.0.1 2025-08-26T20:04:46.3481854Z -- The C compiler identification is Clang 12.0.1 2025-08-26T20:04:46.3563713Z -- Detecting CXX compiler ABI info 2025-08-26T20:04:46.5141715Z -- Detecting CXX compiler ABI info - done 2025-08-26T20:04:46.5279135Z -- Check for working CXX compiler: /opt/cache/bin/c++ - skipped 2025-08-26T20:04:46.5282786Z -- Detecting CXX compile features 2025-08-26T20:04:46.5289947Z -- Detecting CXX compile features - done 2025-08-26T20:04:46.5401718Z -- Detecting C compiler ABI info 2025-08-26T20:04:46.6552982Z -- Detecting C compiler ABI info - done 2025-08-26T20:04:46.6681585Z -- Check for working C compiler: /opt/cache/bin/cc - skipped 2025-08-26T20:04:46.6685476Z -- Detecting C compile features 2025-08-26T20:04:46.6690777Z -- Detecting C compile features - done 2025-08-26T20:04:46.7758240Z CMake Warning at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:22 (message): 2025-08-26T20:04:46.7759070Z static library kineto_LIBRARY-NOTFOUND not found. 2025-08-26T20:04:46.7759466Z Call Stack (most recent call first): 2025-08-26T20:04:46.7760206Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/share/cmake/Torch/TorchConfig.cmake:125 (append_torchlib_if_found) 2025-08-26T20:04:46.7761126Z CMakeLists.txt:29 (find_package) 2025-08-26T20:04:46.7761344Z 2025-08-26T20:04:46.7761481Z  2025-08-26T20:04:46.7766556Z -- Found Torch: /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so 2025-08-26T20:04:46.7793003Z -- Configuring done (0.7s) 2025-08-26T20:04:46.7914702Z -- Generating done (0.0s) 2025-08-26T20:04:46.7927352Z -- Build files have been written to: /var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/build 2025-08-26T20:04:46.9382979Z [ 5%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/device.cpp.o 2025-08-26T20:04:46.9384010Z [ 11%] Building CXX object third_party/openreg/CMakeFiles/openreg.dir/csrc/memory.cpp.o 2025-08-26T20:04:47.0381502Z [ 17%] Linking CXX shared library libopenreg.so 2025-08-26T20:04:47.1156326Z [ 17%] Built target openreg 2025-08-26T20:04:47.1245418Z [ 23%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegExtra.cpp.o 2025-08-26T20:04:47.1247135Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/OpenRegMinimal.cpp.o 2025-08-26T20:04:47.1248654Z [ 35%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Extra.cpp.o 2025-08-26T20:04:47.1250649Z [ 41%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/aten/native/Minimal.cpp.o 2025-08-26T20:04:47.1252197Z [ 47%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegDeviceAllocator.cpp.o 2025-08-26T20:04:47.1257639Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegFunctions.cpp.o 2025-08-26T20:04:47.1259315Z [ 58%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGenerator.cpp.o 2025-08-26T20:04:47.1260789Z [ 64%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegGuard.cpp.o 2025-08-26T20:04:47.1268403Z [ 70%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHooks.cpp.o 2025-08-26T20:04:47.1269736Z [ 76%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegHostAllocator.cpp.o 2025-08-26T20:04:47.1270870Z [ 82%] Building CXX object csrc/CMakeFiles/torch_openreg.dir/runtime/OpenRegSerialization.cpp.o 2025-08-26T20:04:47.6934873Z [ 88%] Linking CXX shared library libtorch_openreg.so 2025-08-26T20:04:48.1846594Z [ 88%] Built target torch_openreg 2025-08-26T20:04:48.1933366Z [ 94%] Building CXX object torch_openreg/csrc/CMakeFiles/torch_bindings.dir/Module.cpp.o 2025-08-26T20:04:48.7504459Z [100%] Linking CXX shared library libtorch_bindings.so 2025-08-26T20:04:49.0289085Z [100%] Built target torch_bindings 2025-08-26T20:04:49.0353911Z Install the project... 2025-08-26T20:04:49.0379190Z -- Install configuration: "" 2025-08-26T20:04:49.0931967Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/config/_apply_pyprojecttoml.py:82: SetuptoolsDeprecationWarning: `project.license` as a TOML table is deprecated 2025-08-26T20:04:49.0932976Z !! 2025-08-26T20:04:49.0933092Z 2025-08-26T20:04:49.0933377Z ******************************************************************************** 2025-08-26T20:04:49.0934291Z Please use a simple string containing a SPDX expression for `project.license`. You can also use `project.license-files`. (Both options available on setuptools>=77.0.0). 2025-08-26T20:04:49.0935035Z 2025-08-26T20:04:49.0935346Z By 2026-Feb-18, you need to update your project and remove deprecated calls 2025-08-26T20:04:49.0935840Z or your builds will no longer be supported. 2025-08-26T20:04:49.0936114Z 2025-08-26T20:04:49.0936494Z See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. 2025-08-26T20:04:49.0937119Z ******************************************************************************** 2025-08-26T20:04:49.0937532Z 2025-08-26T20:04:49.0937691Z !! 2025-08-26T20:04:49.0937922Z corresp(dist, value, root_dir) 2025-08-26T20:04:49.1236429Z running install 2025-08-26T20:04:49.1239072Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:04:49.1240009Z !! 2025-08-26T20:04:49.1240154Z 2025-08-26T20:04:49.1240305Z ******************************************************************************** 2025-08-26T20:04:49.1240697Z Please avoid running ``setup.py`` directly. 2025-08-26T20:04:49.1241186Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:04:49.1241635Z standards-based tools. 2025-08-26T20:04:49.1241855Z 2025-08-26T20:04:49.1242088Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:04:49.1242659Z or your builds will no longer be supported. 2025-08-26T20:04:49.1242909Z 2025-08-26T20:04:49.1243295Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:04:49.1243835Z ******************************************************************************** 2025-08-26T20:04:49.1244171Z 2025-08-26T20:04:49.1244258Z !! 2025-08-26T20:04:49.1244485Z self.initialize_options() 2025-08-26T20:04:49.1367824Z running build 2025-08-26T20:04:49.1368481Z running build_py 2025-08-26T20:04:49.1446018Z creating build/lib.linux-x86_64-cpython-313/torch_openreg 2025-08-26T20:04:49.1447718Z copying torch_openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg 2025-08-26T20:04:49.1449608Z copying torch_openreg/_utils.py -> build/lib.linux-x86_64-cpython-313/torch_openreg 2025-08-26T20:04:49.1451779Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:49.1453103Z copying torch_openreg/openreg/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:49.1454247Z copying torch_openreg/openreg/meta.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:49.1455646Z copying torch_openreg/openreg/random.py -> build/lib.linux-x86_64-cpython-313/torch_openreg/openreg 2025-08-26T20:04:49.1463754Z creating build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:49.1464763Z copying torch_openreg/lib/libopenreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:49.1477823Z copying torch_openreg/lib/libtorch_openreg.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:49.1576878Z copying torch_openreg/lib/libtorch_bindings.so -> build/lib.linux-x86_64-cpython-313/torch_openreg/lib 2025-08-26T20:04:49.1617166Z running build_ext 2025-08-26T20:04:49.1705219Z building 'torch_openreg._C' extension 2025-08-26T20:04:49.1706863Z creating build/temp.linux-x86_64-cpython-313/torch_openreg/csrc 2025-08-26T20:04:49.1711361Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/include/python3.13 -c torch_openreg/csrc/stub.c -o build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -Wall -Wextra -Wno-strict-overflow -Wno-unused-parameter -Wno-missing-field-initializers -Wno-unknown-pragmas -fno-strict-aliasing 2025-08-26T20:04:49.2777854Z gcc -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/torch_openreg/csrc/stub.o -L/var/lib/jenkins/workspace/test/cpp_extensions/open_registration_extension/torch_openreg/torch_openreg/lib -ltorch_bindings -o build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -Wl,-rpath,$ORIGIN/lib 2025-08-26T20:04:49.2996609Z running install_lib 2025-08-26T20:04:49.3079183Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libopenreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-08-26T20:04:49.3081021Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_openreg.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-08-26T20:04:49.3099365Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/lib/libtorch_bindings.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg/lib 2025-08-26T20:04:49.3105972Z copying build/lib.linux-x86_64-cpython-313/torch_openreg/_C.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg 2025-08-26T20:04:49.3111536Z running install_egg_info 2025-08-26T20:04:49.3264811Z running egg_info 2025-08-26T20:04:49.3339137Z writing torch_openreg.egg-info/PKG-INFO 2025-08-26T20:04:49.3343304Z writing dependency_links to torch_openreg.egg-info/dependency_links.txt 2025-08-26T20:04:49.3375074Z writing requirements to torch_openreg.egg-info/requires.txt 2025-08-26T20:04:49.3384010Z writing top-level names to torch_openreg.egg-info/top_level.txt 2025-08-26T20:04:49.3474008Z reading manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-08-26T20:04:49.3483795Z writing manifest file 'torch_openreg.egg-info/SOURCES.txt' 2025-08-26T20:04:49.3494217Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info' (and everything under it) 2025-08-26T20:04:49.3495927Z Copying torch_openreg.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_openreg-0.0.1-py3.13.egg-info 2025-08-26T20:04:49.3501389Z running install_scripts 2025-08-26T20:04:49.6176955Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:04:49.6179978Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_openreg.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:04:49.617748] 2025-08-26T20:04:53.9875643Z 2025-08-26T20:04:53.9876816Z test_openreg 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_openreg_1.1_39f2c09fcf7a21f5_.log 2025-08-26T20:04:53.9889809Z Running 44 items in this shard: test/test_openreg.py::TestPrivateUse1::test_backend_dispatchstub, test/test_openreg.py::TestPrivateUse1::test_backend_generate_methods, test/test_openreg.py::TestPrivateUse1::test_backend_module_function, test/test_openreg.py::TestPrivateUse1::test_backend_module_methods, test/test_openreg.py::TestPrivateUse1::test_backend_module_registration, test/test_openreg.py::TestPrivateUse1::test_backend_name, test/test_openreg.py::TestPrivateUse1::test_backend_operator_registration, test/test_openreg.py::TestPrivateUse1::test_backend_packed_sequence_methods, test/test_openreg.py::TestPrivateUse1::test_backend_storage_methods, test/test_openreg.py::TestPrivateUse1::test_backend_tensor_methods, test/test_openreg.py::TestPrivateUse1::test_backend_tensor_type, test/test_openreg.py::TestPrivateUse1::test_backend_type_methods, test/test_openreg.py::TestOpenReg::test_autograd_init, test/test_openreg.py::TestOpenReg::test_compile_autograd_function_aliasing, test/test_openreg.py::TestOpenReg::test_compile_autograd_function_returns_self, test/test_openreg.py::TestOpenReg::test_copy_same_device, test/test_openreg.py::TestOpenReg::test_cross_device_copy, test/test_openreg.py::TestOpenReg::test_cross_diff_devices_copy, test/test_openreg.py::TestOpenReg::test_data_dependent_output, test/test_openreg.py::TestOpenReg::test_event_elapsed_time, test/test_openreg.py::TestOpenReg::test_event_wait_stream, test/test_openreg.py::TestOpenReg::test_expand, test/test_openreg.py::TestOpenReg::test_factory, test/test_openreg.py::TestOpenReg::test_fake_tensor, test/test_openreg.py::TestOpenReg::test_generator, test/test_openreg.py::TestOpenReg::test_manual_seed, test/test_openreg.py::TestOpenReg::test_named_tensor, test/test_openreg.py::TestOpenReg::test_open_device_cpu_serialization, test/test_openreg.py::TestOpenReg::test_open_device_dlpack, test/test_openreg.py::TestOpenReg::test_open_device_numpy_serialization, test/test_openreg.py::TestOpenReg::test_pin_memory, test/test_openreg.py::TestOpenReg::test_printing, test/test_openreg.py::TestOpenReg::test_quantize, test/test_openreg.py::TestOpenReg::test_record_event, test/test_openreg.py::TestOpenReg::test_resize, test/test_openreg.py::TestOpenReg::test_rewrapped_storage, test/test_openreg.py::TestOpenReg::test_rng_state, test/test_openreg.py::TestOpenReg::test_scalar_type_fallback, test/test_openreg.py::TestOpenReg::test_serialization, test/test_openreg.py::TestOpenReg::test_stream_synchronize, test/test_openreg.py::TestOpenReg::test_stream_wait_event, test/test_openreg.py::TestOpenReg::test_stream_wait_stream, test/test_openreg.py::TestOpenReg::test_tensor_type_fallback, test/test_openreg.py::TestOpenReg::test_tensorlist_type_fallback 2025-08-26T20:04:53.9901482Z 2025-08-26T20:04:53.9901688Z Running test_show_pickle 1/1 ... [2025-08-26 20:04:53.987808] 2025-08-26T20:04:53.9902108Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:04:53.9903170Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_show_pickle.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:04:53.988100] 2025-08-26T20:04:57.0561928Z 2025-08-26T20:04:57.0562779Z test_show_pickle 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_show_pickle_1.1_032c6fc1a436d160_.log 2025-08-26T20:04:57.0563751Z Running 1 items in this shard: test/test_show_pickle.py::TestShowPickle::test_scripted_model 2025-08-26T20:04:57.0564188Z 2025-08-26T20:04:57.0564721Z Running test_torch 1/1 ... [2025-08-26 20:04:57.056345] 2025-08-26T20:04:57.0565106Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:04:57.0568050Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_torch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:04:57.056626] 2025-08-26T20:05:11.7907467Z 2025-08-26T20:05:11.7908261Z test_torch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_torch_1.1_0757e1b4ee51d332_.log 2025-08-26T20:05:11.8210012Z Running 953 items in this shard: test/test_torch.py::TestBasicVitalSigns::test_basic_vitals, test/test_torch.py::TestBasicVitalSigns::test_basic_vitals_read_write, test/test_torch.py::TestBasicVitalSigns::test_dataloader_vitals, test/test_torch.py::TestTorch::test_RNGState, test/test_torch.py::TestTorch::test_RNGStateAliasing, test/test_torch.py::TestTorch::test_RNG_after_pickle, test/test_torch.py::TestTorch::test_Size, test/test_torch.py::TestTorch::test_Size_concat_non_tuple_sequence, test/test_torch.py::TestTorch::test_Size_concat_wildcard, test/test_torch.py::TestTorch::test_Size_iter, test/test_torch.py::TestTorch::test_Size_scalar, test/test_torch.py::TestTorch::test_add_meta_scalar, test/test_torch.py::TestTorch::test_allow_tensor_metadata_change, test/test_torch.py::TestTorch::test_apply, test/test_torch.py::TestTorch::test_as_subclass, test/test_torch.py::TestTorch::test_assert_async, test/test_torch.py::TestTorch::test_backward_hooks_traverse, test/test_torch.py::TestTorch::test_batch_norm_cpu_inference, test/test_torch.py::TestTorch::test_bf16_supported_on_cpu, test/test_torch.py::TestTorch::test_bmm_multithreaded, test/test_torch.py::TestTorch::test_boxMullerState, test/test_torch.py::TestTorch::test_cat_neg_dim, test/test_torch.py::TestTorch::test_check, test/test_torch.py::TestTorch::test_chunk_neg_dim, test/test_torch.py::TestTorch::test_conj_neg_tolist, test/test_torch.py::TestTorch::test_conj_physical_meta_stride, test/test_torch.py::TestTorch::test_contains, test/test_torch.py::TestTorch::test_copy_broadcast, test/test_torch.py::TestTorch::test_copy_dtypes, test/test_torch.py::TestTorch::test_copy_float16, test/test_torch.py::TestTorch::test_copy_many_to_one, test/test_torch.py::TestTorch::test_copy_transpose, test/test_torch.py::TestTorch::test_cuda_not_built, test/test_torch.py::TestTorch::test_cummax_neg_dim, test/test_torch.py::TestTorch::test_cummin_neg_dim, test/test_torch.py::TestTorch::test_cumprod_neg_dim, test/test_torch.py::TestTorch::test_cumsum_neg_dim, test/test_torch.py::TestTorch::test_cxx_flags, test/test_torch.py::TestTorch::test_data_ptr_of_empty_tensor_with_storage, test/test_torch.py::TestTorch::test_data_ptr_of_empty_view_with_storage, test/test_torch.py::TestTorch::test_deepcopy_gradient, test/test_torch.py::TestTorch::test_deepcopy_parameter, test/test_torch.py::TestTorch::test_deterministic_fill_uninitialized_memory, test/test_torch.py::TestTorch::test_deterministic_flag, test/test_torch.py::TestTorch::test_device, test/test_torch.py::TestTorch::test_dim_order, test/test_torch.py::TestTorch::test_dir, test/test_torch.py::TestTorch::test_doc, test/test_torch.py::TestTorch::test_doc_template, test/test_torch.py::TestTorch::test_dot_data_use, test/test_torch.py::TestTorch::test_dtype_is_signed, test/test_torch.py::TestTorch::test_element_size, test/test_torch.py::TestTorch::test_empty_meta, test/test_torch.py::TestTorch::test_empty_storage_view, test/test_torch.py::TestTorch::test_equal, test/test_torch.py::TestTorch::test_error_msg_type_translation, test/test_torch.py::TestTorch::test_fill_diagonal, test/test_torch.py::TestTorch::test_format_scalar_meta, test/test_torch.py::TestTorch::test_from_buffer, test/test_torch.py::TestTorch::test_from_file, test/test_torch.py::TestTorch::test_gather_neg_dim, test/test_torch.py::TestTorch::test_generator_cpu, test/test_torch.py::TestTorch::test_get_cpu_capability, test/test_torch.py::TestTorch::test_has_internal_overlap, test/test_torch.py::TestTorch::test_has_storage, test/test_torch.py::TestTorch::test_index_add, test/test_torch.py::TestTorch::test_index_add_all_dtypes, test/test_torch.py::TestTorch::test_index_add_cornercase, test/test_torch.py::TestTorch::test_index_add_correctness, test/test_torch.py::TestTorch::test_index_add_neg_dim, test/test_torch.py::TestTorch::test_index_copy_neg_dim, test/test_torch.py::TestTorch::test_index_fill_neg_dim, test/test_torch.py::TestTorch::test_index_select_neg_dim, test/test_torch.py::TestTorch::test_invalid_arg_error_handling, test/test_torch.py::TestTorch::test_invalid_generator_raises, test/test_torch.py::TestTorch::test_is_nonzero, test/test_torch.py::TestTorch::test_is_same_size, test/test_torch.py::TestTorch::test_iter, test/test_torch.py::TestTorch::test_kthvalue_neg_dim, test/test_torch.py::TestTorch::test_linspace_logspace, test/test_torch.py::TestTorch::test_logcumsumexp_neg_dim, test/test_torch.py::TestTorch::test_manual_seed, test/test_torch.py::TestTorch::test_map, test/test_torch.py::TestTorch::test_map2, test/test_torch.py::TestTorch::test_max_neg_dim, test/test_torch.py::TestTorch::test_mean_neg_dim, test/test_torch.py::TestTorch::test_median_neg_dim, test/test_torch.py::TestTorch::test_memory_format, test/test_torch.py::TestTorch::test_memory_format_contiguous_returns_same_tensor_if_already_satisfies, test/test_torch.py::TestTorch::test_memory_format_empty, test/test_torch.py::TestTorch::test_min_neg_dim, test/test_torch.py::TestTorch::test_mode_neg_dim, test/test_torch.py::TestTorch::test_multinomial_invalid_probs, test/test_torch.py::TestTorch::test_nanmedian_neg_dim, test/test_torch.py::TestTorch::test_narrow_neg_dim, test/test_torch.py::TestTorch::test_nbytes, test/test_torch.py::TestTorch::test_ndim, test/test_torch.py::TestTorch::test_new, test/test_torch.py::TestTorch::test_newaxis_numpy_comparison, test/test_torch.py::TestTorch::test_newindex, test/test_torch.py::TestTorch::test_no_cuda_monkeypatch, test/test_torch.py::TestTorch::test_norm_neg_dim, test/test_torch.py::TestTorch::test_normal_shape, test/test_torch.py::TestTorch::test_numel, test/test_torch.py::TestTorch::test_parallel_info, test/test_torch.py::TestTorch::test_parsing_double, test/test_torch.py::TestTorch::test_parsing_int64, test/test_torch.py::TestTorch::test_parsing_intlist, test/test_torch.py::TestTorch::test_permute, test/test_torch.py::TestTorch::test_pickle, test/test_torch.py::TestTorch::test_pickle_dtype, test/test_torch.py::TestTorch::test_pickle_function, test/test_torch.py::TestTorch::test_pickle_generator, test/test_torch.py::TestTorch::test_pickle_parameter, test/test_torch.py::TestTorch::test_pickle_parameter_no_requires_grad, test/test_torch.py::TestTorch::test_pickle_size, test/test_torch.py::TestTorch::test_pin_memory, test/test_torch.py::TestTorch::test_print, test/test_torch.py::TestTorch::test_prod_neg_dim, test/test_torch.py::TestTorch::test_pyobj_preserved, test/test_torch.py::TestTorch::test_qengine, test/test_torch.py::TestTorch::test_renorm_neg_dim, test/test_torch.py::TestTorch::test_resizable, test/test_torch.py::TestTorch::test_reversed, test/test_torch.py::TestTorch::test_scatter_neg_dim, test/test_torch.py::TestTorch::test_select_neg_dim, test/test_torch.py::TestTorch::test_set_flush_denormal, test/test_torch.py::TestTorch::test_setting_real_imag_to_a_number, test/test_torch.py::TestTorch::test_show_config, test/test_torch.py::TestTorch::test_size_neg_dim, test/test_torch.py::TestTorch::test_size_stride, test/test_torch.py::TestTorch::test_sizeof, test/test_torch.py::TestTorch::test_slice, test/test_torch.py::TestTorch::test_slow_test, test/test_torch.py::TestTorch::test_sobolengine_bounds, test/test_torch.py::TestTorch::test_sobolengine_bounds_scrambled, test/test_torch.py::TestTorch::test_sobolengine_continuing, test/test_torch.py::TestTorch::test_sobolengine_continuing_scrambled, test/test_torch.py::TestTorch::test_sobolengine_default_dtype, test/test_torch.py::TestTorch::test_sobolengine_distribution, test/test_torch.py::TestTorch::test_sobolengine_distribution_scrambled, test/test_torch.py::TestTorch::test_sobolengine_draw, test/test_torch.py::TestTorch::test_sobolengine_draw_base2, test/test_torch.py::TestTorch::test_sobolengine_draw_base2_scrambled, test/test_torch.py::TestTorch::test_sobolengine_draw_scrambled, test/test_torch.py::TestTorch::test_sobolengine_fast_forward, test/test_torch.py::TestTorch::test_sobolengine_fast_forward_scrambled, test/test_torch.py::TestTorch::test_sobolengine_first_point, test/test_torch.py::TestTorch::test_sobolengine_high_dim, test/test_torch.py::TestTorch::test_sobolengine_raise, test/test_torch.py::TestTorch::test_sobolengine_reset, test/test_torch.py::TestTorch::test_sobolengine_reset_scrambled, test/test_torch.py::TestTorch::test_sort_neg_dim, test/test_torch.py::TestTorch::test_split_neg_dim, test/test_torch.py::TestTorch::test_split_with_sizes_copy_out, test/test_torch.py::TestTorch::test_squeeze_neg_dim, test/test_torch.py::TestTorch::test_std_neg_dim, test/test_torch.py::TestTorch::test_storage_base_init, test/test_torch.py::TestTorch::test_storage_base_new, test/test_torch.py::TestTorch::test_storage_byteswap, test/test_torch.py::TestTorch::test_storage_casts, test/test_torch.py::TestTorch::test_storage_cycle_via_dict, test/test_torch.py::TestTorch::test_storage_cycle_via_slots, test/test_torch.py::TestTorch::test_storage_dead_weak_ref, test/test_torch.py::TestTorch::test_storage_dealloc, test/test_torch.py::TestTorch::test_storage_dealloc_resurrected, test/test_torch.py::TestTorch::test_storage_dealloc_subclass_resurrected, test/test_torch.py::TestTorch::test_storage_dealloc_subclass_zombie, test/test_torch.py::TestTorch::test_storage_dict_dealloc, test/test_torch.py::TestTorch::test_storage_error, test/test_torch.py::TestTorch::test_storage_error_no_attribute, test/test_torch.py::TestTorch::test_storage_finalizer_dealloc, test/test_torch.py::TestTorch::test_storage_fix_weakref_no_leak, test/test_torch.py::TestTorch::test_storage_from_tensor_dealloc, test/test_torch.py::TestTorch::test_storage_from_tensor_dealloc_resurrected, test/test_torch.py::TestTorch::test_storage_from_tensor_dealloc_zombie, test/test_torch.py::TestTorch::test_storage_preserve_nonhermetic_in_hermetic_context, test/test_torch.py::TestTorch::test_storage_resurrected_weak_ref, test/test_torch.py::TestTorch::test_storage_slot_dealloc, test/test_torch.py::TestTorch::test_storage_weakref_dealloc, test/test_torch.py::TestTorch::test_structseq_repr, test/test_torch.py::TestTorch::test_subclass_preserved, test/test_torch.py::TestTorch::test_subclass_tensors, test/test_torch.py::TestTorch::test_sum_neg_dim, test/test_torch.py::TestTorch::test_swap_basic, test/test_torch.py::TestTorch::test_swap_fail_slots, test/test_torch.py::TestTorch::test_t_not_2d_error, test/test_torch.py::TestTorch::test_tensor_base_init, test/test_torch.py::TestTorch::test_tensor_base_new, test/test_torch.py::TestTorch::test_tensor_ctor_scalar, test/test_torch.py::TestTorch::test_tensor_cycle_via_dict, test/test_torch.py::TestTorch::test_tensor_cycle_via_slots, test/test_torch.py::TestTorch::test_tensor_dead_weak_ref, test/test_torch.py::TestTorch::test_tensor_dict_dealloc, test/test_torch.py::TestTorch::test_tensor_finalizer_dealloc, test/test_torch.py::TestTorch::test_tensor_fix_weakref_no_leak, test/test_torch.py::TestTorch::test_tensor_item_no_warning, test/test_torch.py::TestTorch::test_tensor_ressurecting_clear, test/test_torch.py::TestTorch::test_tensor_resurrected_weak_ref, test/test_torch.py::TestTorch::test_tensor_set, test/test_torch.py::TestTorch::test_tensor_set_errors, test/test_torch.py::TestTorch::test_tensor_slot_dealloc, test/test_torch.py::TestTorch::test_tensor_weakref_dealloc, test/test_torch.py::TestTorch::test_tensor_where_scalar, test/test_torch.py::TestTorch::test_tensor_with_grad_to_scalar_warning, test/test_torch.py::TestTorch::test_tensoriterator_output_setup, test/test_torch.py::TestTorch::test_terminate_handler_on_crash, test/test_torch.py::TestTorch::test_to, test/test_torch.py::TestTorch::test_to_with_tensor, test/test_torch.py::TestTorch::test_topk_neg_dim, test/test_torch.py::TestTorch::test_torch_from_file, test/test_torch.py::TestTorch::test_transpose_neg_dim, test/test_torch.py::TestTorch::test_type, test/test_torch.py::TestTorch::test_type_alias, test/test_torch.py::TestTorch::test_type_conversion_via_dtype_name, test/test_torch.py::TestTorch::test_typed_storage_deprecation_warning, test/test_torch.py::TestTorch::test_typed_storage_internal_no_warning, test/test_torch.py::TestTorch::test_unbind_neg_dim, test/test_torch.py::TestTorch::test_unflatten, test/test_torch.py::TestTorch::test_unfold_neg_dim, test/test_torch.py::TestTorch::test_unsqueeze_neg_dim, test/test_torch.py::TestTorch::test_upsample_nearest1d_meta, test/test_torch.py::TestTorch::test_upsample_nearest2d_meta, test/test_torch.py::TestTorch::test_var_neg_dim, test/test_torch.py::TestTorch::test_warn_types, test/test_torch.py::TestTorch::test_wildcard_import, test/test_torch.py::TestVitalSignsCudaCPU::test_cuda_vitals_gpu_only_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test__local_scalar_dense_with_empty_tensor_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcdiv_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_cuda_errors_with_cpu_scalars_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_False_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_addcmul_use_cpu_scalar_True_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_assertRaisesRegex_ignore_msg_non_native_device_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_edge_cases_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_edge_cases_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_edge_cases_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_p_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_bernoulli_self_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_bfloat16_neg_abs_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bool_tensor_value_change_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_add_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_addcdiv_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_addcmul_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_atan2_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_copy_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_dist_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_div_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_eq_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_fmod_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_ge_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_gt_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_le_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_lerp_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_lt_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_map2_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_map_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_fill_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_scatter_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_masked_select_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_max_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_min_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_mul_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_ne_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_pow_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_remainder_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_broadcast_fn_sub_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_bytes_to_scalar_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_kstest_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_no_inf_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_cauchy_no_inf_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_cuda_backward_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_euclidean_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_grad_p_lt_1_no_nan_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_large_batch_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_non_contiguous_batch_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_non_contiguous_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_norm_batch_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_norm_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cdist_same_inputs_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_check_tensor_all_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_check_tensor_internal_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_clone_all_dtypes_and_devices_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_clone_not_memory_dense_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_clone_zero_stride_dim_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_complex_half_experimental_warning_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_constants_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_conv_transposed_backward_agnostic_to_memory_format_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_conv_transposed_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_complex32, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy__cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy_all_dtypes_and_devices_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy_math_view_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy_mem_overlap_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy_transpose_math_view_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy_transpose_math_view_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_copy_transpose_math_view_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_corrcoef_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_corrcoef_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_corrcoef_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_cov_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cpp_warnings_have_python_context_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cublas_config_nondeterministic_alert_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cummax_cummin_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cummax_discontiguous_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cummin_discontiguous_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cumprod_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cumsum_64bit_indexing_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_cumsum_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_deepcopy_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deepcopy_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deepcopy_scalar_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deepcopy_scalar_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_cumsum_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_complex32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_empty_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_interpolate_bilinear_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_replication_pad2d_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_deterministic_resize_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_device_guard_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_diff_noncontig_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_dim_function_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_discontiguous_out_cumsum_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_dist_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_dtypetensor_warnings_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_expected_failure_xla_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_kstest_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_kstest_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_kstest_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_kstest_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_no_zero_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_exponential_no_zero_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_gather_backward_deterministic_path_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_gather_backward_one_dim_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_geometric_kstest_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scale_will_not_overflow_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaler_deprecated_warning_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaler_pass_itself_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_accumulation_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach0_fused0_AdamW_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach0_fused0_Adam_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach0_fused0_SGD_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach2_fused_True_AdamW_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach2_fused_True_Adam_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach2_fused_True_SGD_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach_True_fused1_AdamW_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach_True_fused1_Adam_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_autocast_foreach_True_fused1_SGD_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_clipping_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_clipping_separate_unscale_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_multiple_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_penalty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_state_dict_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_unscale_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_unscale_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_unscale_sparse_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_grad_scaling_update_scale_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_all_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_all_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_all_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_extreme_cases_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_extreme_cases_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_extreme_cases_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_spacing_list_length_error_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_spacing_list_length_error_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_spacing_list_length_error_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_gradient_type_promotion_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_hook_remove_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_index_add_large_inputs_cpu, 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test/test_torch.py::TestTorchDeviceTypeCPU::test_parallel_cow_materialize_error_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_parallel_cow_materialize_error_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_parallel_cow_materialize_error_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_parallel_cow_materialize_error_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_parallel_cow_materialize_error_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_parallel_cow_materialize_error_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_parallel_cow_materialize_error_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_and_graph_partition_AdamW_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_and_graph_partition_Adam_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_and_graph_partition_SGD_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_between_unscale_and_step_AdamW_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_between_unscale_and_step_Adam_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_params_invalidated_with_grads_invalidated_between_unscale_and_step_SGD_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_pdist_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_pdist_norm_large_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_pickle_gradscaler_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_pin_memory_from_constructor_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_accumulate_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_put_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_reduced_type_float_copy_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_reduced_type_float_copy_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_repeat_interleave_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scalar_check_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_bool_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_non_unique_index_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_one_dim_deterministic_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_add_to_large_input_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_bool_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_multiply_unsupported_dtypes_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_multiply_unsupported_dtypes_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_non_unique_index_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_operations_to_large_input_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_reduce_scalar_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_to_large_input_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_scatter_zero_size_index_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_serialization_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_default_tensor_type_warnings_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_set_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_shift_mem_overlap_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_skip_xla_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_all_devices_non_blocking_False_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_all_devices_non_blocking_True_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_errors_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_from_tensor_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_meta_ok_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_qint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_qint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_quint4x2, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_quint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_setitem_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_storage_use_count_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_strides_propagation_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_sync_warning_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_take_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_from_storage_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_set_errors_multigpu_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_shape_empty_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_storage_type_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_tensor_type_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_ternary_op_mem_overlap_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_bool, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_complex128, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_complex64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int16, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int32, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int64, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_int8, test/test_torch.py::TestTorchDeviceTypeCPU::test_typed_storage_meta_cpu_uint8, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_bfloat16, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float16, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float32, test/test_torch.py::TestTorchDeviceTypeCPU::test_uniform_kstest_cpu_float64, test/test_torch.py::TestTorchDeviceTypeCPU::test_untyped_storage_meta_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_warn_always_caught_cpu, test/test_torch.py::TestTorchDeviceTypeCPU::test_where_scalar_handcrafted_values_cpu 2025-08-26T20:05:11.8866508Z 2025-08-26T20:05:11.8866887Z Running test_tensorexpr 1/1 ... [2025-08-26 20:05:11.792032] 2025-08-26T20:05:11.8867672Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:05:11.8869660Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorexpr.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:05:11.792337] 2025-08-26T20:05:32.0844047Z 2025-08-26T20:05:32.0845020Z test_tensorexpr 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorexpr_1.1_63973a47a7090828_.log 2025-08-26T20:05:32.0866602Z Running 74 items in this shard: test/test_tensorexpr.py::TestTensorExprFuser::test_add_const_rhs, test/test_tensorexpr.py::TestTensorExprFuser::test_add_sub, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_input_and_module, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_inputs, test/test_tensorexpr.py::TestTensorExprFuser::test_alias_analysis_module, test/test_tensorexpr.py::TestTensorExprFuser::test_all_combos, test/test_tensorexpr.py::TestTensorExprFuser::test_alpha, test/test_tensorexpr.py::TestTensorExprFuser::test_binary_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_bitwise_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast3, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast_2, test/test_tensorexpr.py::TestTensorExprFuser::test_broadcast_big2, test/test_tensorexpr.py::TestTensorExprFuser::test_cat, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_empty_tensors, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_negative_dim, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_only, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_promote_inputs, test/test_tensorexpr.py::TestTensorExprFuser::test_cat_with_constant_dim, test/test_tensorexpr.py::TestTensorExprFuser::test_char, test/test_tensorexpr.py::TestTensorExprFuser::test_chunk, test/test_tensorexpr.py::TestTensorExprFuser::test_clamp, test/test_tensorexpr.py::TestTensorExprFuser::test_constant, test/test_tensorexpr.py::TestTensorExprFuser::test_double, test/test_tensorexpr.py::TestTensorExprFuser::test_double_intrinsics, test/test_tensorexpr.py::TestTensorExprFuser::test_dynamic_shape, test/test_tensorexpr.py::TestTensorExprFuser::test_easy, test/test_tensorexpr.py::TestTensorExprFuser::test_eq, test/test_tensorexpr.py::TestTensorExprFuser::test_exp_pow, test/test_tensorexpr.py::TestTensorExprFuser::test_four_arg, test/test_tensorexpr.py::TestTensorExprFuser::test_ge, test/test_tensorexpr.py::TestTensorExprFuser::test_gt, test/test_tensorexpr.py::TestTensorExprFuser::test_guard_fails, test/test_tensorexpr.py::TestTensorExprFuser::test_half_bn_relu, test/test_tensorexpr.py::TestTensorExprFuser::test_half_gelu, test/test_tensorexpr.py::TestTensorExprFuser::test_int64_promotion, test/test_tensorexpr.py::TestTensorExprFuser::test_int_output, test/test_tensorexpr.py::TestTensorExprFuser::test_le, test/test_tensorexpr.py::TestTensorExprFuser::test_loop, test/test_tensorexpr.py::TestTensorExprFuser::test_lt, test/test_tensorexpr.py::TestTensorExprFuser::test_mask, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction2, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction_dim1, test/test_tensorexpr.py::TestTensorExprFuser::test_min_max_reduction_dim1_2, test/test_tensorexpr.py::TestTensorExprFuser::test_multi_rand, test/test_tensorexpr.py::TestTensorExprFuser::test_multioutput, test/test_tensorexpr.py::TestTensorExprFuser::test_multiple_outputs, test/test_tensorexpr.py::TestTensorExprFuser::test_nans, test/test_tensorexpr.py::TestTensorExprFuser::test_ne, test/test_tensorexpr.py::TestTensorExprFuser::test_promotion, test/test_tensorexpr.py::TestTensorExprFuser::test_propagated_mem_layout, test/test_tensorexpr.py::TestTensorExprFuser::test_rand_like, test/test_tensorexpr.py::TestTensorExprFuser::test_rank_two, test/test_tensorexpr.py::TestTensorExprFuser::test_relu, test/test_tensorexpr.py::TestTensorExprFuser::test_remainder, test/test_tensorexpr.py::TestTensorExprFuser::test_reps, test/test_tensorexpr.py::TestTensorExprFuser::test_round_2, test/test_tensorexpr.py::TestTensorExprFuser::test_scalar, test/test_tensorexpr.py::TestTensorExprFuser::test_short, test/test_tensorexpr.py::TestTensorExprFuser::test_simple_add, test/test_tensorexpr.py::TestTensorExprFuser::test_sin_pow, test/test_tensorexpr.py::TestTensorExprFuser::test_slice, test/test_tensorexpr.py::TestTensorExprFuser::test_sliced_stride, test/test_tensorexpr.py::TestTensorExprFuser::test_softmax_cpu, test/test_tensorexpr.py::TestTensorExprFuser::test_softmax_cuda, test/test_tensorexpr.py::TestTensorExprFuser::test_strided_output_preserved, test/test_tensorexpr.py::TestTensorExprFuser::test_three_arg, test/test_tensorexpr.py::TestTensorExprFuser::test_three_arg2, test/test_tensorexpr.py::TestTensorExprFuser::test_transpose, test/test_tensorexpr.py::TestTensorExprFuser::test_unary_ops, test/test_tensorexpr.py::TestTensorExprFuser::test_unsqueeze, test/test_tensorexpr.py::TestTensorExprFuser::test_where 2025-08-26T20:05:32.0886869Z 2025-08-26T20:05:32.0887090Z Running test_namedtuple_return_api 1/1 ... [2025-08-26 20:05:32.084725] 2025-08-26T20:05:32.0887548Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:05:32.0888706Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_namedtuple_return_api.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:05:32.085061] 2025-08-26T20:05:36.0566970Z 2025-08-26T20:05:36.0567941Z test_namedtuple_return_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_namedtuple_return_api_1.1_9560845986ab9550_.log 2025-08-26T20:05:36.0569995Z Running 3 items in this shard: test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_import_return_types, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_namedtuple_return, test/test_namedtuple_return_api.py::TestNamedTupleAPI::test_native_functions_yaml 2025-08-26T20:05:36.0571444Z 2025-08-26T20:05:36.0571678Z Running test_multiprocessing 1/1 ... [2025-08-26 20:05:36.056877] 2025-08-26T20:05:36.0572195Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:05:36.0574252Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_multiprocessing.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:05:36.057201] 2025-08-26T20:06:34.7008209Z 2025-08-26T20:06:34.7009157Z test_multiprocessing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_1.1_6903975d470639fc_.log 2025-08-26T20:06:34.7024573Z Running 42 items in this shard: test/test_multiprocessing.py::TestMultiprocessing::test_autograd_errors, test/test_multiprocessing.py::TestMultiprocessing::test_autograd_fine_with_spawn, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_bad_call, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_ipc_deadlock, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_memory_allocation, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_parameter_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_send_many, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_simple, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_small_tensors, test/test_multiprocessing.py::TestMultiprocessing::test_cuda_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_empty_shared, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_empty_tensor_sharing_meta, test/test_multiprocessing.py::TestMultiprocessing::test_event, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_exporter, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_importer, test/test_multiprocessing.py::TestMultiprocessing::test_event_handle_multi_gpu, test/test_multiprocessing.py::TestMultiprocessing::test_event_multiprocess, test/test_multiprocessing.py::TestMultiprocessing::test_fd_pool, test/test_multiprocessing.py::TestMultiprocessing::test_fd_preserve_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fd_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fs, test/test_multiprocessing.py::TestMultiprocessing::test_fs_is_shared, test/test_multiprocessing.py::TestMultiprocessing::test_fs_pool, test/test_multiprocessing.py::TestMultiprocessing::test_fs_preserve_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_fs_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_inherit_tensor, test/test_multiprocessing.py::TestMultiprocessing::test_integer_parameter_serialization_cpu, test/test_multiprocessing.py::TestMultiprocessing::test_integer_parameter_serialization_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_is_shared, test/test_multiprocessing.py::TestMultiprocessing::test_is_shared_cuda, test/test_multiprocessing.py::TestMultiprocessing::test_leaf_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_meta_simple, test/test_multiprocessing.py::TestMultiprocessing::test_mixed_types_cuda_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_non_leaf_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_parameter_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_rebuild_cuda_tensor, test/test_multiprocessing.py::TestMultiprocessing::test_set_thread_name, test/test_multiprocessing.py::TestMultiprocessing::test_tensor_sharing_meta, test/test_multiprocessing.py::TestMultiprocessing::test_variable_sharing, test/test_multiprocessing.py::TestMultiprocessing::test_wrong_cuda_fork 2025-08-26T20:06:34.7039181Z 2025-08-26T20:06:34.7039407Z Running test_autograd_fallback 1/1 ... [2025-08-26 20:06:34.700975] 2025-08-26T20:06:34.7039853Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:06:34.7040938Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_autograd_fallback.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:06:34.701283] 2025-08-26T20:06:37.9700073Z 2025-08-26T20:06:37.9701007Z test_autograd_fallback 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autograd_fallback_1.1_b7122dbe4d2ccea3_.log 2025-08-26T20:06:37.9713884Z Running 28 items in this shard: test/test_autograd_fallback.py::TestAutogradFallback::test_autograd_function_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_autograd_function_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_base_does_not_require_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_base_does_not_require_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_composite_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_composite_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_cpu_return_self_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_cpu_return_self_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_autograd_function_registered_to_cpu_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_autograd_function_registered_to_cpu_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_on_tensor_that_does_not_require_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_inplace_on_tensor_that_does_not_require_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_inplace_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_inplace_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_autograd_kernel_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_no_grad_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_no_grad_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_leaf_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_leaf_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_mix_of_requires_grad_tensors_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_post_autograd_returns_mix_of_requires_grad_tensors_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_supports_tensor_lists_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_supports_tensor_lists_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_grads_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_grads_mode_warn, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_inputs_outputs_mode_nothing, test/test_autograd_fallback.py::TestAutogradFallback::test_undefined_inputs_outputs_mode_warn 2025-08-26T20:06:37.9726306Z 2025-08-26T20:06:37.9726511Z Running test_fake_tensor 1/1 ... [2025-08-26 20:06:37.970216] 2025-08-26T20:06:37.9726925Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:06:37.9727979Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fake_tensor.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:06:37.970569] 2025-08-26T20:06:49.9511541Z 2025-08-26T20:06:49.9512353Z test_fake_tensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fake_tensor_1.1_57cf845708d3e0b4_.log 2025-08-26T20:06:49.9632356Z Running 290 items in this shard: test/test_fake_tensor.py::FakeTensorTest::test__adaptive_avg_pool2d_backward, test/test_fake_tensor.py::FakeTensorTest::test_alias_call, test/test_fake_tensor.py::FakeTensorTest::test_allow_meta, test/test_fake_tensor.py::FakeTensorTest::test_aten_copy_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_index_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_aten_slice_scatter_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_basic, test/test_fake_tensor.py::FakeTensorTest::test_batch_tensor, test/test_fake_tensor.py::FakeTensorTest::test_binary_op_type_promotion, test/test_fake_tensor.py::FakeTensorTest::test_constructor, test/test_fake_tensor.py::FakeTensorTest::test_convert_fake_to_real, test/test_fake_tensor.py::FakeTensorTest::test_cpu_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cuda_initialized, test/test_fake_tensor.py::FakeTensorTest::test_cuda_lstm, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_with_fallback, test/test_fake_tensor.py::FakeTensorTest::test_cudnn_rnn_without_fallback, test/test_fake_tensor.py::FakeTensorTest::test_custom_op_fallback, test/test_fake_tensor.py::FakeTensorTest::test_data_dependent_operator, test/test_fake_tensor.py::FakeTensorTest::test_deepcopy, test/test_fake_tensor.py::FakeTensorTest::test_device_inplace_copy, test/test_fake_tensor.py::FakeTensorTest::test_embedding_bag_meta, test/test_fake_tensor.py::FakeTensorTest::test_export_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fake_device, test/test_fake_tensor.py::FakeTensorTest::test_fake_dispatch_keys, test/test_fake_tensor.py::FakeTensorTest::test_fake_grad_copy, test/test_fake_tensor.py::FakeTensorTest::test_fake_mode_error, test/test_fake_tensor.py::FakeTensorTest::test_fast_div, test/test_fake_tensor.py::FakeTensorTest::test_from_numpy, test/test_fake_tensor.py::FakeTensorTest::test_fsdp_flat_param, test/test_fake_tensor.py::FakeTensorTest::test_full, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex128, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_complex64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int16, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int32, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int64, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_int8, test/test_fake_tensor.py::FakeTensorTest::test_index_cuda_with_cpu_uint8, test/test_fake_tensor.py::FakeTensorTest::test_index_put_error, test/test_fake_tensor.py::FakeTensorTest::test_jagged_fake_to_fake_preserved, test/test_fake_tensor.py::FakeTensorTest::test_like_constructor, test/test_fake_tensor.py::FakeTensorTest::test_mixed_real_and_fake_inputs, test/test_fake_tensor.py::FakeTensorTest::test_mode, test/test_fake_tensor.py::FakeTensorTest::test_nan_to_num, test/test_fake_tensor.py::FakeTensorTest::test_nanmean_out, test/test_fake_tensor.py::FakeTensorTest::test_new, test/test_fake_tensor.py::FakeTensorTest::test_no_tag_func, test/test_fake_tensor.py::FakeTensorTest::test_non_kwarg_device, test/test_fake_tensor.py::FakeTensorTest::test_non_overlapping_stride_zero, test/test_fake_tensor.py::FakeTensorTest::test_non_parameter_grad, test/test_fake_tensor.py::FakeTensorTest::test_normalize_device, test/test_fake_tensor.py::FakeTensorTest::test_op_with_zero_dim_bypassed, test/test_fake_tensor.py::FakeTensorTest::test_out_multi_device, test/test_fake_tensor.py::FakeTensorTest::test_parameter_instantiation, test/test_fake_tensor.py::FakeTensorTest::test_parameter_view, test/test_fake_tensor.py::FakeTensorTest::test_print_in_fake_mode, test/test_fake_tensor.py::FakeTensorTest::test_randperm, test/test_fake_tensor.py::FakeTensorTest::test_recursive_invocation, test/test_fake_tensor.py::FakeTensorTest::test_repr, test/test_fake_tensor.py::FakeTensorTest::test_same_shape_env_preserved, test/test_fake_tensor.py::FakeTensorTest::test_scalar_inputs, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_False, test/test_fake_tensor.py::FakeTensorTest::test_scan_reverse_True, test/test_fake_tensor.py::FakeTensorTest::test_setitem, test/test_fake_tensor.py::FakeTensorTest::test_shape_take_not_device, test/test_fake_tensor.py::FakeTensorTest::test_split_return_self, test/test_fake_tensor.py::FakeTensorTest::test_throw, test/test_fake_tensor.py::FakeTensorTest::test_tolist, test/test_fake_tensor.py::FakeTensorTest::test_type_as, test/test_fake_tensor.py::FakeTensorTest::test_unbind_copy_out, test/test_fake_tensor.py::FakeTensorTest::test_unsqueeze_copy, test/test_fake_tensor.py::FakeTensorTest::test_upsample_bilinear_small_channels, test/test_fake_tensor.py::FakeTensorTest::test_zero_dim, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test__adaptive_avg_pool2d_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_alias_call_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_allow_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_copy_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_index_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_aten_slice_scatter_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_basic_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_batch_tensor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_binary_op_type_promotion_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_convert_fake_to_real_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cpu_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_initialized_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cuda_lstm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_with_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_cudnn_rnn_without_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_custom_op_fallback_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_data_dependent_operator_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_deepcopy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_device_inplace_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_embedding_bag_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_export_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_dispatch_keys_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_grad_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fake_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fast_div_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_from_numpy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_fsdp_flat_param_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_full_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex128_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_complex64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fn_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e4m3fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_float8_e5m2fnuz_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int16_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int32_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int64_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_int8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_cuda_with_cpu_uint8_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_index_put_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_jagged_fake_to_fake_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_like_constructor_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mixed_real_and_fake_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nan_to_num_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_nanmean_out_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_new_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_no_tag_func_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_kwarg_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_overlapping_stride_zero_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_non_parameter_grad_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_normalize_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_op_with_zero_dim_bypassed_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_out_multi_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_parameter_instantiation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_parameter_view_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_print_in_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_randperm_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_recursive_invocation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_repr_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_same_shape_env_preserved_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scalar_inputs_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_False_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_scan_reverse_True_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_setitem_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_shape_take_not_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_split_return_self_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_throw_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_tolist_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_type_as_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unbind_copy_out_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_unsqueeze_copy_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_upsample_bilinear_small_channels_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorTest::test_zero_dim_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorConstHandling::test_aliased_const_write, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_constant_propagate_through_functions, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_batch_norm_cpu, test/test_fake_tensor.py::FakeTensorConstHandling::test_fake_tensor_in_intlist_repro, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_add, test/test_fake_tensor.py::FakeTensorConstHandling::test_inplace_view_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storage_invalidation, test/test_fake_tensor.py::FakeTensorConstHandling::test_shared_storages, test/test_fake_tensor.py::FakeTensorConstHandling::test_simple, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_aliased_const_write_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_constant_propagate_through_functions_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_batch_norm_cpu_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_fake_tensor_in_intlist_repro_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_add_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_inplace_view_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storage_invalidation_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_shared_storages_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConstHandling::test_simple_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyCatCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyCubeCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyMulCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyMulScalarCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyNMSCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyNonzeroCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySortCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySplitCopyCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyTakeCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorOpInfoTestCPU::test_fake_NumpyViewCopyCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyCatCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyCubeCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyMulCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyMulScalarCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyNMSCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyNonzeroCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySortCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySplitCopyCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyTakeCustomOp_cpu_float32, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOpInfoTestCPU::test_fake_propagate_real_tensors_NumpyViewCopyCustomOp_cpu_float32, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_key, test/test_fake_tensor.py::FakeTensorConverterTest::test_dead_weak_ref, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_from_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_memoized_conversion_to_meta, test/test_fake_tensor.py::FakeTensorConverterTest::test_multiple_modes, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_active_mode, test/test_fake_tensor.py::FakeTensorConverterTest::test_no_ref_cycle, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_mode_error, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_non_view, test/test_fake_tensor.py::FakeTensorConverterTest::test_separate_tensor_storages_view, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_key_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_dead_weak_ref_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_from_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_memoized_conversion_to_meta_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_multiple_modes_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_active_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_no_ref_cycle_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_mode_error_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_non_view_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorConverterTest::test_separate_tensor_storages_view_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_conv_c1_backward, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_cross_entropy_loss, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_embedding_bag_private, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_fake_gpu_no_init, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_flash_attention, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_like_ops, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_module_to, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_no_dispatch_with_like_function, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_non_kwarg_only_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_sparse_new, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_str_storage, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device, test/test_fake_tensor.py::FakeTensorOperatorInvariants::test_tensor_new, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_conv_c1_backward_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_cross_entropy_loss_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_embedding_bag_private_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_fake_gpu_no_init_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_flash_attention_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_like_ops_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_module_to_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_no_dispatch_with_like_function_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_non_kwarg_only_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_sparse_new_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_str_storage_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_constructors_all_have_kwarg_device_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorOperatorInvariants::test_tensor_new_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module, test/test_fake_tensor.py::FakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args, test/test_fake_tensor.py::FakeTensorPropTest::test_nan_to_num, test/test_fake_tensor.py::FakeTensorPropTest::test_nonzero_stride, test/test_fake_tensor.py::FakeTensorPropTest::test_torch_load_with_fake_mode, test/test_fake_tensor.py::FakeTensorPropTest::test_unbacked_shape_realloc, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_fake_tensor_prop_on_nn_module_with_optional_args_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_nan_to_num_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_nonzero_stride_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_torch_load_with_fake_mode_propagate_real_tensors, test/test_fake_tensor.py::PropagateRealTensorsFakeTensorPropTest::test_unbacked_shape_realloc_propagate_real_tensors, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization, test/test_fake_tensor.py::FakeTensorSerialization::test_serialization_with_tracing, test/test_fake_tensor.py::FakeTensorDispatchCache::test__upsample_bilinear2d_aa_backward_dynamic_shapes, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_aten_index, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_bypass, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_default_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_dispatch_key_set, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_hit, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_inplace_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_constants, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_device, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_dtype, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_conj, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_inference, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_is_neg, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_memory_format, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_requires_grad, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_shape, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_storage_offset, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_key_stride, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_tuple_outputs, test/test_fake_tensor.py::FakeTensorDispatchCache::test_cache_view_op, test/test_fake_tensor.py::FakeTensorDispatchCache::test_fft_hfft2_issue145522, test/test_fake_tensor.py::FakeTensorDispatchCache::test_from_buffer, test/test_fake_tensor.py::FakeTensorDispatchCache::test_inference_mode, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph, test/test_fake_tensor.py::FakeTensorDispatchCache::test_invoke_subgraph_cacheable_inplace, test/test_fake_tensor.py::FakeTensorDispatchCache::test_meta_tensor_to_fake_cpu, test/test_fake_tensor.py::FakeTensorDispatchCache::test_shape_env_settings, test/test_fake_tensor.py::FakeTensorDispatchCache::test_unbacked_output, test/test_fake_tensor.py::FakeTensorDispatchCache::test_wrapper_tensor_subclass_different_device, test/test_fake_tensor.py::FakeTensorPreferDeviceType::test_fake_tensor_prefer_device_type, test/test_fake_tensor.py::FakeTensorPreferDeviceType::test_fake_tensor_prefer_device_type_cpu_only 2025-08-26T20:06:49.9750718Z 2025-08-26T20:06:49.9750934Z Running test_python_dispatch 1/1 ... [2025-08-26 20:06:49.951833] 2025-08-26T20:06:49.9751373Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:06:49.9752464Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_python_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:06:49.952148] 2025-08-26T20:06:55.1230309Z 2025-08-26T20:06:55.1231313Z test_python_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_python_dispatch_1.1_8c9d022405436a14_.log 2025-08-26T20:06:55.1278831Z Running 118 items in this shard: test/test_python_dispatch.py::TestDispatcherPythonBindings::test_call_boxed, test/test_python_dispatch.py::TestPythonRegistration::test_alias_analysis, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library_fragment_no_existing, test/test_python_dispatch.py::TestPythonRegistration::test_create_new_library_fragment_with_existing, test/test_python_dispatch.py::TestPythonRegistration::test_dispatchkeyset_eq, test/test_python_dispatch.py::TestPythonRegistration::test_dispatchkeyset_pickle, test/test_python_dispatch.py::TestPythonRegistration::test_error_for_unsupported_ns_or_kind, test/test_python_dispatch.py::TestPythonRegistration::test_error_if_fn_not_callable, test/test_python_dispatch.py::TestPythonRegistration::test_extend_library_with_dispatch_key_arg, test/test_python_dispatch.py::TestPythonRegistration::test_fallback, test/test_python_dispatch.py::TestPythonRegistration::test_fallback_fallthrough, test/test_python_dispatch.py::TestPythonRegistration::test_fallback_keyset, test/test_python_dispatch.py::TestPythonRegistration::test_fallthrough_for_dense_key_with_meta_in_tls, test/test_python_dispatch.py::TestPythonRegistration::test_finalizer, test/test_python_dispatch.py::TestPythonRegistration::test_override_aten_ops_with_multiple_libraries, test/test_python_dispatch.py::TestPythonRegistration::test_override_cpu_sum, test/test_python_dispatch.py::TestPythonRegistration::test_override_cuda_with_jiterator, test/test_python_dispatch.py::TestPythonRegistration::test_register_fallthrough, test/test_python_dispatch.py::TestPythonRegistration::test_returning_symint, test/test_python_dispatch.py::TestPythonDispatch::test_all_same_mode, test/test_python_dispatch.py::TestPythonDispatch::test_autograd_in_attr, test/test_python_dispatch.py::TestPythonDispatch::test_basic, test/test_python_dispatch.py::TestPythonDispatch::test_capture_logs_with_torch_dispatch_mode, test/test_python_dispatch.py::TestPythonDispatch::test_construct_int_tensor, test/test_python_dispatch.py::TestPythonDispatch::test_custom_autograd, test/test_python_dispatch.py::TestPythonDispatch::test_custom_dispatch_mode_not_supports_higher_order_operators, test/test_python_dispatch.py::TestPythonDispatch::test_custom_dispatch_mode_supports_higher_order_operators, test/test_python_dispatch.py::TestPythonDispatch::test_custom_size_policy_dynamic_shapes, test/test_python_dispatch.py::TestPythonDispatch::test_data_ptr_respects_numel_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_non_wrapper_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_wrapper_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_deepcopy_wrapper_subclass_with_clone_returning_different_type, test/test_python_dispatch.py::TestPythonDispatch::test_detach_appears_twice_when_called_once, test/test_python_dispatch.py::TestPythonDispatch::test_device_slowpath, test/test_python_dispatch.py::TestPythonDispatch::test_dim_slowpath, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_call, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_call_list_arg, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_super_dont_autograd, test/test_python_dispatch.py::TestPythonDispatch::test_dispatch_uint64, test/test_python_dispatch.py::TestPythonDispatch::test_error_using_class_method_on_mode, test/test_python_dispatch.py::TestPythonDispatch::test_exception_handling, test/test_python_dispatch.py::TestPythonDispatch::test_fancy_strides, test/test_python_dispatch.py::TestPythonDispatch::test_format, test/test_python_dispatch.py::TestPythonDispatch::test_get_cur_mode, test/test_python_dispatch.py::TestPythonDispatch::test_get_mode_stack, test/test_python_dispatch.py::TestPythonDispatch::test_index_put_where_only_index_is_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_invalid_ret, test/test_python_dispatch.py::TestPythonDispatch::test_is_contiguous_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_kwarg_only, test/test_python_dispatch.py::TestPythonDispatch::test_kwarg_only_and_positional_default, test/test_python_dispatch.py::TestPythonDispatch::test_layout_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_like, test/test_python_dispatch.py::TestPythonDispatch::test_list_ret, test/test_python_dispatch.py::TestPythonDispatch::test_make_fx_with_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_make_subclass_with_modes, test/test_python_dispatch.py::TestPythonDispatch::test_make_wrapper_subclass_noalloc, test/test_python_dispatch.py::TestPythonDispatch::test_make_wrapper_subclass_propagates_metadata, test/test_python_dispatch.py::TestPythonDispatch::test_maybe_tuple_bug, test/test_python_dispatch.py::TestPythonDispatch::test_mode_detection, test/test_python_dispatch.py::TestPythonDispatch::test_mode_with_make_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_multiple_ops_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_nested_push_logging_tensor_mode, test/test_python_dispatch.py::TestPythonDispatch::test_nesting_same_mode, test/test_python_dispatch.py::TestPythonDispatch::test_new_ones, test/test_python_dispatch.py::TestPythonDispatch::test_none_wrapping, test/test_python_dispatch.py::TestPythonDispatch::test_notimplemented_mode, test/test_python_dispatch.py::TestPythonDispatch::test_optional_tensor_list, test/test_python_dispatch.py::TestPythonDispatch::test_out, test/test_python_dispatch.py::TestPythonDispatch::test_produce_real_type, test/test_python_dispatch.py::TestPythonDispatch::test_record_stream, test/test_python_dispatch.py::TestPythonDispatch::test_return_and_correct_aliasing_gives_correct_stride, test/test_python_dispatch.py::TestPythonDispatch::test_return_stream, test/test_python_dispatch.py::TestPythonDispatch::test_set_data, test/test_python_dispatch.py::TestPythonDispatch::test_shallow_copy_and_detach, test/test_python_dispatch.py::TestPythonDispatch::test_sizes_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_standard_is_not_subclass, test/test_python_dispatch.py::TestPythonDispatch::test_storage, test/test_python_dispatch.py::TestPythonDispatch::test_storage_can_be_converted_to_python_object, test/test_python_dispatch.py::TestPythonDispatch::test_strides_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_subclass_creation, test/test_python_dispatch.py::TestPythonDispatch::test_subclass_priority, test/test_python_dispatch.py::TestPythonDispatch::test_sym_sizes_strides_slow_path, test/test_python_dispatch.py::TestPythonDispatch::test_tolist_numpy_with_torch_dispatch_mode, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_basic, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_respects_no_dispatch, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_subclass_priority, test/test_python_dispatch.py::TestPythonDispatch::test_torch_dispatch_mode_unrelated_tensors, test/test_python_dispatch.py::TestPythonDispatch::test_version, test/test_python_dispatch.py::TestPythonDispatch::test_view_returns_alias_under_torch_dispatch, test/test_python_dispatch.py::TestPythonDispatch::test_with_mode_created_separately, test/test_python_dispatch.py::TestPythonDispatch::test_with_nested_modes, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_extra_dispatch_keys, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_multiprocessing_preserves_dtype, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_reentrant_dispatch_with_mode, test/test_python_dispatch.py::TestPythonDispatch::test_wrapper_subclass_serializes, test/test_python_dispatch.py::TestPythonDispatcher::test_basic, test/test_python_dispatch.py::TestPythonDispatcher::test_lstsq, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_cat_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_conv2d_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyCatCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyCubeCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyMulCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyMulScalarCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyNMSCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyNonzeroCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySortCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySplitCopyCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpySplitCopyWithIntCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyTakeCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_custom_NumpyViewCopyCustomOp_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_fft_fft2_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_mul_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_native_batch_norm_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_out_op_cpu, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_split_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_split_list_args_cpu_float32, test/test_python_dispatch.py::TestWrapperSubclassAliasingCPU::test_wrapper_subclass_aliasing_view_cpu_float32 2025-08-26T20:06:55.1324472Z 2025-08-26T20:06:55.1324657Z Running test_autocast 1/1 ... [2025-08-26 20:06:55.123365] 2025-08-26T20:06:55.1325097Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:06:55.1326156Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_autocast.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:06:55.123654] 2025-08-26T20:06:58.9428532Z 2025-08-26T20:06:58.9429383Z test_autocast 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_autocast_1.1_5230431b8347b595_.log 2025-08-26T20:06:58.9436569Z Running 20 items in this shard: test/test_autocast.py::TestAutocastCPU::test_autocast_disabled_with_fp32_dtype, test/test_autocast.py::TestAutocastCPU::test_autocast_methods_expect_builtin_promote, test/test_autocast.py::TestAutocastCPU::test_autocast_nn_16, test/test_autocast.py::TestAutocastCPU::test_autocast_nn_fp32, test/test_autocast.py::TestAutocastCPU::test_autocast_rnn, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_16, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_expect_builtin_promote, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_fp32, test/test_autocast.py::TestAutocastCPU::test_autocast_torch_need_autocast_promote, test/test_autocast.py::TestAutocastCPU::test_cpu_autocast_deprecated_warning, test/test_autocast.py::TestAutocastCPU::test_generic_autocast, test/test_autocast.py::TestAutocastGPU::test_autocast_prioritize, test/test_autocast.py::TestAutocastGPU::test_cache_disabled, test/test_autocast.py::TestAutocastGPU::test_cast_cache_is_global, test/test_autocast.py::TestAutocastMPS::test_cast_cache_is_global, test/test_autocast.py::TestAutocastMPS::test_mps_autocast_bfloat16_supported, test/test_autocast.py::TestAutocastMPS::test_mps_autocast_error_message, test/test_autocast.py::TestTorchAutocast::test_autocast_fast_dtype, test/test_autocast.py::TestTorchAutocast::test_invalid_device, test/test_autocast.py::TestTorchAutocast::test_non_string_device 2025-08-26T20:06:58.9443583Z 2025-08-26T20:06:58.9443811Z Running test_jit_disabled 1/1 ... [2025-08-26 20:06:58.943094] 2025-08-26T20:06:58.9444233Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:06:58.9445428Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit_disabled.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:06:58.943413] 2025-08-26T20:07:02.3120647Z 2025-08-26T20:07:02.3121526Z test_jit_disabled 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_disabled_1.1_116c8d8f56b85712_.log 2025-08-26T20:07:02.3123108Z Running 3 items in this shard: test/test_jit_disabled.py::TestJitDisabled::test_attribute, test/test_jit_disabled.py::TestJitDisabled::test_recursive_script, test/test_jit_disabled.py::TestJitDisabled::test_script_module_construction 2025-08-26T20:07:02.3124274Z 2025-08-26T20:07:02.3124512Z Running test_dispatch 1/1 ... [2025-08-26 20:07:02.312304] 2025-08-26T20:07:02.3124906Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:07:02.3128278Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_dispatch.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:07:02.312622] 2025-08-26T20:07:29.5115600Z 2025-08-26T20:07:29.5116418Z test_dispatch 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_dispatch_1.1_e604c876e06248f0_.log 2025-08-26T20:07:29.5127328Z Running 32 items in this shard: test/test_dispatch.py::TestDispatch::test_all_invariants, test/test_dispatch.py::TestDispatch::test_computed_table, test/test_dispatch.py::TestDispatch::test_computed_table_with_ambiguous_autogradother, test/test_dispatch.py::TestDispatch::test_computed_table_with_autograd, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_math, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_autograd_math_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_defaultbackend, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_math, test/test_dispatch.py::TestDispatch::test_computed_table_with_cpu_math_autogradcpu_fallthrough, test/test_dispatch.py::TestDispatch::test_computed_table_with_math, test/test_dispatch.py::TestDispatch::test_def, test/test_dispatch.py::TestDispatch::test_def_impl_schema_mismatch, test/test_dispatch.py::TestDispatch::test_def_only, test/test_dispatch.py::TestDispatch::test_def_with_explicit_alias, test/test_dispatch.py::TestDispatch::test_def_with_inference, test/test_dispatch.py::TestDispatch::test_dispatch_print_registrations_for_dispatch_key_invalid, test/test_dispatch.py::TestDispatch::test_find_dangling_impls, test/test_dispatch.py::TestDispatch::test_find_dangling_impls_ext, test/test_dispatch.py::TestDispatch::test_impl_only, test/test_dispatch.py::TestDispatch::test_multiple_def_alias_defaulting, test/test_dispatch.py::TestDispatch::test_multiple_def_alias_mismatch, test/test_dispatch.py::TestDispatch::test_multiple_def_error, test/test_dispatch.py::TestDispatch::test_multiple_fallback, test/test_dispatch.py::TestDispatch::test_overwrite_math, test/test_dispatch.py::TestPythonDispatcher::test_autogradother, test/test_dispatch.py::TestPythonDispatcher::test_basic, test/test_dispatch.py::TestPythonDispatcher::test_defaultbackend_autogradcpu, test/test_dispatch.py::TestPythonDispatcher::test_defaultbackend_math, test/test_dispatch.py::TestPythonDispatcher::test_duplicate_registrations, test/test_dispatch.py::TestPythonDispatcher::test_math_autogradcpu, test/test_dispatch.py::TestPythonDispatcher::test_quantized_structured_not_implemented 2025-08-26T20:07:29.5137597Z 2025-08-26T20:07:29.5137800Z Running test_native_mha 1/1 ... [2025-08-26 20:07:29.511793] 2025-08-26T20:07:29.5138207Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:07:29.5146641Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_native_mha.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:07:29.512090] 2025-08-26T20:07:32.8809177Z 2025-08-26T20:07:32.8810660Z test_native_mha 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_native_mha_1.1_101419de7e78ad6d_.log 2025-08-26T20:07:32.8837867Z Running 28 items in this shard: test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_attention_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_encoder_decoder_attention_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_False_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_False_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_False_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_False_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_False_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_native_multihead_self_attention_use_nt_True_use_padding_True_pad_all_True_need_weights_False_average_attn_weights_True_fused_True_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_transform_bias_rescale_qkv_cpu_float32, test/test_native_mha.py::TestMHADeviceTypeCPU::test_transform_bias_rescale_qkv_nested_cpu_float32 2025-08-26T20:07:32.8859393Z 2025-08-26T20:07:32.8859619Z Running test_sort_and_select 1/1 ... [2025-08-26 20:07:32.881303] 2025-08-26T20:07:32.8860056Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:07:32.8861252Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sort_and_select.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:07:32.881733] 2025-08-26T20:07:38.0527742Z 2025-08-26T20:07:38.0529373Z test_sort_and_select 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sort_and_select_1.1_cff8ee9c768f0a07_.log 2025-08-26T20:07:38.0573871Z Running 113 items in this shard: test/test_sort_and_select.py::TestSortAndSelectCPU::test_complex_unsupported_cpu_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_devices_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_isin_different_dtypes_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_kthvalue_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_kthvalue_scalar_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_msort_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_output_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_1d_parallel_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_discontiguous_slow_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_expanded_tensor_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_large_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_large_slice_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_overflow_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_restride_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_sort_stable_none_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_against_numpy_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_stable_sort_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_1d_output_discontiguous_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_4d_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_arguments_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_integral_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_lower_precision_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_lower_precision_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_noncontiguous_gpu_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_nonfinite_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_quantized_scalar_input_cpu, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_topk_zero_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_consecutive_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_bfloat16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_bool, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_float64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int16, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int32, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int64, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_int8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_cpu_uint8, test/test_sort_and_select.py::TestSortAndSelectCPU::test_unique_dim_cpu 2025-08-26T20:07:38.0612076Z 2025-08-26T20:07:38.0612335Z Running test_cpp_extensions_jit 1/1 ... [2025-08-26 20:07:38.053305] 2025-08-26T20:07:38.0612768Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:07:38.0613844Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_jit.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:07:38.053720] 2025-08-26T20:08:14.3153148Z 2025-08-26T20:08:14.3154053Z test_cpp_extensions_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_jit_1.1_6851085f19d3ce3f_.log 2025-08-26T20:08:14.3168057Z Running 34 items in this shard: test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_aoti_torch_call_dispatcher, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_autograd_from_cpp, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_compilation_error_formatting, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_has_same_output_as_python, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_has_up_to_date_attributes, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_python_inter_op, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cpp_frontend_module_python_inter_op_with_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_arch_flags_default_gencode, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_arch_flags_non_default_gencode, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_cuda_pluggable_allocator_include, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_custom_compound_op_autograd, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_custom_functorch_error, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_gen_extension_h_pch, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_half_support, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_custom_op_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_cuda, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_multiple_sources_and_no_functions, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_throws_when_functions_is_bad, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_with_functions_as_dict, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_with_functions_as_list, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_inline_jit_compile_extension_xpu, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_compile_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cuda_archflags, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cuda_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_cudnn_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_xpu_archlists, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_jit_xpu_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_lenient_flag_handling_in_jit_extensions, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_load_with_non_platform_default_encoding, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_mps_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_reload_jit_extension, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_returns_shared_library_path_when_is_python_module_is_true, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_set_default_type_also_changes_aten_default_type, test/test_cpp_extensions_jit.py::TestCppExtensionJIT::test_warning 2025-08-26T20:08:14.3181828Z 2025-08-26T20:08:14.3182020Z Running nn/test_pooling 1/1 ... [2025-08-26 20:08:14.315606] 2025-08-26T20:08:14.3182439Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:08:14.3183508Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_pooling.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:08:14.315908] 2025-08-26T20:08:41.7753674Z 2025-08-26T20:08:41.7754654Z nn/test_pooling 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_pooling_1.1_089fb7dae72fa7ce_.log 2025-08-26T20:08:41.7799196Z Running 111 items in this shard: test/nn/test_pooling.py::TestAvgPool::test_avg_pool1d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_avg_pool2d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_avg_pool3d_ceil_mode, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool2d, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool2d_with_divisor, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool3d, test/nn/test_pooling.py::TestAvgPool::test_doubletensor_avg_pool3d_with_divisor, test/nn/test_pooling.py::TestPoolingNN::test_MaxUnpool2d_output_size, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_avg_pooling_nhwc_overflow, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_avg_pooling_overflow, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_launch_config_backward, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_launch_config_forward, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_avg_nhwc_non_contiguous, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_lower_precision, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_size_none, test/nn/test_pooling.py::TestPoolingNN::test_adaptive_pooling_size_overflow, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool2d_nhwc_cpu, test/nn/test_pooling.py::TestPoolingNN::test_max_unpool3d_input_check, test/nn/test_pooling.py::TestPoolingNN::test_quantized_max_pool1d_empty_kernel, test/nn/test_pooling.py::TestPoolingNN::test_quantized_max_pool3d, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool1d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool2d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool3d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AdaptiveMaxPool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AvgPool2d_empty_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_AvgPool3d_backward_after_cat_dim1_device_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_batch_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_out_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool2d_zero_samples_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_errors_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_batch_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_out_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_FractionalMaxPool3d_zero_samples_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool1d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool2d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool3d_indices_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxPool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case10_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case1_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case2_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case3_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case4_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case5_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case6_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case7_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case8_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_index_errors_case9_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_MaxUnpool_zero_batch_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pool2d_output_size_one_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pool3d_output_size_one_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_avg_pooling_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_max_pooling_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pool_odd_size_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_empty_output_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_empty_output_size_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_max_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_max_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_int8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_no_suppot_input_cpu_uint8, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_zero_batch_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_adaptive_pooling_zero_batch_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_reduced_floating_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_avg_pool2d_reduced_floating_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool2d_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool2d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool3d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_fractional_max_pool_nan_inf_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_corner_cases_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_corner_cases_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool1d_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_corner_cases_cpu_int32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_corner_cases_cpu_int64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_indices_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool2d_with_indices_backward_fails_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool3d_ndhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_bfloat16_half_cpu_bfloat16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_bfloat16_half_cpu_float16, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_max_pool_nan_inf_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_maxpool3d_non_square_backward_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_maxpool_indices_no_batch_dim_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool3d_large_size_int64_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool3d_size_one_feature_dim_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool_invalid_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pool_large_size_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_bfloat16_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_large_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_max_nhwc_cpu_float32, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_max_nhwc_cpu_float64, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_avg_pooling_dims_1_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_avg_pooling_dims_2_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_avg_pooling_dims_3_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_max_pooling_dims_1_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_max_pooling_dims_2_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_shape_kernel_max_pooling_dims_3_cpu, test/nn/test_pooling.py::TestPoolingNNDeviceTypeCPU::test_pooling_zero_stride_cpu 2025-08-26T20:08:41.7843467Z 2025-08-26T20:08:41.7843688Z Running nn/test_convolution 1/1 ... [2025-08-26 20:08:41.775748] 2025-08-26T20:08:41.7844128Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:08:41.7845283Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_convolution.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:08:41.776060] 2025-08-26T20:09:04.0224159Z 2025-08-26T20:09:04.0225267Z nn/test_convolution 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_convolution_1.1_1a4a21bcd989f722_.log 2025-08-26T20:09:04.0580466Z Running 598 items in this shard: test/nn/test_convolution.py::TestConvolutionNN::test_Conv1d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_1x1, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_OneDNN, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_backward_twice, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_groups_nobias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_groups_nobias_v2, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types_on_GPU_with_cudnn, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_inconsistent_types_on_GPU_without_cudnn, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_missing_argument, test/nn/test_convolution.py::TestConvolutionNN::test_Conv2d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_groups_nobias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_groups_wbias, test/nn/test_convolution.py::TestConvolutionNN::test_Conv3d_module_same_padding, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_half_cublas_gemm, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_output_size, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose2d_output_size_downsample_upsample, test/nn/test_convolution.py::TestConvolutionNN::test_ConvTranspose3d_correct_output_size, test/nn/test_convolution.py::TestConvolutionNN::test_conv1d_issue_120547, test/nn/test_convolution.py::TestConvolutionNN::test_conv2d_discontiguous_weight, test/nn/test_convolution.py::TestConvolutionNN::test_conv3d_issue_120406, test/nn/test_convolution.py::TestConvolutionNN::test_conv_backcompat, test/nn/test_convolution.py::TestConvolutionNN::test_conv_cudnn_memory_layout_dominance, test/nn/test_convolution.py::TestConvolutionNN::test_conv_invalid_groups, test/nn/test_convolution.py::TestConvolutionNN::test_conv_modules_raise_error_on_incorrect_input_size, test/nn/test_convolution.py::TestConvolutionNN::test_conv_padding_mode, test/nn/test_convolution.py::TestConvolutionNN::test_conv_shapecheck, test/nn/test_convolution.py::TestConvolutionNN::test_conv_tbc, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_non_contiguous, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_noncontiguous_weight, test/nn/test_convolution.py::TestConvolutionNN::test_cudnn_not_mutate_stride, test/nn/test_convolution.py::TestConvolutionNN::test_functional_grad_conv, test/nn/test_convolution.py::TestConvolutionNN::test_functional_grad_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv1d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv1d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv2d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv2d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv3d_input, test/nn/test_convolution.py::TestConvolutionNN::test_grad_conv3d_weight, test/nn/test_convolution.py::TestConvolutionNN::test_grouped_conv_cudnn_nhwc_support, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv1d, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_invalid_conv3d, test/nn/test_convolution.py::TestConvolutionNN::test_mismatch_shape_conv2d, test/nn/test_convolution.py::TestConvolutionNN::test_nnpack_conv, test/nn/test_convolution.py::TestConvolutionNN::test_permute_conv2d_issue_120211, test/nn/test_convolution.py::TestConvolutionNN::test_thnn_conv_strided_padded_dilated, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_backward_depthwise_cpu_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_backward_depthwise_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_depthwise_naive_groups_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_depthwise_naive_groups_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_depthwise_naive_groups_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_1_cpu_complex128, 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test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_2_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_complex128, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_deterministic_cudnn_dilation_3_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_large_workspace_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_large_workspace_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_large_workspace_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_naive_groups_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv2d_size_1_kernel_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv3d_depthwise_naive_groups_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv3d_depthwise_naive_groups_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_Conv3d_depthwise_naive_groups_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose2d_large_output_padding_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose2d_large_output_padding_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose2d_size_1_kernel_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_ConvTranspose3d_size_1_kernel_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_contig_wrong_stride_cudnn_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_backward_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_backward_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_same_padding_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_valid_padding_backward_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_valid_padding_backward_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv1d_valid_padding_cpu_complex64, 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test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_has_bias_True_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_has_bias_True_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_has_bias_True_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_False_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_False_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_False_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_False_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_True_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_True_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_True_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow2d_transposed_has_bias_True_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_False_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_False_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_False_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_False_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_True_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_True_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_True_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cpu_has_bias_True_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_False_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_False_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_False_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_False_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_True_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_True_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_True_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_cuda_has_bias_True_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_False_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_False_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_False_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_False_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_True_strided_False_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_True_strided_False_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_True_strided_True_contiguous_False_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_backend_slow3d_dilated_has_bias_True_strided_True_contiguous_True_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_contiguous_for_oneDNN_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_mismatch_memory_format_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_ndhwc_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_ndhwc_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_nhwc_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_nhwc_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_nhwc_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_nhwc_support_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_cudnn_nhwc_support_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_groups_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_no_bias_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_stride_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_double_backward_strided_with_3D_input_and_weight_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_empty_channel_cpu_complex64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_empty_channel_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_ic1_channels_last_for_oneDNN_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_batch_1_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_large_nosplit_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_noncontig_weights_and_bias_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_noncontig_weights_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_thnn_nhwc_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_thnn_nhwc_cpu_float64, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transpose_with_output_size_and_no_batch_dim_ConvTranspose2d_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transpose_with_output_size_and_no_batch_dim_ConvTranspose3d_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_conv_transposed_large_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_convert_conv2d_weight_memory_format_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_convert_conv3d_weight_memory_format_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_add_relu_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_add_relu_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_relu_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_cudnn_convolution_relu_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_depthwise_conv_64bit_indexing_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_group_convTranspose_empty_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_group_conv_empty_cpu, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float16, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float32, test/nn/test_convolution.py::TestConvolutionNNDeviceTypeCPU::test_noncontig_conv_grad_cpu_float64 2025-08-26T20:09:04.0939164Z 2025-08-26T20:09:04.0939427Z Running test_multiprocessing_spawn 1/1 ... [2025-08-26 20:09:04.023675] 2025-08-26T20:09:04.0939918Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:09:04.0941057Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_multiprocessing_spawn.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:09:04.024017] 2025-08-26T20:11:21.8743930Z 2025-08-26T20:11:21.8744880Z test_multiprocessing_spawn 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_multiprocessing_spawn_1.1_cdd55f052873e0ec_.log 2025-08-26T20:11:21.8756684Z Running 31 items in this shard: test/test_multiprocessing_spawn.py::SpawnTest::test_exception_all, test/test_multiprocessing_spawn.py::SpawnTest::test_exception_raises, test/test_multiprocessing_spawn.py::SpawnTest::test_exception_single, test/test_multiprocessing_spawn.py::SpawnTest::test_first_argument_index, test/test_multiprocessing_spawn.py::SpawnTest::test_signal_raises, test/test_multiprocessing_spawn.py::SpawnTest::test_success, test/test_multiprocessing_spawn.py::SpawnTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::SpawnTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_exit_grace_period_20, test/test_multiprocessing_spawn.py::SpawnTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ForkTest::test_exception_all, test/test_multiprocessing_spawn.py::ForkTest::test_exception_single, test/test_multiprocessing_spawn.py::ForkTest::test_first_argument_index, test/test_multiprocessing_spawn.py::ForkTest::test_success, test/test_multiprocessing_spawn.py::ForkTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::ForkTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_exit_grace_period_20, test/test_multiprocessing_spawn.py::ForkTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_exception_all, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_exception_single, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_first_argument_index, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success_first_then_exception, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_success_non_blocking, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_exit_grace_period0, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_exit_grace_period_20, test/test_multiprocessing_spawn.py::ParallelForkServerShouldWorkTest::test_terminate_signal, test/test_multiprocessing_spawn.py::ParallelForkServerPerfTest::test_forkserver_perf, test/test_multiprocessing_spawn.py::ErrorTest::test_errors_pickleable 2025-08-26T20:11:21.8768234Z 2025-08-26T20:11:22.3926179Z Uploading artifacts took 0.52 seconds 2025-08-26T20:11:22.3929038Z Running test_cuda_primary_ctx 1/1 ... [2025-08-26 20:11:22.392735] 2025-08-26T20:11:22.3929485Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:11:22.3932809Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_primary_ctx.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:11:22.393077] 2025-08-26T20:11:25.3682079Z 2025-08-26T20:11:25.3683132Z test_cuda_primary_ctx 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_primary_ctx_1.1_74ce7530da60b9df_.log 2025-08-26T20:11:25.3684089Z Running 0 items in this shard: 2025-08-26T20:11:25.3684444Z 2025-08-26T20:11:25.3687037Z Running test_mobile_optimizer 1/1 ... [2025-08-26 20:11:25.368506] 2025-08-26T20:11:25.3687673Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:11:25.3690743Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mobile_optimizer.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:11:25.368831] 2025-08-26T20:11:30.6400517Z 2025-08-26T20:11:30.6401337Z test_mobile_optimizer 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mobile_optimizer_1.1_42269a36feb538c2_.log 2025-08-26T20:11:30.6404599Z Running 7 items in this shard: test/test_mobile_optimizer.py::TestOptimizer::test_clone_module_with_class, test/test_mobile_optimizer.py::TestOptimizer::test_generate_mobile_module_lints, test/test_mobile_optimizer.py::TestOptimizer::test_hoist_conv_packed_params, test/test_mobile_optimizer.py::TestOptimizer::test_mobilenet_optimize_for_mobile, test/test_mobile_optimizer.py::TestOptimizer::test_optimize_for_mobile, test/test_mobile_optimizer.py::TestOptimizer::test_preserve_bundled_inputs_methods, test/test_mobile_optimizer.py::TestOptimizer::test_quantized_conv_no_asan_failures 2025-08-26T20:11:30.6407246Z 2025-08-26T20:11:30.6407438Z Running test_cuda_trace 1/1 ... [2025-08-26 20:11:30.640246] 2025-08-26T20:11:30.6408083Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:11:30.6409339Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_trace.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:11:30.640536] 2025-08-26T20:11:33.6437855Z 2025-08-26T20:11:33.6438867Z test_cuda_trace 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_trace_1.1_ad98ef44ea9590ce_.log 2025-08-26T20:11:33.6439630Z Running 0 items in this shard: 2025-08-26T20:11:33.6439824Z 2025-08-26T20:11:33.6441385Z Running test_cuda_nvml_based_avail 1/1 ... [2025-08-26 20:11:33.643995] 2025-08-26T20:11:33.6441839Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:11:33.6444871Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_nvml_based_avail.py', '--shard-id=1', '--num-shards=1', '-v', '--subprocess', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:11:33.644293] 2025-08-26T20:11:36.5905211Z 2025-08-26T20:11:36.5906054Z test_cuda_nvml_based_avail 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_nvml_based_avail_1.1_56f0f8902578c3fa_.log 2025-08-26T20:11:36.5907081Z Running 0 items in this shard: 2025-08-26T20:11:36.5907275Z 2025-08-26T20:11:36.5908932Z Running test_spectral_ops 1/1 ... [2025-08-26 20:11:36.590747] 2025-08-26T20:11:36.5909337Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:11:36.5912169Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_spectral_ops.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:11:36.591029] 2025-08-26T20:11:46.5222965Z 2025-08-26T20:11:46.5223775Z test_spectral_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_spectral_ops_1.1_c6a087e458c51e5b_.log 2025-08-26T20:11:46.5317914Z Running 281 items in this shard: test/test_spectral_ops.py::TestFFTCPU::test_batch_istft_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_istft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_definition_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_onesided_cpu, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_real_equiv_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_complex_stft_roundtrip_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_cufft_context_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_cufft_plan_cache_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_fftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_hfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ifftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ihfft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ihfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_ihfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_irfft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_irfft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_irfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_irfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_irfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_irfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_rfft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_rfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft__refs_fft_rfftn_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft_fft_fft2_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft_fft_fft2_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft_fft_fft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_empty_fft_fft_fft_cpu_float32, 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test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_hfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_hfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_ifft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_ifft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_ihfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_irfft_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_irfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_1d_fft_rfft_cpu_float32, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_fftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_hfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_ifftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_ifftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_irfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd__refs_fft_irfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_fftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_fftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_hfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_hfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_ifftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_ifftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_irfftn_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_reference_nd_fft_irfftn_cpu_complex64, test/test_spectral_ops.py::TestFFTCPU::test_stft_align_to_window_only_requires_non_center_cpu, test/test_spectral_ops.py::TestFFTCPU::test_stft_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_stft_requires_complex_cpu, test/test_spectral_ops.py::TestFFTCPU::test_stft_requires_window_cpu, test/test_spectral_ops.py::TestFFTCPU::test_stft_roundtrip_complex_window_cpu_complex128, test/test_spectral_ops.py::TestFFTCPU::test_stft_roundtrip_complex_window_cpu_float64, test/test_spectral_ops.py::TestFFTCPU::test_stft_window_device_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fftfreq_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fftn_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_fftshift_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_hfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifftn_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ifftshift_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_ihfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_irfft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_irfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_irfftn_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfft2_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfft_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfftfreq_cpu, test/test_spectral_ops.py::TestFFTDocExamplesCPU::test_rfftn_cpu 2025-08-26T20:11:46.5411045Z 2025-08-26T20:11:46.5411311Z Running distributions/test_distributions 1/1 ... [2025-08-26 20:11:46.522912] 2025-08-26T20:11:46.5411943Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:11:46.5413086Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'distributions/test_distributions.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:11:46.523230] 2025-08-26T20:12:30.3491509Z 2025-08-26T20:12:30.3492558Z distributions/test_distributions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/distributions.test_distributions_1.1_356d027b5fcf195f_.log 2025-08-26T20:12:30.3586565Z Running 230 items in this shard: test/distributions/test_distributions.py::TestDistributions::test_argmax_relaxed_categorical, test/distributions/test_distributions.py::TestDistributions::test_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_bernoulli_3d, test/distributions/test_distributions.py::TestDistributions::test_bernoulli_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_beta_log_prob, test/distributions/test_distributions.py::TestDistributions::test_beta_sample, test/distributions/test_distributions.py::TestDistributions::test_beta_shape, test/distributions/test_distributions.py::TestDistributions::test_beta_underflow, test/distributions/test_distributions.py::TestDistributions::test_beta_underflow_gpu, test/distributions/test_distributions.py::TestDistributions::test_binomial, test/distributions/test_distributions.py::TestDistributions::test_binomial_bfloat16, test/distributions/test_distributions.py::TestDistributions::test_binomial_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_binomial_extreme_vals, test/distributions/test_distributions.py::TestDistributions::test_binomial_half, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_and_entropy, test/distributions/test_distributions.py::TestDistributions::test_binomial_log_prob_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_binomial_sample, test/distributions/test_distributions.py::TestDistributions::test_binomial_stable, test/distributions/test_distributions.py::TestDistributions::test_binomial_vectorized_count, test/distributions/test_distributions.py::TestDistributions::test_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_categorical_enumerate_support, test/distributions/test_distributions.py::TestDistributions::test_cauchy, test/distributions/test_distributions.py::TestDistributions::test_cdf_icdf_inverse, test/distributions/test_distributions.py::TestDistributions::test_cdf_log_prob, test/distributions/test_distributions.py::TestDistributions::test_chi2_sample, test/distributions/test_distributions.py::TestDistributions::test_chi2_shape, test/distributions/test_distributions.py::TestDistributions::test_continuous_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_continuous_bernoulli_3d, test/distributions/test_distributions.py::TestDistributions::test_dirichlet_log_prob, 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test/distributions/test_distributions.py::TestDistributions::test_poisson_forward_ad, test/distributions/test_distributions.py::TestDistributions::test_poisson_gpu_sample, test/distributions/test_distributions.py::TestDistributions::test_poisson_log_prob, test/distributions/test_distributions.py::TestDistributions::test_poisson_sample, test/distributions/test_distributions.py::TestDistributions::test_poisson_shape, test/distributions/test_distributions.py::TestDistributions::test_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_1d, test/distributions/test_distributions.py::TestDistributions::test_relaxed_one_hot_categorical_2d, test/distributions/test_distributions.py::TestDistributions::test_repr, test/distributions/test_distributions.py::TestDistributions::test_rounded_relaxed_bernoulli, test/distributions/test_distributions.py::TestDistributions::test_rsample_requires_grad, 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test/distributions/test_distributions.py::TestKL::test_kl_lowrank_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_monte_carlo, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal_batched, test/distributions/test_distributions.py::TestKL::test_kl_multivariate_normal_batched_broadcasted, test/distributions/test_distributions.py::TestKL::test_kl_shape, test/distributions/test_distributions.py::TestKL::test_kl_transformed, test/distributions/test_distributions.py::TestConstraints::test_params_constraints, test/distributions/test_distributions.py::TestConstraints::test_support_constraints, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_gradient, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_overflow, test/distributions/test_distributions.py::TestNumericalStability::test_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob, test/distributions/test_distributions.py::TestNumericalStability::test_categorical_log_prob_with_logits, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_gradient, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_with_logits_overflow, test/distributions/test_distributions.py::TestNumericalStability::test_continuous_bernoulli_with_logits_underflow, test/distributions/test_distributions.py::TestNumericalStability::test_multinomial_log_prob, test/distributions/test_distributions.py::TestNumericalStability::test_multinomial_log_prob_with_logits, test/distributions/test_distributions.py::TestLazyLogitsInitialization::test_lazy_logits_initialization, test/distributions/test_distributions.py::TestLazyLogitsInitialization::test_lazy_probs_initialization, test/distributions/test_distributions.py::TestAgainstScipy::test_cdf, test/distributions/test_distributions.py::TestAgainstScipy::test_icdf, test/distributions/test_distributions.py::TestAgainstScipy::test_mean, test/distributions/test_distributions.py::TestAgainstScipy::test_variance_stddev, test/distributions/test_distributions.py::TestFunctors::test_cat_event_dim, test/distributions/test_distributions.py::TestFunctors::test_cat_transform, test/distributions/test_distributions.py::TestFunctors::test_cat_transform_non_uniform, test/distributions/test_distributions.py::TestFunctors::test_stack_transform, test/distributions/test_distributions.py::TestValidation::test_invalid, test/distributions/test_distributions.py::TestValidation::test_invalid_log_probs_arg, test/distributions/test_distributions.py::TestValidation::test_valid, test/distributions/test_distributions.py::TestValidation::test_warning_unimplemented_constraints, test/distributions/test_distributions.py::TestJit::test_cdf, test/distributions/test_distributions.py::TestJit::test_entropy, test/distributions/test_distributions.py::TestJit::test_enumerate_support, test/distributions/test_distributions.py::TestJit::test_log_prob, test/distributions/test_distributions.py::TestJit::test_mean, test/distributions/test_distributions.py::TestJit::test_rsample, test/distributions/test_distributions.py::TestJit::test_sample, test/distributions/test_distributions.py::TestJit::test_variance 2025-08-26T20:12:30.3679577Z 2025-08-26T20:12:30.3679841Z Running test_cpp_extensions_aot_no_ninja 1/1 ... [2025-08-26 20:12:30.349945] 2025-08-26T20:12:32.6468117Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:12:32.6469709Z import pkg_resources 2025-08-26T20:12:32.7113545Z running install 2025-08-26T20:12:32.7115798Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:12:32.7116627Z !! 2025-08-26T20:12:32.7116761Z 2025-08-26T20:12:32.7116897Z ******************************************************************************** 2025-08-26T20:12:32.7117297Z Please avoid running ``setup.py`` directly. 2025-08-26T20:12:32.7117719Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:12:32.7118102Z standards-based tools. 2025-08-26T20:12:32.7118294Z 2025-08-26T20:12:32.7118546Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:12:32.7119042Z or your builds will no longer be supported. 2025-08-26T20:12:32.7119301Z 2025-08-26T20:12:32.7119610Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:12:32.7120155Z ******************************************************************************** 2025-08-26T20:12:32.7120405Z 2025-08-26T20:12:32.7120499Z !! 2025-08-26T20:12:32.7120728Z self.initialize_options() 2025-08-26T20:12:32.7250016Z running build 2025-08-26T20:12:32.7250284Z running build_py 2025-08-26T20:12:32.7334782Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:12:32.7337111Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:12:32.7346154Z running build_ext 2025-08-26T20:12:32.7360653Z building 'torch_test_cpp_extension.cpp' extension 2025-08-26T20:12:32.7362435Z creating build/temp.linux-x86_64-cpython-313 2025-08-26T20:12:32.7366893Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c extension.cpp -o build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cpp -std=c++17 2025-08-26T20:12:34.0800989Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/Exceptions.h:12, 2025-08-26T20:12:34.0802056Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/python.h:11, 2025-08-26T20:12:34.0803119Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:9, 2025-08-26T20:12:34.0803698Z from extension.cpp:1: 2025-08-26T20:12:34.0806703Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘class pybind11::class_’: 2025-08-26T20:12:34.0807607Z extension.cpp:45:53: required from here 2025-08-26T20:12:34.0809432Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:2041:7: warning: ‘pybind11::class_’ declared with greater visibility than its base ‘pybind11::detail::generic_type’ [-Wattributes] 2025-08-26T20:12:34.0810778Z 2041 | class class_ : public detail::generic_type { 2025-08-26T20:12:34.0811122Z | ^~~~~~ 2025-08-26T20:12:34.0812794Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘pybind11::class_< , >::class_(pybind11::handle, const char*, const Extra& ...) [with Extra = {}; type_ = MatrixMultiplier; options = {}]’: 2025-08-26T20:12:34.0814217Z extension.cpp:45:53: required from here 2025-08-26T20:12:34.0816602Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:2139:28: warning: ‘pybind11::class_::class_<>(pybind11::handle, const char*)::’ declared with greater visibility than the type of its field ‘pybind11::class_::class_<>(pybind11::handle, const char*)::::’ [-Wattributes] 2025-08-26T20:12:34.0818593Z 2139 | with_internals([&](internals &internals) { 2025-08-26T20:12:34.0818993Z | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:34.0819515Z 2140 | auto &instances = record.module_local ? get_local_internals().registered_types_cpp 2025-08-26T20:12:34.0820111Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:34.0820581Z 2141 | : internals.registered_types_cpp; 2025-08-26T20:12:34.0821004Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:34.0821441Z 2142 | instances[std::type_index(typeid(type_alias))] 2025-08-26T20:12:34.0821852Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:34.0822263Z 2143 | = instances[std::type_index(typeid(type))]; 2025-08-26T20:12:34.0822672Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:34.0823008Z 2144 | }); 2025-08-26T20:12:34.0823253Z | ~ 2025-08-26T20:12:34.0826671Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:12:34.6514110Z building 'torch_test_cpp_extension.maia' extension 2025-08-26T20:12:34.6517609Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c maia_extension.cpp -o build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=maia -std=c++17 2025-08-26T20:12:35.7963126Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:12:36.3618715Z building 'torch_test_cpp_extension.rng' extension 2025-08-26T20:12:36.3622284Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c rng_extension.cpp -o build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=rng -std=c++17 2025-08-26T20:12:37.8253987Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:12:37.8255083Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:12:37.8256467Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:12:37.8258112Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:12:37.8259115Z from rng_extension.cpp:6: 2025-08-26T20:12:37.8260798Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1478: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:37.8262130Z 1478 | #pragma unroll 2025-08-26T20:12:37.8262488Z | 2025-08-26T20:12:37.8263275Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_convert.h:4, 2025-08-26T20:12:37.8264651Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1530, 2025-08-26T20:12:37.8266428Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:12:37.8267861Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:12:37.8269253Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:12:37.8270931Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:12:37.8272234Z from rng_extension.cpp:6: 2025-08-26T20:12:37.8273702Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:59: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:37.8274611Z 59 | #pragma unroll 2025-08-26T20:12:37.8274962Z | 2025-08-26T20:12:37.8276141Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:72: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:37.8276960Z 72 | #pragma unroll 2025-08-26T20:12:37.8277216Z | 2025-08-26T20:12:37.8278060Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:87: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:37.8278844Z 87 | #pragma unroll 2025-08-26T20:12:37.8279171Z | 2025-08-26T20:12:37.8279725Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1531, 2025-08-26T20:12:37.8280665Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:12:37.8281496Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:12:37.8282301Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:12:37.8283234Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:12:37.8283997Z from rng_extension.cpp:6: 2025-08-26T20:12:37.8284998Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_mask.h:160: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:37.8285825Z 160 | #pragma unroll 2025-08-26T20:12:37.8286063Z | 2025-08-26T20:12:37.8286584Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8287458Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8288289Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8289184Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8289936Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8290796Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8291740Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8292658Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8293564Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8294510Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8295487Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8296405Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8296972Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8298061Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8299705Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8301509Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8303351Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8305298Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8307442Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8313869Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8324730Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8330995Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8331951Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8332382Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8339563Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8346416Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8348161Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8348876Z | ^~~~~~~~ 2025-08-26T20:12:37.8349635Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8350660Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8351558Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8352398Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8353183Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8354041Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8355126Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8356280Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8357450Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8358594Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8359759Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8360729Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8361594Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8362150Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8363119Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8363884Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8364241Z | ^~~~ 2025-08-26T20:12:37.8364872Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8365748Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8366578Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8367383Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8368177Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8369102Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8370050Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8370959Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8371865Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8372825Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8373804Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8374649Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8375216Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8376256Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8377871Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8379635Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8381438Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8383379Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8385463Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8391523Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8401575Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8407384Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8408339Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8408798Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8414824Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8421218Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8422527Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8422953Z | ^~~~~~~~ 2025-08-26T20:12:37.8423608Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8424634Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8425571Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8426408Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8427190Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8428032Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8429140Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8430309Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8431479Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8432620Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8433636Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8434601Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8435464Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8436027Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8436877Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8437848Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8438204Z | ^~~~ 2025-08-26T20:12:37.8438799Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8439801Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8440612Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8441383Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8442126Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8442960Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8443872Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8444759Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8445704Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8446663Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8447611Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8448490Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8449120Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8450140Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8451815Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8453542Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8455300Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8457385Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8459457Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8465755Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8476448Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8482553Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8483508Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8483930Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8490398Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8497150Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8498464Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8498893Z | ^~~~~~~~ 2025-08-26T20:12:37.8499524Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8500551Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8501464Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8502296Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8503078Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8503921Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8505000Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8506161Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8507366Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8508505Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8509534Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8510513Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8511376Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8511945Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8512826Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8513593Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8513933Z | ^~~~ 2025-08-26T20:12:37.8514522Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8515397Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8516257Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8517065Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8517816Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8518673Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8519616Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8520527Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8521433Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8522379Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8523359Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8524221Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8524786Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8525795Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8527400Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8529212Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8531029Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8532960Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8535066Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8541634Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8552322Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8558418Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8559369Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8559748Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8566135Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8572973Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8574321Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8574736Z | ^~~~~~~~ 2025-08-26T20:12:37.8575374Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8576396Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8577332Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8578170Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8578937Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8579794Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8580878Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8582047Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8583219Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8584366Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8585384Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8586345Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8587209Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8587774Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8588621Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8589364Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8589718Z | ^~~~ 2025-08-26T20:12:37.8590308Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8591186Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8592003Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8592809Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8593574Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8594477Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8595421Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8596334Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8597256Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8598215Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8599228Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8600092Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8600665Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8601663Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8603304Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8605071Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8606892Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8608886Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8610975Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8617279Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8628000Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8634085Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8635054Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8635450Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8641997Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8648673Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8650032Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8650454Z | ^~~~~~~~ 2025-08-26T20:12:37.8651094Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8652122Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8653028Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8653851Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8654642Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8655574Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8656656Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8657825Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8659020Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8660171Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8661233Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8662198Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8663056Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8663625Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8664507Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8665266Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8665619Z | ^~~~ 2025-08-26T20:12:37.8666206Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8667074Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8667908Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8668716Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8669477Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8670334Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8671274Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8672175Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8673077Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8674033Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8675015Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8675876Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8676429Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8677437Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8679037Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8680793Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8682626Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8684578Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8686652Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8692739Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8702811Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8708580Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8709531Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8709923Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8715986Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8722405Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8723718Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8724142Z | ^~~~~~~~ 2025-08-26T20:12:37.8724781Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8725823Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8726739Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8727573Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8728354Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8729275Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8730343Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8731512Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8732683Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8733822Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8734857Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8735821Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8736665Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8737230Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8738283Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8739166Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8739512Z | ^~~~ 2025-08-26T20:12:37.8740077Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8740938Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8741750Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8742617Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8743369Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8744413Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8745370Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8746257Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8747182Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8748120Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8749066Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8749904Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8750491Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8751488Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8753042Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8754751Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8756514Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8758389Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8760554Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8766510Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8776703Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8782472Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8783454Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8783838Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8789884Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8796257Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8797575Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8797989Z | ^~~~~~~~ 2025-08-26T20:12:37.8798634Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8799659Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8800566Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8801399Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8802165Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8803055Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8804134Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8805301Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8806497Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8807647Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8808771Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8809754Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8810620Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8811270Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8812123Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8812874Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8813241Z | ^~~~ 2025-08-26T20:12:37.8813837Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8814718Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8815551Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8816343Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8817103Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8817962Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8818909Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8819816Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8820710Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8821667Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8822647Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8823503Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8824070Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8825072Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8826671Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8828431Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8830277Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8832249Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8834322Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8840534Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8850700Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8856486Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8857444Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8857834Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8863940Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8870338Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8871654Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8872112Z | ^~~~~~~~ 2025-08-26T20:12:37.8872752Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8873776Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8874670Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8875504Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8876286Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8877144Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8878220Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8879376Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8880553Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8881700Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8882730Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8883699Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8884558Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8885115Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8885967Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8886725Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8887081Z | ^~~~ 2025-08-26T20:12:37.8887671Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8888536Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8889475Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8890286Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8891048Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8891942Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8892877Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8893785Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8894715Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8895681Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8896667Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8897544Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8898108Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8899125Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8900729Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8902493Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8904306Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8906236Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8908305Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8914256Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8924402Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.8930273Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.8931225Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.8931617Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.8937826Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.8944208Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.8945516Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.8945944Z | ^~~~~~~~ 2025-08-26T20:12:37.8946575Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.8947604Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.8948504Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.8949342Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.8950201Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.8951048Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.8952137Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.8953348Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.8954523Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.8955702Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.8956732Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.8957681Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.8958543Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8959150Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8960003Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.8960760Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.8961099Z | ^~~~ 2025-08-26T20:12:37.8961685Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.8962559Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.8963394Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.8964193Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.8964944Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.8965806Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.8966745Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.8967649Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.8968554Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.8969579Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.8970558Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.8971421Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.8971985Z from rng_extension.cpp:1: 2025-08-26T20:12:37.8972994Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.8974598Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.8976386Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.8978189Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.8980151Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.8982259Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.8988220Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.8998274Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9004056Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9004993Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9005383Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9011554Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9018054Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9019318Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9019764Z | ^~~~~~~~ 2025-08-26T20:12:37.9020387Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9021382Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9022283Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9023090Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9023981Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9024839Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9025925Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9027097Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9028266Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9029403Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9030442Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9031413Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9032281Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9032856Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9033696Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9034464Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9034823Z | ^~~~ 2025-08-26T20:12:37.9035412Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9048241Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9049500Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9050309Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9051087Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9052011Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9052962Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9053913Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9054813Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9055774Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9056754Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9057661Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9058236Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9059338Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9060954Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9062720Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9064524Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9066464Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9068553Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9074527Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9084691Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9090580Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9091531Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9091921Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9097945Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9104321Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9105637Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9106063Z | ^~~~~~~~ 2025-08-26T20:12:37.9106708Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9107731Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9108631Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9109466Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9110285Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9111148Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9112239Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9113425Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9114582Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9115766Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9116798Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9117761Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9118649Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9119203Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9120056Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9120816Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9121169Z | ^~~~ 2025-08-26T20:12:37.9121764Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9122627Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9123460Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9124265Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9125031Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9125885Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9126817Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9127724Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9128630Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9129676Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9130658Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9131513Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9132082Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9133103Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9134702Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9136502Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9138504Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9140505Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9142627Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9148599Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9158671Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9164462Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9165412Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9165803Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9171994Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9178423Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9179770Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9180198Z | ^~~~~~~~ 2025-08-26T20:12:37.9180829Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9181853Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9182764Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9183598Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9184378Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9185220Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9186304Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9187467Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9188642Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9189783Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9190816Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9191766Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9192632Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9193206Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9194055Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9194814Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9195153Z | ^~~~ 2025-08-26T20:12:37.9195744Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9196655Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9197482Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9198286Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9199072Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9199932Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9200881Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9201818Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9202728Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9203672Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9204683Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9205545Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9206109Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9207127Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9208801Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9210561Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9212478Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9214348Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9216367Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9222755Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9233558Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9239824Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9240777Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9241163Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9247558Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9254319Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9255635Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9256051Z | ^~~~~~~~ 2025-08-26T20:12:37.9256694Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9257718Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9258700Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9259533Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9260307Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9261236Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9262320Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9263523Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9264702Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9265848Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9266903Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9267872Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9268733Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9269299Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9270152Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9270900Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9271250Z | ^~~~ 2025-08-26T20:12:37.9271837Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9272710Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9273546Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9274336Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9275095Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9275951Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9276894Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9277798Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9278693Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9279651Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9280632Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9281488Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9282050Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9283044Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9284680Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9286461Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9288267Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9290323Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9292401Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9298848Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9309687Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9315876Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9316813Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9317202Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9323727Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9330567Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9331883Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9332294Z | ^~~~~~~~ 2025-08-26T20:12:37.9332935Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9333958Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9334870Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9335706Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9336472Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9337337Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9338590Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9339760Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9340940Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9342073Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9343108Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9344078Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9345027Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9345595Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9346443Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9347210Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9347568Z | ^~~~ 2025-08-26T20:12:37.9348204Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9349088Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9349907Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9350752Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9351520Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9352376Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9353353Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9354249Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9355157Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9356109Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9357083Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9357940Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9358499Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9359498Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9361102Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9362865Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9364668Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9366590Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9368669Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9375221Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9386111Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9392371Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9393283Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9393664Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9399967Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9406767Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9408069Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9408494Z | ^~~~~~~~ 2025-08-26T20:12:37.9409234Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9410260Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9411201Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9412021Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9412809Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9413670Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9414781Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9415949Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9417123Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9418255Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9419294Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9420252Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9421114Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9421682Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9422520Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9423277Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9423628Z | ^~~~ 2025-08-26T20:12:37.9424216Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9425093Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9425910Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9426716Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9427480Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9428337Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9429278Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9430181Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9431124Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9432078Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9433056Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9433946Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9434497Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9435510Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9437135Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9439102Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9440907Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9442935Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9445015Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9451488Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9462402Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9468606Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9469594Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9469986Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9476481Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9483278Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9484552Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9484966Z | ^~~~~~~~ 2025-08-26T20:12:37.9485591Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9486590Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9487459Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9488273Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9489108Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9490064Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9491160Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9492336Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9493537Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9494792Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9495806Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9496779Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9497621Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9498161Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9499020Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9499765Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9500118Z | ^~~~ 2025-08-26T20:12:37.9500700Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9501570Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9502387Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9503168Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9503908Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9504744Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9505649Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9506533Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9507415Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9508346Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9509299Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9510136Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9510680Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9511807Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9513411Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9515175Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9516975Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9518904Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9521015Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9527494Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9538687Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9544834Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9545786Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9546179Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9552731Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9559556Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9560879Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9561303Z | ^~~~~~~~ 2025-08-26T20:12:37.9561943Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9562999Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9563896Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9564731Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9565507Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9566374Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9567460Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9568612Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9569869Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9571017Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9572055Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9573021Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9573885Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9574442Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9575300Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9576061Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9576415Z | ^~~~ 2025-08-26T20:12:37.9576987Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9577860Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9578697Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9579541Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9580300Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9581140Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9582085Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9583021Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9583929Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9584909Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9585893Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9586743Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9587310Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9588353Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9589957Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9591719Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9593525Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9595454Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9597526Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9603922Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9614927Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9621085Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9622050Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9622441Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9628938Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9635674Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9636996Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9637586Z | ^~~~~~~~ 2025-08-26T20:12:37.9638246Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9639264Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9640185Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9641091Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9641873Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9642739Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9643855Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9645032Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9646237Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9647380Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9648419Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9649450Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9650347Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9650920Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9651778Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9652539Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9652892Z | ^~~~ 2025-08-26T20:12:37.9653470Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9654347Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9655178Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9655994Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9656753Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9657595Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9658537Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9659450Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9660361Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9661315Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9662289Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9663151Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9663716Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9664731Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9666334Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9668132Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9669995Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9671922Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9674022Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9680433Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9691418Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9697563Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9698524Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9698958Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9705492Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9712246Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9713554Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9713977Z | ^~~~~~~~ 2025-08-26T20:12:37.9714609Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9715634Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9716541Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9717377Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9718157Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9719011Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9720079Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9721306Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9722473Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9723615Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9724679Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9725643Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9726493Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9727085Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9727935Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9728756Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9729109Z | ^~~~ 2025-08-26T20:12:37.9729699Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9730614Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9731449Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9732256Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9733013Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9733878Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9734822Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9735733Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9736643Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9737773Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9738748Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9739613Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9740189Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9741225Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9742824Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9744585Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9746379Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9748303Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9750468Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9756997Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9767885Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9774082Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9775037Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9775447Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9781989Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9788786Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9790107Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9790541Z | ^~~~~~~~ 2025-08-26T20:12:37.9791175Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9792234Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9793145Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9793973Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9794756Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9795606Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9796684Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9797847Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9799014Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9800155Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9801186Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9802133Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9802988Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9803550Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9804397Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9805157Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9805496Z | ^~~~ 2025-08-26T20:12:37.9806085Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9806968Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9807807Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9808651Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9809476Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9810341Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9811319Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9812237Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9813147Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9814123Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9815111Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9815969Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9816561Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9817585Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9819186Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9820932Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9822735Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9824660Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9826734Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9833155Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9844304Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9850552Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9851512Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9851892Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9858423Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9865271Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9866557Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9866959Z | ^~~~~~~~ 2025-08-26T20:12:37.9867581Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9868576Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9869461Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9870322Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9871077Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9871899Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9872973Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9874242Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9875433Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9876573Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9877589Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9878586Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9879448Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9880017Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9880869Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9881612Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9881967Z | ^~~~ 2025-08-26T20:12:37.9882559Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9883437Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9884273Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9885070Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9885835Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9886693Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9887638Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9888549Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9889558Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9890513Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9891497Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9892360Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9892928Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9893964Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9895621Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9897389Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9899236Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9901167Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9903276Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9909276Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9919345Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9925153Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9926092Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9926493Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9932631Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9939204Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9940594Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9941022Z | ^~~~~~~~ 2025-08-26T20:12:37.9941668Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9942698Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9943596Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9944426Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9945201Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9946059Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9947139Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9948300Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9949455Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9950597Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9951626Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9952585Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9953448Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9954001Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9954849Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9955617Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9955975Z | ^~~~ 2025-08-26T20:12:37.9956623Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9957486Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9957850Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9958220Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9958543Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9958967Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9959401Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9959795Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9960184Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9960634Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9961077Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9961410Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9961527Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9962319Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:37.9963201Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:37.9964157Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:37.9965100Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:37.9966184Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:37.9967293Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:37.9972822Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:37.9979046Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:37.9979911Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:37.9980087Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:37.9980204Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:37.9986484Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:37.9987794Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:37.9988007Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:37.9988145Z | ^~~~~~~~ 2025-08-26T20:12:37.9988621Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:37.9989045Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:37.9989418Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:37.9989791Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:37.9990103Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:37.9990529Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:37.9991096Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:37.9991609Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:37.9992144Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:37.9992667Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:37.9993090Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:37.9993512Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:37.9993836Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9993967Z from rng_extension.cpp:1: 2025-08-26T20:12:37.9994579Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:37.9994718Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:37.9994825Z | ^~~~ 2025-08-26T20:12:37.9995221Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:37.9995585Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:37.9995932Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:37.9996255Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:37.9996576Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:37.9997000Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:37.9997403Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:37.9997792Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:37.9998194Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:37.9998633Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:37.9999058Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:37.9999410Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:37.9999526Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0000314Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:38.0001223Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:38.0002189Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:38.0003150Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:38.0004234Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:38.0005339Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:38.0010852Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:38.0016977Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:38.0017860Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:38.0018022Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:38.0018137Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:38.0024442Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:38.0025774Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:38.0025985Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:38.0026085Z | ^~~~~~~~ 2025-08-26T20:12:38.0026566Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:38.0027002Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:38.0027358Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:38.0027711Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:38.0028020Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:38.0028448Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:38.0028989Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:38.0029503Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:38.0030051Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:38.0030531Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:38.0030969Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:38.0031420Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:38.0031744Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:38.0031876Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0032524Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:38.0032680Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:38.0032773Z | ^~~~ 2025-08-26T20:12:38.0033166Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:38.0033556Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:38.0033911Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:38.0034244Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:38.0034547Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:38.0035015Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:38.0035405Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:38.0035794Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:38.0036196Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:38.0036635Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:38.0037059Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:38.0037569Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:38.0037708Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0038502Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:38.0039401Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:38.0040350Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:38.0041304Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:38.0042379Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:38.0043503Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:38.0049102Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:38.0055240Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:38.0056133Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:38.0056297Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:38.0056431Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:38.0062673Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:38.0064052Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:38.0064282Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:38.0064373Z | ^~~~~~~~ 2025-08-26T20:12:38.0064850Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:38.0065317Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:38.0065685Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:38.0066049Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:38.0066351Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:38.0066855Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:38.0067383Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:38.0067898Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:38.0068444Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:38.0068928Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:38.0069364Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:38.0069781Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:38.0070114Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:38.0070233Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0070845Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:38.0070998Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:38.0071095Z | ^~~~ 2025-08-26T20:12:38.0071498Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:38.0071850Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:38.0072217Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:38.0072547Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:38.0072855Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:38.0073289Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:38.0073681Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:38.0074113Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:38.0074500Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:38.0074953Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:38.0075390Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:38.0075712Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:38.0075840Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0076641Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:38.0077539Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:38.0078487Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:38.0079472Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:38.0080541Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:38.0081659Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:38.0086640Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:38.0092393Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:38.0093264Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:38.0093452Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:38.0093586Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:38.0099419Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:38.0100759Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:38.0100986Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:38.0101075Z | ^~~~~~~~ 2025-08-26T20:12:38.0101554Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:38.0101996Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:38.0102357Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:38.0102721Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:38.0103025Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:38.0103464Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:38.0103994Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:38.0104516Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:38.0105074Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:38.0105558Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:38.0105991Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:38.0106429Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:38.0106763Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:38.0106879Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0107534Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:38.0107680Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:38.0107774Z | ^~~~ 2025-08-26T20:12:38.0108179Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:38.0108531Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:38.0108919Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:38.0109248Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:38.0109554Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:38.0109993Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:38.0110385Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:38.0110788Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:38.0111174Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:38.0111630Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:38.0112044Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:38.0112376Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:38.0112493Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0113271Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:38.0114163Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:38.0115116Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:38.0116067Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:38.0117135Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:38.0118293Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:38.0123759Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:38.0129947Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:38.0130795Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:38.0130974Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:38.0131092Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:38.0137537Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:38.0138949Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:38.0139175Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:38.0139268Z | ^~~~~~~~ 2025-08-26T20:12:38.0139761Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:38.0140185Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:38.0140599Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:38.0140952Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:38.0141251Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:38.0141692Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:38.0142219Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:38.0142741Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:38.0143272Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:38.0143765Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:38.0144186Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:38.0144612Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:38.0144936Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:38.0145053Z from rng_extension.cpp:1: 2025-08-26T20:12:38.0145680Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:38.0145824Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:38.0145930Z | ^~~~ 2025-08-26T20:12:38.0149128Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:12:38.4320402Z running install_lib 2025-08-26T20:12:38.4448078Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages 2025-08-26T20:12:38.4451692Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:38.4453258Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/__init__.py -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:38.4455114Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:38.4524193Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:38.4595723Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:38.4673980Z byte-compiling ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension/__init__.py to __init__.cpython-313.pyc 2025-08-26T20:12:38.4676302Z running install_egg_info 2025-08-26T20:12:38.4863166Z running egg_info 2025-08-26T20:12:38.4937528Z creating torch_test_cpp_extension.egg-info 2025-08-26T20:12:38.4938272Z writing torch_test_cpp_extension.egg-info/PKG-INFO 2025-08-26T20:12:38.4941652Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt 2025-08-26T20:12:38.4943536Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt 2025-08-26T20:12:38.4945587Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt 2025-08-26T20:12:38.4946768Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:12:38.5027554Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:12:38.5035018Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:12:38.5036399Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info 2025-08-26T20:12:38.5042831Z running install_scripts 2025-08-26T20:12:40.5195805Z running install 2025-08-26T20:12:40.5196875Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:12:40.5197685Z !! 2025-08-26T20:12:40.5197799Z 2025-08-26T20:12:40.5197955Z ******************************************************************************** 2025-08-26T20:12:40.5198348Z Please avoid running ``setup.py`` directly. 2025-08-26T20:12:40.5198763Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:12:40.5199145Z standards-based tools. 2025-08-26T20:12:40.5199336Z 2025-08-26T20:12:40.5199581Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:12:40.5200085Z or your builds will no longer be supported. 2025-08-26T20:12:40.5200330Z 2025-08-26T20:12:40.5200648Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:12:40.5201203Z ******************************************************************************** 2025-08-26T20:12:40.5201462Z 2025-08-26T20:12:40.5201544Z !! 2025-08-26T20:12:40.5201772Z self.initialize_options() 2025-08-26T20:12:40.5328625Z running build 2025-08-26T20:12:40.5328926Z running build_ext 2025-08-26T20:12:40.5653283Z building 'no_python_abi_suffix_test' extension 2025-08-26T20:12:40.5656265Z creating /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313 2025-08-26T20:12:40.7136330Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/no_python_abi_suffix_test.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=no_python_abi_suffix_test -std=c++17 2025-08-26T20:12:40.7182153Z creating build/lib.linux-x86_64-cpython-313 2025-08-26T20:12:40.7187119Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so 2025-08-26T20:12:40.8259992Z running install_lib 2025-08-26T20:12:40.8351124Z creating install/opt/conda/envs/py_3.13/lib/python3.13/site-packages 2025-08-26T20:12:40.8354498Z copying build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages 2025-08-26T20:12:40.8359699Z running install_egg_info 2025-08-26T20:12:40.8549685Z running egg_info 2025-08-26T20:12:40.8622885Z creating no_python_abi_suffix_test.egg-info 2025-08-26T20:12:40.8623792Z writing no_python_abi_suffix_test.egg-info/PKG-INFO 2025-08-26T20:12:40.8627399Z writing dependency_links to no_python_abi_suffix_test.egg-info/dependency_links.txt 2025-08-26T20:12:40.8629669Z writing top-level names to no_python_abi_suffix_test.egg-info/top_level.txt 2025-08-26T20:12:40.8631027Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt' 2025-08-26T20:12:40.8710582Z reading manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt' 2025-08-26T20:12:40.8717691Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt' 2025-08-26T20:12:40.8719230Z Copying no_python_abi_suffix_test.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/no_python_abi_suffix_test-0.0.0-py3.13.egg-info 2025-08-26T20:12:40.8727612Z running install_scripts 2025-08-26T20:12:41.2328672Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:12:41.2332147Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_aot_no_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:12:41.232982] 2025-08-26T20:12:44.3454489Z 2025-08-26T20:12:44.3459858Z test_cpp_extensions_aot_no_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_no_ninja_1.1_5d6504892157146d_.log 2025-08-26T20:12:44.3469086Z Running 21 items in this shard: test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_backward, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cublas_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cuda_dlink_libs, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cuda_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_cusolver_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_extension_function, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_extension_module, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_mps_extension, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_no_python_abi_suffix_sets_the_correct_library_name, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_optional, test/test_cpp_extensions_aot_no_ninja.py::TestCppExtensionAOT::test_sycl_extension, test/test_cpp_extensions_aot_no_ninja.py::TestPybindTypeCasters::test_pybind_return_types, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_add, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_autocast_apis_for_maia_device, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_conv_backend_override, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_matmul_autocast_default_precision, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_matmul_autocast_float16_precision, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_unregistered, test/test_cpp_extensions_aot_no_ninja.py::TestMAIATensor::test_zeros, test/test_cpp_extensions_aot_no_ninja.py::TestRNGExtension::test_rng, test/test_cpp_extensions_aot_no_ninja.py::TestTorchLibrary::test_torch_library 2025-08-26T20:12:44.3477712Z 2025-08-26T20:12:44.3477930Z Running test_autoload_disable 1/1 ... [2025-08-26 20:12:44.345760] 2025-08-26T20:12:46.6552787Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:12:46.6554388Z import pkg_resources 2025-08-26T20:12:46.7193963Z running install 2025-08-26T20:12:46.7195969Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:12:46.7196868Z !! 2025-08-26T20:12:46.7197053Z 2025-08-26T20:12:46.7197202Z ******************************************************************************** 2025-08-26T20:12:46.7197606Z Please avoid running ``setup.py`` directly. 2025-08-26T20:12:46.7198090Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:12:46.7198504Z standards-based tools. 2025-08-26T20:12:46.7198720Z 2025-08-26T20:12:46.7198963Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:12:46.7199517Z or your builds will no longer be supported. 2025-08-26T20:12:46.7199778Z 2025-08-26T20:12:46.7200151Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:12:46.7200701Z ******************************************************************************** 2025-08-26T20:12:46.7201007Z 2025-08-26T20:12:46.7201090Z !! 2025-08-26T20:12:46.7201324Z self.initialize_options() 2025-08-26T20:12:46.7328133Z running build 2025-08-26T20:12:46.7328404Z running build_py 2025-08-26T20:12:46.7411339Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:12:46.7413459Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:12:46.7416739Z running build_ext 2025-08-26T20:12:46.7430815Z building 'torch_test_cpp_extension.cpp' extension 2025-08-26T20:12:46.7432440Z creating build/temp.linux-x86_64-cpython-313 2025-08-26T20:12:46.7436508Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c extension.cpp -o build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cpp -std=c++17 2025-08-26T20:12:47.8659189Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/Exceptions.h:12, 2025-08-26T20:12:47.8660335Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/python.h:11, 2025-08-26T20:12:47.8661305Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:9, 2025-08-26T20:12:47.8661891Z from extension.cpp:1: 2025-08-26T20:12:47.8663207Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘class pybind11::class_’: 2025-08-26T20:12:47.8664088Z extension.cpp:45:53: required from here 2025-08-26T20:12:47.8665593Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:2041:7: warning: ‘pybind11::class_’ declared with greater visibility than its base ‘pybind11::detail::generic_type’ [-Wattributes] 2025-08-26T20:12:47.8668514Z 2041 | class class_ : public detail::generic_type { 2025-08-26T20:12:47.8668883Z | ^~~~~~ 2025-08-26T20:12:47.8670728Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘pybind11::class_< , >::class_(pybind11::handle, const char*, const Extra& ...) [with Extra = {}; type_ = MatrixMultiplier; options = {}]’: 2025-08-26T20:12:47.8672297Z extension.cpp:45:53: required from here 2025-08-26T20:12:47.8674878Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:2139:28: warning: ‘pybind11::class_::class_<>(pybind11::handle, const char*)::’ declared with greater visibility than the type of its field ‘pybind11::class_::class_<>(pybind11::handle, const char*)::::’ [-Wattributes] 2025-08-26T20:12:47.8677066Z 2139 | with_internals([&](internals &internals) { 2025-08-26T20:12:47.8677449Z | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:47.8678048Z 2140 | auto &instances = record.module_local ? get_local_internals().registered_types_cpp 2025-08-26T20:12:47.8678705Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:47.8679228Z 2141 | : internals.registered_types_cpp; 2025-08-26T20:12:47.8679651Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:47.8680129Z 2142 | instances[std::type_index(typeid(type_alias))] 2025-08-26T20:12:47.8680563Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:47.8681016Z 2143 | = instances[std::type_index(typeid(type))]; 2025-08-26T20:12:47.8681478Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:47.8681818Z 2144 | }); 2025-08-26T20:12:47.8682064Z | ~ 2025-08-26T20:12:47.8685745Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:12:48.4824128Z building 'torch_test_cpp_extension.maia' extension 2025-08-26T20:12:48.4827898Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c maia_extension.cpp -o build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=maia -std=c++17 2025-08-26T20:12:49.5302078Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:12:50.0894072Z building 'torch_test_cpp_extension.rng' extension 2025-08-26T20:12:50.0898038Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c rng_extension.cpp -o build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=rng -std=c++17 2025-08-26T20:12:51.3870763Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:12:51.3872515Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:12:51.3873974Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:12:51.3875486Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:12:51.3876584Z from rng_extension.cpp:6: 2025-08-26T20:12:51.3878151Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1478: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:51.3879430Z 1478 | #pragma unroll 2025-08-26T20:12:51.3879770Z | 2025-08-26T20:12:51.3880659Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_convert.h:4, 2025-08-26T20:12:51.3881995Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1530, 2025-08-26T20:12:51.3883358Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:12:51.3884877Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:12:51.3886312Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:12:51.3887979Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:12:51.3889327Z from rng_extension.cpp:6: 2025-08-26T20:12:51.3890378Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:59: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:51.3891177Z 59 | #pragma unroll 2025-08-26T20:12:51.3891434Z | 2025-08-26T20:12:51.3892588Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:72: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:51.3893420Z 72 | #pragma unroll 2025-08-26T20:12:51.3893666Z | 2025-08-26T20:12:51.3894522Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:87: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:51.3895323Z 87 | #pragma unroll 2025-08-26T20:12:51.3895573Z | 2025-08-26T20:12:51.3896172Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1531, 2025-08-26T20:12:51.3897112Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:12:51.3897942Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:12:51.3898758Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:12:51.3899700Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:12:51.3900398Z from rng_extension.cpp:6: 2025-08-26T20:12:51.3901471Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_mask.h:160: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:12:51.3902361Z 160 | #pragma unroll 2025-08-26T20:12:51.3902614Z | 2025-08-26T20:12:51.3903136Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.3904010Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.3904842Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.3905653Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.3906418Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.3907274Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.3908200Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.3909111Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.3910017Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.3910969Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.3911948Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.3912862Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.3913413Z from rng_extension.cpp:1: 2025-08-26T20:12:51.3914512Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.3916167Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.3917934Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.3919783Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.3921720Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.3923856Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.3930464Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.3941321Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.3947390Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.3948324Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.3948756Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.3955118Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.3961889Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.3963205Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.3963637Z | ^~~~~~~~ 2025-08-26T20:12:51.3964280Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.3965307Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.3966202Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.3967041Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.3967821Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.3968676Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.3969831Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.3970990Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.3972167Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.3973315Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.3974378Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.3975339Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.3976199Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.3976753Z from rng_extension.cpp:1: 2025-08-26T20:12:51.3977666Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.3978443Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.3978807Z | ^~~~ 2025-08-26T20:12:51.3979398Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.3980293Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.3981132Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.3981942Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.3982735Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.3983600Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.3984533Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.3985448Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.3986366Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.3987328Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.3988315Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.3989181Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.3989734Z from rng_extension.cpp:1: 2025-08-26T20:12:51.3990748Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.3992356Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.3994123Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.3995932Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.3997860Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.3999929Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4005973Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4016075Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4021880Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4022822Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4023215Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4029231Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4035631Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4036941Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4037544Z | ^~~~~~~~ 2025-08-26T20:12:51.4038272Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4039283Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4040193Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4041069Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4041853Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4042709Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4043815Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4044981Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4046147Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4047287Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4048319Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4049345Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4050200Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4050775Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4051651Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4052411Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4052756Z | ^~~~ 2025-08-26T20:12:51.4053357Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4054490Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4055328Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4056142Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4056910Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4057757Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4058698Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4059603Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4060506Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4061509Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4062478Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4063341Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4063933Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4064957Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4066593Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4068355Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4070151Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4072115Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4074183Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4080483Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4091219Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4097355Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4098303Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4098696Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4105102Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4111767Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4113085Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4113510Z | ^~~~~~~~ 2025-08-26T20:12:51.4114135Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4115159Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4116069Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4116901Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4117676Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4118523Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4119601Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4120866Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4122007Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4123156Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4124159Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4125135Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4125979Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4126671Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4127525Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4128319Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4128668Z | ^~~~ 2025-08-26T20:12:51.4129339Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4130217Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4131091Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4131913Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4132668Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4133531Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4134476Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4135391Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4136299Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4137252Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4138407Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4139275Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4139844Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4140868Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4142457Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4144210Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4146023Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4147945Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4150103Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4156488Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4167221Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4173358Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4174319Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4174700Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4181070Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4187793Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4189109Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4189550Z | ^~~~~~~~ 2025-08-26T20:12:51.4190196Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4191221Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4192125Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4193004Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4193778Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4194641Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4195731Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4196905Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4198081Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4199231Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4200253Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4201214Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4202078Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4202647Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4203500Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4204243Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4204595Z | ^~~~ 2025-08-26T20:12:51.4205190Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4206070Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4206893Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4207703Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4208471Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4209450Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4210393Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4211304Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4212230Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4213189Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4214167Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4215069Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4215636Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4216644Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4218243Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4220036Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4221847Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4223774Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4225843Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4232158Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4243115Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4249300Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4250242Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4250688Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4257079Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4266758Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4268151Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4268578Z | ^~~~~~~~ 2025-08-26T20:12:51.4269229Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4270273Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4271178Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4272020Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4272805Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4273696Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4274848Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4276008Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4277227Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4278383Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4279421Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4280399Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4281268Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4281828Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4282732Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4283528Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4283887Z | ^~~~ 2025-08-26T20:12:51.4284465Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4285345Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4286184Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4287002Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4287763Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4288604Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4289644Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4290555Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4291467Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4292425Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4293486Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4294339Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4294907Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4295952Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4297557Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4299315Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4301173Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4303096Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4305235Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4311190Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4321315Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4327087Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4328041Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4328435Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4334583Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4341171Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4342496Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4342925Z | ^~~~~~~~ 2025-08-26T20:12:51.4343553Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4344658Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4345575Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4346414Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4347202Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4348053Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4349137Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4350302Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4351483Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4352628Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4353663Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4354670Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4355538Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4356104Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4356961Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4357720Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4358066Z | ^~~~ 2025-08-26T20:12:51.4358656Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4359533Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4360363Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4361212Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4361974Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4362835Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4363820Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4364736Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4365645Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4366591Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4367574Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4368436Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4369109Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4370145Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4371741Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4373507Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4375323Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4377252Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4379333Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4385331Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4395457Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4401269Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4402238Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4402635Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4408700Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4415196Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4416517Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4416945Z | ^~~~~~~~ 2025-08-26T20:12:51.4417589Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4418628Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4419542Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4420365Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4421148Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4422060Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4423149Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4424325Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4425517Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4426660Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4427696Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4428666Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4429530Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4430101Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4430962Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4431723Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4432074Z | ^~~~ 2025-08-26T20:12:51.4432667Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4433530Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4434362Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4435173Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4435940Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4436800Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4437979Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4438893Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4439802Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4440839Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4441830Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4442693Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4443253Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4444296Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4445902Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4447666Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4449603Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4451587Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4453661Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4459611Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4469730Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4475507Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4476455Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4476850Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4482907Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4489384Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4490713Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4491141Z | ^~~~~~~~ 2025-08-26T20:12:51.4491811Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4492844Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4493750Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4494582Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4495358Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4496219Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4497288Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4498456Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4499631Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4500770Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4501798Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4502799Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4503647Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4504334Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4505164Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4505899Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4506229Z | ^~~~ 2025-08-26T20:12:51.4506801Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4507649Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4509214Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4509998Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4510865Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4511725Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4512700Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4513610Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4514519Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4515485Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4516455Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4517315Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4517914Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4518952Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4520552Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4522317Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4524111Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4526047Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4528124Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4534247Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4544557Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4550349Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4551351Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4551736Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4557780Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4564209Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4565528Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4565949Z | ^~~~~~~~ 2025-08-26T20:12:51.4566600Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4567632Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4568550Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4569456Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4570278Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4571140Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4572225Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4573422Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4574596Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4575728Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4576765Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4577734Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4578592Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4579193Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4580039Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4580792Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4581144Z | ^~~~ 2025-08-26T20:12:51.4581736Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4582608Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4583441Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4584253Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4585020Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4585886Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4586830Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4587727Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4588633Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4589631Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4590617Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4591479Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4592042Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4593049Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4594646Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4596409Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4598242Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4600204Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4602282Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4608225Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4618434Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4624210Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4625166Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4625558Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4631621Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4638173Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4639495Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4640003Z | ^~~~~~~~ 2025-08-26T20:12:51.4640655Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4641664Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4642575Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4643413Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4644200Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4645057Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4646138Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4647296Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4648466Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4649687Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4650783Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4651747Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4652612Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4653169Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4654034Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4654788Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4655139Z | ^~~~ 2025-08-26T20:12:51.4655714Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4656593Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4657478Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4658289Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4659057Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4659939Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4660889Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4661798Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4662706Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4663668Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4664646Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4665526Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4666092Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4667107Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4668706Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4670467Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4672270Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4674210Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4676287Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4682282Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4692455Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4698268Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4699224Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4699622Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4705673Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4712148Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4713466Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4713887Z | ^~~~~~~~ 2025-08-26T20:12:51.4714564Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4715589Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4716495Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4717331Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4718118Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4718966Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4720076Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4721244Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4722412Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4723563Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4724588Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4725552Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4726416Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4726988Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4727842Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4728585Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4729015Z | ^~~~ 2025-08-26T20:12:51.4729605Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4730490Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4731332Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4732127Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4732890Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4733752Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4734696Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4735608Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4736550Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4737786Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4738790Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4739669Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4740330Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4741395Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4742990Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4744761Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4746569Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4748552Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4750624Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4756597Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4766701Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4772646Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4773594Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4773988Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4780046Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4786444Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4787759Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4788185Z | ^~~~~~~~ 2025-08-26T20:12:51.4788827Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4789852Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4790748Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4791586Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4792369Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4793227Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4794313Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4795481Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4796638Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4797783Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4798879Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4799842Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4800711Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4801265Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4802150Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4802914Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4803272Z | ^~~~ 2025-08-26T20:12:51.4803870Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4804742Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4805575Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4806383Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4807176Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4808036Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4809153Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4810045Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4810957Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4811895Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4812857Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4813703Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4814247Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4815377Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4816984Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4818754Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4820561Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4822496Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4824581Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4831003Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4841807Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4847953Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4848963Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4849358Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4855804Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4862557Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4863884Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4864313Z | ^~~~~~~~ 2025-08-26T20:12:51.4864954Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4865967Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4866887Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4867720Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4868532Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4869507Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4870560Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4871684Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4872832Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4873951Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4874960Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4876027Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4876880Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4877449Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4878300Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4879178Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4879520Z | ^~~~ 2025-08-26T20:12:51.4880080Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4880932Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4881743Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4882530Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4883269Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4884090Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4885045Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4886092Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4887001Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4887968Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4889065Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4889922Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4890493Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4891516Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4893118Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4894878Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4896816Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4898690Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4900716Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4907216Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.4918113Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.4924265Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.4925216Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.4925608Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.4932163Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.4939104Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.4940416Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.4940847Z | ^~~~~~~~ 2025-08-26T20:12:51.4941483Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.4942488Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.4943404Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.4944242Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.4945022Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.4945879Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.4947057Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.4948232Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.4949403Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.4950584Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.4951621Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.4952588Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.4953441Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4954007Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4966281Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.4967111Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.4967610Z | ^~~~ 2025-08-26T20:12:51.4968219Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.4969239Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.4970081Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.4970891Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.4971657Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.4972520Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.4973471Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.4974391Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.4975304Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.4976249Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.4977235Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.4978100Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.4978668Z from rng_extension.cpp:1: 2025-08-26T20:12:51.4979784Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.4981404Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.4983159Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.4985041Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.4987010Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.4989134Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.4995553Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5006491Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5012711Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5013669Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5014066Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5020598Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5027395Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5028710Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5029172Z | ^~~~~~~~ 2025-08-26T20:12:51.5029806Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5030833Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5031741Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5032576Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5033369Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5034221Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5035309Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5036484Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5037845Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5038996Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5040039Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5040997Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5041862Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5042434Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5043295Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5044040Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5044397Z | ^~~~ 2025-08-26T20:12:51.5044989Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5045949Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5046822Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5047621Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5048390Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5049362Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5050313Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5051223Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5052130Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5053080Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5054065Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5054962Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5055530Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5056560Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5058146Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5059901Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5061700Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5063631Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5065704Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5072189Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5083097Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5089352Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5090301Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5090683Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5097223Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5103947Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5105257Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5105666Z | ^~~~~~~~ 2025-08-26T20:12:51.5106301Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5107390Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5108300Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5109128Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5109895Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5110783Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5111868Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5113032Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5114214Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5115355Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5116401Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5117364Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5118222Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5118780Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5119632Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5120383Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5120730Z | ^~~~ 2025-08-26T20:12:51.5121315Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5122185Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5123019Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5123815Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5124571Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5125431Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5126375Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5127285Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5128175Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5129202Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5130184Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5131042Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5131601Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5132669Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5134268Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5136054Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5137984Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5139918Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5142001Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5148490Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5159347Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5165572Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5166511Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5166906Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5173586Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5180333Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5181652Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5182063Z | ^~~~~~~~ 2025-08-26T20:12:51.5182703Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5183721Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5184641Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5185474Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5186241Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5187217Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5188280Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5189418Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5190564Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5191665Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5192668Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5193744Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5194687Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5195252Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5196088Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5196854Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5197208Z | ^~~~ 2025-08-26T20:12:51.5197836Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5198713Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5199528Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5200338Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5201102Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5201957Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5202929Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5203829Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5204734Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5205688Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5206670Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5207528Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5208091Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5209175Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5210784Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5212544Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5214373Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5216294Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5218375Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5224901Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5235859Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5242175Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5243118Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5243507Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5250157Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5256956Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5258262Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5258688Z | ^~~~~~~~ 2025-08-26T20:12:51.5259376Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5260399Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5261316Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5262146Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5262926Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5263782Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5264905Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5266077Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5267249Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5268384Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5269424Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5270390Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5271267Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5271837Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5272675Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5273442Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5273795Z | ^~~~ 2025-08-26T20:12:51.5274391Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5275277Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5276096Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5276900Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5277664Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5278522Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5279464Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5280357Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5281321Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5282276Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5283253Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5284140Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5284692Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5285696Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5287295Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5289135Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5290946Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5292922Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5294995Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5301432Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5312329Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5318473Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5319419Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5319815Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5326298Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5333124Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5334435Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5334860Z | ^~~~~~~~ 2025-08-26T20:12:51.5335500Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5336530Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5337572Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5338414Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5339204Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5340069Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5341151Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5342384Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5343579Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5344724Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5345799Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5346771Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5347632Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5348185Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5349038Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5349797Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5350149Z | ^~~~ 2025-08-26T20:12:51.5350740Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5351644Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5352478Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5353285Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5354042Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5354899Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5355831Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5356737Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5357645Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5358601Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5359580Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5360438Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5360994Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5362007Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5363607Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5365372Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5367180Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5369222Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5371331Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5377760Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5388627Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5394758Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5395706Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5396096Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5402621Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5409442Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5410770Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5411199Z | ^~~~~~~~ 2025-08-26T20:12:51.5411847Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5412918Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5413816Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5414665Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5415449Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5416315Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5417403Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5418562Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5419742Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5420886Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5421916Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5422878Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5423747Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5424299Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5425152Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5425917Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5426272Z | ^~~~ 2025-08-26T20:12:51.5426850Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5427728Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5428557Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5429443Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5430206Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5431050Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5432021Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5432930Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5433835Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5434795Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5435783Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5436630Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5437200Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5438404Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5440004Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5441757Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5443568Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5445489Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5447561Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5454019Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5465050Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5471223Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5472178Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5472573Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5479058Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5485777Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5487091Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5487521Z | ^~~~~~~~ 2025-08-26T20:12:51.5488160Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5489229Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5490133Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5491040Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5491821Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5492681Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5493783Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5494949Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5496119Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5497396Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5498400Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5499334Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5500194Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5500744Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5501569Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5502306Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5502649Z | ^~~~ 2025-08-26T20:12:51.5503211Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5504204Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5505038Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5505847Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5506611Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5507458Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5508402Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5509313Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5510226Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5511186Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5512158Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5513022Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5513594Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5514607Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5516250Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5518042Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5519883Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5521812Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5523881Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5529933Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5540228Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5546026Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5546986Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5547386Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5553515Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5559912Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5561231Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5561653Z | ^~~~~~~~ 2025-08-26T20:12:51.5562409Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5563562Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5564453Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5565279Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5566036Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5566863Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5567915Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5569110Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5570397Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5571547Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5572567Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5573535Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5574400Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5574968Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5575824Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5576564Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5576913Z | ^~~~ 2025-08-26T20:12:51.5577568Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5578441Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5578793Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5579133Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5579469Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5579904Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5580297Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5580689Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5581088Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5581526Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5581981Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5582302Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5582434Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5583210Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5584092Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5585057Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5586014Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5587080Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5588205Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5593645Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5599805Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5600670Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5600835Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5600966Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5607209Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5608516Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5608800Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5608892Z | ^~~~~~~~ 2025-08-26T20:12:51.5609440Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5609878Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5610238Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5610607Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5610948Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5611394Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5611922Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5612434Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5612979Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5613490Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5613925Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5614338Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5614673Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5614796Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5615414Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5615568Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5615662Z | ^~~~ 2025-08-26T20:12:51.5616072Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5616427Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5616788Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5617114Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5617419Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5617864Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5618256Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5618658Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5619051Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5619502Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5619916Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5620234Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5620422Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5621195Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5622084Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5623064Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5624013Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5625088Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5626203Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5631694Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5638028Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5638918Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5639083Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5639212Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5645515Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5646846Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5647069Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5647158Z | ^~~~~~~~ 2025-08-26T20:12:51.5647655Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5648080Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5648436Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5648869Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5649175Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5649621Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5650146Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5650671Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5651205Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5651699Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5652122Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5652606Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5652939Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5653054Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5653683Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5653853Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5653948Z | ^~~~ 2025-08-26T20:12:51.5654354Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5654704Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5655069Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5655396Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5655716Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5656167Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5656558Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5656966Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5657353Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5657810Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5658220Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5658551Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5658668Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5659446Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5660336Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5661299Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5662236Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5663321Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5664421Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5669916Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5676045Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5676917Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5677088Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5677207Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5683516Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5684850Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5685091Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5685182Z | ^~~~~~~~ 2025-08-26T20:12:51.5685672Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5686094Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5686472Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5686823Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5687138Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5687594Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5688122Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5688647Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5689274Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5689775Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5690197Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5690624Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5690946Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5691079Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5691698Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5691841Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5691956Z | ^~~~ 2025-08-26T20:12:51.5692388Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5692754Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5693107Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5693439Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5693758Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5694182Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5694589Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5695008Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5695414Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5695853Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5696296Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5696629Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5696746Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5697540Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5698426Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5699392Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5700364Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5701442Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5702558Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5707555Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5713235Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5714085Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5714254Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5714372Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5720183Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5721523Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5721739Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5721842Z | ^~~~~~~~ 2025-08-26T20:12:51.5722318Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5722739Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5723154Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5723503Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5723814Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5724245Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5724783Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5725289Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5725821Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5726345Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5726768Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5727222Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5727544Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5727674Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5728285Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5728426Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5728536Z | ^~~~ 2025-08-26T20:12:51.5729000Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:12:51.5729369Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:12:51.5729754Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:12:51.5730085Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:12:51.5730404Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:12:51.5730829Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:12:51.5731233Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:12:51.5731625Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:12:51.5732024Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:12:51.5732468Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:12:51.5732896Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:12:51.5733216Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5733333Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5734121Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:12:51.5735033Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:12:51.5735995Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:12:51.5736936Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:12:51.5738150Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:12:51.5739337Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:12:51.5744792Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:12:51.5750933Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:12:51.5751818Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:12:51.5751985Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:12:51.5752103Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:51.5758387Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:12:51.5759717Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:12:51.5759926Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:12:51.5760034Z | ^~~~~~~~ 2025-08-26T20:12:51.5760515Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:12:51.5760951Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:12:51.5761337Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:12:51.5761687Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:12:51.5762002Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:12:51.5762425Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:12:51.5762966Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:12:51.5763477Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:12:51.5764020Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:12:51.5764506Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:12:51.5764939Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:12:51.5765351Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:12:51.5765670Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:12:51.5765837Z from rng_extension.cpp:1: 2025-08-26T20:12:51.5766448Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:12:51.5766603Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:12:51.5766700Z | ^~~~ 2025-08-26T20:12:51.5769967Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:12:51.9937054Z running install_lib 2025-08-26T20:12:52.0067439Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:52.0147902Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:52.0229253Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:12:52.0316388Z running install_egg_info 2025-08-26T20:12:52.0504858Z running egg_info 2025-08-26T20:12:52.0580098Z writing torch_test_cpp_extension.egg-info/PKG-INFO 2025-08-26T20:12:52.0583284Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt 2025-08-26T20:12:52.0596219Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt 2025-08-26T20:12:52.0608495Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt 2025-08-26T20:12:52.0698325Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:12:52.0706905Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:12:52.0718511Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info' (and everything under it) 2025-08-26T20:12:52.0720090Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info 2025-08-26T20:12:52.0726193Z running install_scripts 2025-08-26T20:12:55.0141589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:12:55.0143177Z import pkg_resources 2025-08-26T20:12:55.0435484Z 2025-08-26T20:12:55.0435642Z Running tests... 2025-08-26T20:12:55.0435975Z ---------------------------------------------------------------------- 2025-08-26T20:12:55.0568230Z . 2025-08-26T20:12:55.0568516Z ---------------------------------------------------------------------- 2025-08-26T20:12:55.0568968Z Ran 1 test in 0.013s 2025-08-26T20:12:55.0569128Z 2025-08-26T20:12:55.0569225Z OK 2025-08-26T20:12:55.0569336Z 2025-08-26T20:12:55.0569457Z Generating XML reports... 2025-08-26T20:12:55.6790439Z Running test_autoload_enable 1/1 ... [2025-08-26 20:12:55.678781] 2025-08-26T20:12:57.9829691Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:12:57.9831272Z import pkg_resources 2025-08-26T20:12:58.0477636Z running install 2025-08-26T20:12:58.0479809Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:12:58.0480617Z !! 2025-08-26T20:12:58.0480731Z 2025-08-26T20:12:58.0480885Z ******************************************************************************** 2025-08-26T20:12:58.0481270Z Please avoid running ``setup.py`` directly. 2025-08-26T20:12:58.0481683Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:12:58.0482065Z standards-based tools. 2025-08-26T20:12:58.0482408Z 2025-08-26T20:12:58.0482662Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:12:58.0483169Z or your builds will no longer be supported. 2025-08-26T20:12:58.0483419Z 2025-08-26T20:12:58.0483724Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:12:58.0484275Z ******************************************************************************** 2025-08-26T20:12:58.0484536Z 2025-08-26T20:12:58.0484618Z !! 2025-08-26T20:12:58.0484898Z self.initialize_options() 2025-08-26T20:12:58.0613636Z running build 2025-08-26T20:12:58.0613925Z running build_py 2025-08-26T20:12:58.0698741Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:12:58.0700783Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:12:58.0704039Z running build_ext 2025-08-26T20:12:58.0718065Z building 'torch_test_cpp_extension.cpp' extension 2025-08-26T20:12:58.0719725Z creating build/temp.linux-x86_64-cpython-313 2025-08-26T20:12:58.0723851Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c extension.cpp -o build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cpp -std=c++17 2025-08-26T20:12:59.1270120Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/Exceptions.h:12, 2025-08-26T20:12:59.1271135Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/python.h:11, 2025-08-26T20:12:59.1272057Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:9, 2025-08-26T20:12:59.1272609Z from extension.cpp:1: 2025-08-26T20:12:59.1273916Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘class pybind11::class_’: 2025-08-26T20:12:59.1274768Z extension.cpp:45:53: required from here 2025-08-26T20:12:59.1276239Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:2041:7: warning: ‘pybind11::class_’ declared with greater visibility than its base ‘pybind11::detail::generic_type’ [-Wattributes] 2025-08-26T20:12:59.1277475Z 2041 | class class_ : public detail::generic_type { 2025-08-26T20:12:59.1277825Z | ^~~~~~ 2025-08-26T20:12:59.1279579Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h: In instantiation of ‘pybind11::class_< , >::class_(pybind11::handle, const char*, const Extra& ...) [with Extra = {}; type_ = MatrixMultiplier; options = {}]’: 2025-08-26T20:12:59.1281137Z extension.cpp:45:53: required from here 2025-08-26T20:12:59.1283482Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/pybind11/pybind11.h:2139:28: warning: ‘pybind11::class_::class_<>(pybind11::handle, const char*)::’ declared with greater visibility than the type of its field ‘pybind11::class_::class_<>(pybind11::handle, const char*)::::’ [-Wattributes] 2025-08-26T20:12:59.1285428Z 2139 | with_internals([&](internals &internals) { 2025-08-26T20:12:59.1285815Z | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:59.1286341Z 2140 | auto &instances = record.module_local ? get_local_internals().registered_types_cpp 2025-08-26T20:12:59.1287015Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:59.1287473Z 2141 | : internals.registered_types_cpp; 2025-08-26T20:12:59.1287877Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:59.1288310Z 2142 | instances[std::type_index(typeid(type_alias))] 2025-08-26T20:12:59.1288865Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:59.1289279Z 2143 | = instances[std::type_index(typeid(type))]; 2025-08-26T20:12:59.1289678Z | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:12:59.1289994Z 2144 | }); 2025-08-26T20:12:59.1290247Z | ~ 2025-08-26T20:12:59.1293557Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:12:59.7049326Z building 'torch_test_cpp_extension.maia' extension 2025-08-26T20:12:59.7053395Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c maia_extension.cpp -o build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=maia -std=c++17 2025-08-26T20:13:00.7655186Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:13:01.3435463Z building 'torch_test_cpp_extension.rng' extension 2025-08-26T20:13:01.3439126Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -Iself_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c rng_extension.cpp -o build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=rng -std=c++17 2025-08-26T20:13:02.6272941Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:13:02.6274770Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:13:02.6276075Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:13:02.6277492Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:13:02.6278532Z from rng_extension.cpp:6: 2025-08-26T20:13:02.6280436Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1478: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:13:02.6281649Z 1478 | #pragma unroll 2025-08-26T20:13:02.6282004Z | 2025-08-26T20:13:02.6282759Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_convert.h:4, 2025-08-26T20:13:02.6283869Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1530, 2025-08-26T20:13:02.6285155Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:13:02.6286521Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:13:02.6287704Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:13:02.6289026Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:13:02.6290078Z from rng_extension.cpp:6: 2025-08-26T20:13:02.6291127Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:59: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:13:02.6291934Z 59 | #pragma unroll 2025-08-26T20:13:02.6292182Z | 2025-08-26T20:13:02.6293029Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:72: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:13:02.6293917Z 72 | #pragma unroll 2025-08-26T20:13:02.6294193Z | 2025-08-26T20:13:02.6295028Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_n.h:87: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:13:02.6295834Z 87 | #pragma unroll 2025-08-26T20:13:02.6296084Z | 2025-08-26T20:13:02.6296645Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_base.h:1531, 2025-08-26T20:13:02.6297587Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec256/vec256.h:8, 2025-08-26T20:13:02.6298429Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec.h:7, 2025-08-26T20:13:02.6299350Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/Loops.h:37, 2025-08-26T20:13:02.6300299Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/native/cpu/DistributionTemplates.h:9, 2025-08-26T20:13:02.6300998Z from rng_extension.cpp:6: 2025-08-26T20:13:02.6301979Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/cpu/vec/vec_mask.h:160: warning: ignoring ‘#pragma unroll ’ [-Wunknown-pragmas] 2025-08-26T20:13:02.6303050Z 160 | #pragma unroll 2025-08-26T20:13:02.6303320Z | 2025-08-26T20:13:02.6303848Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6304730Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6305552Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6306426Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6307194Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6308055Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6309050Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6309949Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6310854Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6311807Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6312792Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6313654Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6314254Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6315341Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6316960Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6318726Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6320539Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6322467Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6324564Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6331130Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6342490Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6348698Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6349660Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6350058Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6356599Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6363336Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6364664Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6365094Z | ^~~~~~~~ 2025-08-26T20:13:02.6378245Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6379300Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6380219Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6381198Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6381966Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6382833Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6383965Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6385139Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6386309Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6387458Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6388471Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6389430Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6390331Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6390899Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6391826Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6392589Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6392947Z | ^~~~ 2025-08-26T20:13:02.6393539Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6394402Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6395231Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6396039Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6396800Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6397654Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6398595Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6399529Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6400437Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6401391Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6402369Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6403234Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6403787Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6404837Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6406445Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6408237Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6410174Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6412102Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6414186Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6420151Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6430935Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6436753Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6437967Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6438366Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6444515Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6451007Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6452377Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6452802Z | ^~~~~~~~ 2025-08-26T20:13:02.6453446Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6454469Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6455376Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6456216Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6456993Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6457854Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6458928Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6460097Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6461272Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6462467Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6463499Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6464467Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6465323Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6465896Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6466751Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6467510Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6467852Z | ^~~~ 2025-08-26T20:13:02.6468487Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6469373Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6470206Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6471133Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6471896Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6472730Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6473647Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6474539Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6475424Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6476351Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6477466Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6478324Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6478889Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6479909Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6481512Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6483277Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6485089Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6487004Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6489207Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6495563Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6506305Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6512370Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6513325Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6513724Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6520153Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6526872Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6528189Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6528613Z | ^~~~~~~~ 2025-08-26T20:13:02.6529300Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6530333Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6531242Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6532117Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6532910Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6533753Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6534836Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6536004Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6537174Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6538506Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6539550Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6540495Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6541360Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6541927Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6542800Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6543557Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6543897Z | ^~~~ 2025-08-26T20:13:02.6544483Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6545363Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6546203Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6546999Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6547758Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6548729Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6549715Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6550621Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6551534Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6552518Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6553777Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6554644Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6555210Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6556242Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6557843Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6559643Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6561458Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6563389Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6565477Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6571870Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6582619Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6588707Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6589659Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6590042Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6596458Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6603123Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6604460Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6604877Z | ^~~~~~~~ 2025-08-26T20:13:02.6605524Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6606547Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6607463Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6608303Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6609145Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6610009Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6611186Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6612354Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6613535Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6614709Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6615735Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6616702Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6617571Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6618140Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6619003Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6619782Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6620139Z | ^~~~ 2025-08-26T20:13:02.6620739Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6621617Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6622453Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6623255Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6624029Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6624879Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6625822Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6626732Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6627624Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6628580Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6629568Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6630427Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6630990Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6631992Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6633598Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6635352Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6637203Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6639366Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6641551Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6647854Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6658643Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6664717Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6665659Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6666059Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6672511Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6679228Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6680534Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6681006Z | ^~~~~~~~ 2025-08-26T20:13:02.6681651Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6682677Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6683584Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6684403Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6685191Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6686049Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6687129Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6688294Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6689534Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6690668Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6691705Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6692672Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6693536Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6694104Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6694951Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6695708Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6696058Z | ^~~~ 2025-08-26T20:13:02.6696646Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6697517Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6698409Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6699213Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6699975Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6700864Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6701807Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6702708Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6703617Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6704578Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6705556Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6706451Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6707008Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6708029Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6709636Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6711410Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6713216Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6715152Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6717224Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6723204Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6733392Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6739508Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6740473Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6740870Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6746940Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6753310Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6754635Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6755067Z | ^~~~~~~~ 2025-08-26T20:13:02.6755718Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6756732Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6757642Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6758480Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6759417Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6760284Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6761357Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6762591Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6763766Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6764910Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6765941Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6766912Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6767763Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6768368Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6769292Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6770060Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6770414Z | ^~~~ 2025-08-26T20:13:02.6770988Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6771869Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6772707Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6773511Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6774271Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6775121Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6776063Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6776981Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6777897Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6778862Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6779833Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6780697Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6781264Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6782280Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6783882Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6785747Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6787554Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6789515Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6791579Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6797573Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6807679Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6813543Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6814502Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6814886Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6821005Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6827394Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6828750Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6829166Z | ^~~~~~~~ 2025-08-26T20:13:02.6829814Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6830837Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6831744Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6832580Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6833358Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6834219Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6835303Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6836466Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6837832Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6838983Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6840008Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6840969Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6841834Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6842398Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6843259Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6844002Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6844354Z | ^~~~ 2025-08-26T20:13:02.6844945Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6845963Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6846800Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6847593Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6848361Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6849334Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6850285Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6851197Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6852099Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6853060Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6854045Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6854951Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6855516Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6856526Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6858132Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6859897Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6861704Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6863635Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6865723Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6871729Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6881844Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6887640Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6888595Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6889061Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6895119Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6901485Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6902805Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6903233Z | ^~~~~~~~ 2025-08-26T20:13:02.6903878Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6904902Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6905796Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6906736Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6907524Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6908389Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6909477Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6910659Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6911827Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6912972Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6914007Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6914971Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6915862Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6916416Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6917260Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6918015Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6918364Z | ^~~~ 2025-08-26T20:13:02.6918944Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6919833Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6920673Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6921485Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6922251Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6923113Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6924049Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6924958Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.6925870Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.6926826Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.6927811Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.6928660Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6929314Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6930333Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.6931980Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.6933773Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.6935581Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.6937738Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.6939841Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.6945804Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.6955936Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.6961727Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.6962686Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.6963080Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.6969309Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.6975772Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.6977141Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.6977569Z | ^~~~~~~~ 2025-08-26T20:13:02.6978219Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.6979240Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.6980151Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.6981001Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.6981782Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.6982644Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.6983741Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.6984920Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.6986106Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.6987280Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.6988322Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.6989304Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.6990180Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.6990772Z from rng_extension.cpp:1: 2025-08-26T20:13:02.6991639Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.6992411Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.6992756Z | ^~~~ 2025-08-26T20:13:02.6993359Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.6994361Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.6995202Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.6996025Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.6996807Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.6997674Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.6998626Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.6999536Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7000450Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7001406Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7002427Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7003294Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7003868Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7004886Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7006515Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7008287Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7010192Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7012114Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7014205Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7020257Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7030426Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7036290Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7037256Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7037825Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7043929Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7050383Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7051710Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7052132Z | ^~~~~~~~ 2025-08-26T20:13:02.7052777Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7053797Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7054711Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7055738Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7056513Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7057379Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7058512Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7059679Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7060850Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7062001Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7063018Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7063983Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7064899Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7065460Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7066308Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7067052Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7067402Z | ^~~~ 2025-08-26T20:13:02.7067999Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7068873Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7069693Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7070506Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7071273Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7072132Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7073081Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7073998Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7074898Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7075853Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7076838Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7077702Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7078270Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7079271Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7080911Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7082707Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7084545Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7086476Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7088555Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7094603Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7104708Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7110492Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7111447Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7111842Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7117938Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7124337Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7125691Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7126122Z | ^~~~~~~~ 2025-08-26T20:13:02.7126767Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7127775Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7128696Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7129611Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7130392Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7131248Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7132339Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7133510Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7134688Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7135839Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7136875Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7138012Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7138884Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7139456Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7140321Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7141086Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7141425Z | ^~~~ 2025-08-26T20:13:02.7142179Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7143060Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7143896Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7144709Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7145499Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7146356Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7147301Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7148213Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7149117Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7150059Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7151079Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7151937Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7152503Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7153530Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7155132Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7156873Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7158688Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7160616Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7162696Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7168696Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7178859Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7184663Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7185601Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7185992Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7192034Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7198400Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7199705Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7200129Z | ^~~~~~~~ 2025-08-26T20:13:02.7200770Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7201791Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7202778Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7203600Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7204380Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7205240Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7206364Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7207530Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7208689Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7209913Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7210957Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7211961Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7212826Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7213399Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7214241Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7214994Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7215355Z | ^~~~ 2025-08-26T20:13:02.7215947Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7216814Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7217642Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7218452Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7219213Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7220070Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7221011Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7221913Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7222816Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7223770Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7224754Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7225617Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7226173Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7227179Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7228873Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7230640Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7232480Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7234410Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7236489Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7243011Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7253889Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7259940Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7260961Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7261392Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7267820Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_full_64_bits_range_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7274490Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7275801Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7276227Z | ^~~~~~~~ 2025-08-26T20:13:02.7276881Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7277912Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7278808Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7279650Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7280437Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7281301Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7282384Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7283543Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7284722Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7285865Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7286906Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7287866Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7288739Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7289362Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7290291Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7291051Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7291405Z | ^~~~ 2025-08-26T20:13:02.7291981Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7292864Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7293728Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7294534Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7295293Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7296154Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7297082Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7297989Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7298927Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7299885Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7300870Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7301717Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7302286Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7303305Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7304904Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7306667Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7308471Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7310391Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7312462Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7318947Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7329945Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7336130Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7337083Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7337681Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7344178Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7351023Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7352384Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7352811Z | ^~~~~~~~ 2025-08-26T20:13:02.7353455Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7354510Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7355424Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7356256Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7357036Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7357905Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7358987Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7360189Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7361360Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7362502Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7363532Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7364499Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7365344Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7365907Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7366758Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7367514Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7367868Z | ^~~~ 2025-08-26T20:13:02.7368441Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7369384Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7370217Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7371029Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7371792Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7372637Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7373580Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7374486Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7375398Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7376434Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7377437Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7378300Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7378870Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7379926Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7381526Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7383283Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7385089Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7387013Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7389119Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7395515Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7406407Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7412668Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7413623Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7414020Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7420514Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7427310Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7428634Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7429062Z | ^~~~~~~~ 2025-08-26T20:13:02.7429709Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7430734Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7431628Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7432468Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7433249Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7434109Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7435195Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7436353Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7437742Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7439026Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7440065Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7441036Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7441937Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7442489Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7443355Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7444107Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7444460Z | ^~~~ 2025-08-26T20:13:02.7445041Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7445914Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7446744Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7447597Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7448363Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7449267Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7450213Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7451130Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7452038Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7452997Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7453986Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7454843Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7455408Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7456431Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7458036Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7459786Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7461598Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7463526Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7465650Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7472115Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7482993Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7489186Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7490145Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7490540Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7497088Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7503883Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7505192Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7505612Z | ^~~~~~~~ 2025-08-26T20:13:02.7506258Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7507266Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7508168Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7509032Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7509812Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7510668Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7511733Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7512907Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7514078Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7515220Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7516249Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7517215Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7518061Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7518627Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7519480Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7520236Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7520589Z | ^~~~ 2025-08-26T20:13:02.7521165Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7522043Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7522873Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7523684Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7524444Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7525360Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7526305Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7527222Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7528157Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7529199Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7530244Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7531203Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7532067Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7533192Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7534977Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7536890Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7539039Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7541076Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7543304Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7549942Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7561069Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7567488Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7568625Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7569155Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7575774Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7582788Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7584243Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7584728Z | ^~~~~~~~ 2025-08-26T20:13:02.7585469Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7586619Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7587627Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7588542Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7589455Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7590452Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7591612Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7592945Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7594245Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7595525Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7596631Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7597694Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7598681Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7599397Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7600341Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7611290Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7611674Z | ^~~~ 2025-08-26T20:13:02.7612272Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7613161Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7614013Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7614828Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7615596Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7616445Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7617394Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7618302Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7619196Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7620302Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7621291Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7622153Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7622723Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7623865Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7625460Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7627227Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7629111Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7631076Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7633166Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7639810Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7650881Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7657049Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7658001Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7658379Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7664901Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7671714Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7673065Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7673476Z | ^~~~~~~~ 2025-08-26T20:13:02.7674117Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7675141Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7676056Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7676891Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7677656Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7678520Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7679610Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7680773Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7681978Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7683124Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7684143Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7685114Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7685982Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7686557Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7687408Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7688154Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7688547Z | ^~~~ 2025-08-26T20:13:02.7689209Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7690092Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7690915Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7691765Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7692524Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7693383Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7694326Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7695241Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7696138Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7697128Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7698115Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7698977Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7699544Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7700558Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7702170Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7703936Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7705751Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7707674Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7709788Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7716192Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7727104Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7733369Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7734315Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7734706Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7741469Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7748248Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7749565Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7750040Z | ^~~~~~~~ 2025-08-26T20:13:02.7750685Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7751705Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7752619Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7753491Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7754272Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7755127Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7756214Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7757385Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7758559Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7759731Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7760764Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7761728Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7762594Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7763167Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7764006Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7764788Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7765141Z | ^~~~ 2025-08-26T20:13:02.7765729Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7766605Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7767426Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7768230Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7769118Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7769990Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7770933Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7771831Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7772743Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7773701Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7774679Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7775572Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7776127Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7777148Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7778782Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7780537Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7782344Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7784268Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7786388Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7792803Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7803683Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7809934Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7810875Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7811318Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7817787Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7824589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7825890Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7826325Z | ^~~~~~~~ 2025-08-26T20:13:02.7826965Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7827988Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7828891Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7829720Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7830545Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7831407Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7832492Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7833665Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7834826Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7835991Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7837031Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7838254Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7839121Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7839697Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7840616Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7841380Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7841740Z | ^~~~ 2025-08-26T20:13:02.7842334Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7843198Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7844048Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7844864Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7845631Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7846560Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7847509Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7848408Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7849391Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7850362Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7851346Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7852217Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7852770Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7853818Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7855422Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7857252Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7859061Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7860996Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7863070Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7869562Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7880404Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7886576Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7887528Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7887922Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7894512Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7901305Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7902622Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7903046Z | ^~~~~~~~ 2025-08-26T20:13:02.7903684Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7904702Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7905602Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7906436Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7907251Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7908111Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7909196Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7910362Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7911526Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7912668Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7913701Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7914665Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7915528Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7916078Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7916928Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7917683Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7918065Z | ^~~~ 2025-08-26T20:13:02.7918654Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7919512Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7920342Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7921150Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7921908Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7922770Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7923704Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7924654Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7925561Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.7926519Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.7927532Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.7928381Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7929042Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7930070Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.7931672Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.7933425Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.7935274Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.7937193Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.7939453Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.7945502Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.7955612Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.7961430Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.7962385Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.7962788Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.7968886Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.7975340Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.7976648Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.7977074Z | ^~~~~~~~ 2025-08-26T20:13:02.7977702Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.7978758Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.7979668Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.7980504Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.7981286Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.7982137Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.7983222Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.7984398Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.7985616Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.7986767Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.7987811Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.7988793Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.7989661Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.7990235Z from rng_extension.cpp:1: 2025-08-26T20:13:02.7991087Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.7991854Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.7992196Z | ^~~~ 2025-08-26T20:13:02.7992789Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.7993661Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.7994529Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.7995339Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.7996088Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.7996949Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.7997895Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.7998798Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.7999702Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.8000648Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.8001626Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.8002486Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8003045Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8004094Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.8005698Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.8007478Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.8009356Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.8011293Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.8013406Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.8019856Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.8030709Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.8036905Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.8038041Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.8038432Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.8044993Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.8051844Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.8053164Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.8053594Z | ^~~~~~~~ 2025-08-26T20:13:02.8054225Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.8055254Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.8056167Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.8057004Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.8057782Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.8058629Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.8059716Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.8060885Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.8062060Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.8063204Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.8064231Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.8065178Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.8066142Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8066712Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8067564Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.8068311Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.8068666Z | ^~~~ 2025-08-26T20:13:02.8069282Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.8070156Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.8070984Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.8071775Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.8072541Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.8073396Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.8074363Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.8075273Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.8076179Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.8077125Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.8078106Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.8078966Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8079529Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8080534Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.8082125Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.8083878Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.8085687Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.8087616Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.8089782Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.8096322Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.8107197Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.8113363Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.8114313Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.8114690Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.8121161Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.8127974Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.8129382Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.8129799Z | ^~~~~~~~ 2025-08-26T20:13:02.8130479Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.8131515Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.8132426Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.8133274Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.8134048Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.8134912Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.8136032Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.8137206Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.8138523Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.8139671Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.8140694Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.8141659Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.8142523Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8143096Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8143963Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.8144713Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.8145071Z | ^~~~ 2025-08-26T20:13:02.8145662Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.8146541Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.8147370Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.8148164Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.8148928Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.8149788Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.8150728Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.8151636Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.8152648Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.8153604Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.8154582Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.8155516Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8156081Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8157092Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.8158694Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.8160460Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.8162261Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.8164235Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.8166300Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.8172797Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.8183706Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.8189867Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.8190804Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.8191195Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.8197693Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.8204592Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.8205869Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.8206270Z | ^~~~~~~~ 2025-08-26T20:13:02.8206895Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.8207902Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.8208819Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.8209642Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.8210394Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.8211230Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.8212411Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.8213578Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.8214822Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.8215953Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.8216983Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.8217970Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.8218830Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8219389Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8220232Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.8221104Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.8221444Z | ^~~~ 2025-08-26T20:13:02.8222011Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.8222890Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.8223686Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.8224466Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.8225213Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.8226048Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.8226972Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.8227991Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.8228901Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.8229859Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.8230841Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.8231706Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8232273Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8233279Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.8234879Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.8236635Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.8238617Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.8240630Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.8242749Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.8248756Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.8258906Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.8264711Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.8265670Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.8266065Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.8272133Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_kernel(at::TensorIteratorBase&, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.8278571Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.8279889Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.8280318Z | ^~~~~~~~ 2025-08-26T20:13:02.8280964Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.8281984Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.8282896Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.8283761Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.8284550Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.8285417Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.8286500Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.8287662Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.8288897Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.8290046Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.8291080Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.8292039Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.8292894Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8293462Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8294320Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.8295076Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.8295425Z | ^~~~ 2025-08-26T20:13:02.8296008Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/ArrayRef.h:20, 2025-08-26T20:13:02.8296883Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/core/MemoryFormat.h:3, 2025-08-26T20:13:02.8297717Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/TensorBody.h:13, 2025-08-26T20:13:02.8298523Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/core/Tensor.h:3, 2025-08-26T20:13:02.8299285Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/Tensor.h:3, 2025-08-26T20:13:02.8300178Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/function_hook.h:3, 2025-08-26T20:13:02.8301150Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/cpp_hook.h:2, 2025-08-26T20:13:02.8302063Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/variable.h:6, 2025-08-26T20:13:02.8302972Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/autograd/autograd.h:3, 2025-08-26T20:13:02.8303962Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/autograd.h:3, 2025-08-26T20:13:02.8304948Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7, 2025-08-26T20:13:02.8305800Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8306369Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8307378Z In member function ‘void c10::SmallVectorTemplateCommon >::grow_pod(size_t, size_t) [with T = char*; = void]’, 2025-08-26T20:13:02.8308981Z inlined from ‘void c10::SmallVectorTemplateBase::grow(size_t) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:579:19, 2025-08-26T20:13:02.8310789Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:704:17, 2025-08-26T20:13:02.8312595Z inlined from ‘void c10::SmallVectorImpl::reserve(c10::SmallVectorImpl::size_type) [with T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:702:8, 2025-08-26T20:13:02.8314519Z inlined from ‘void c10::SmallVectorImpl::append(in_iter, in_iter) [with in_iter = char**; = void; T = char*]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:730:18, 2025-08-26T20:13:02.8316596Z inlined from ‘c10::SmallVector::SmallVector(ItTy, ItTy) [with ItTy = char**; = void; T = char*; unsigned int N = 4]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:1295:17, 2025-08-26T20:13:02.8322991Z inlined from ‘at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21, 2025-08-26T20:13:02.8334060Z inlined from ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’ at /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/FunctionRef.h:43:52: 2025-08-26T20:13:02.8340426Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:139:19: warning: ‘data’ may be used uninitialized [-Wmaybe-uninitialized] 2025-08-26T20:13:02.8341380Z 139 | Base::grow_pod(getFirstEl(), MinSize, TSize); 2025-08-26T20:13:02.8341850Z | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2025-08-26T20:13:02.8348343Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h: In static member function ‘static Ret c10::function_ref::callback_fn(intptr_t, Params ...) [with Callable = at::TensorIteratorBase::loop_2d_from_1d(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&):: >(const at::native::CPU_CAPABILITY::cpu_serial_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*):::::: >(at::TensorIteratorBase&, at::native::templates::cpu::{anonymous}::random_from_to_kernel(at::TensorIteratorBase&, uint64_t, int64_t, TestCPUGenerator*)::::::&&, const at::Range&)::&)::; Ret = void; Params = {char**, const long int*, long int, long int}]’: 2025-08-26T20:13:02.8355064Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/c10/util/SmallVector.h:73:8: note: by argument 2 of type ‘const void*’ to ‘void c10::SmallVectorBase::grow_pod(const void*, size_t, size_t) [with Size_T = unsigned int]’ declared here 2025-08-26T20:13:02.8356384Z 73 | void grow_pod(const void* FirstEl, size_t MinSize, size_t TSize); 2025-08-26T20:13:02.8356802Z | ^~~~~~~~ 2025-08-26T20:13:02.8357442Z In file included from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_meta.h:12, 2025-08-26T20:13:02.8358460Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ops/_addmm_activation_native.h:15, 2025-08-26T20:13:02.8359367Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/NativeFunctions.h:37, 2025-08-26T20:13:02.8360200Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIndexing.h:13, 2025-08-26T20:13:02.8360978Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/ATen.h:18, 2025-08-26T20:13:02.8361892Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3, 2025-08-26T20:13:02.8363008Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4, 2025-08-26T20:13:02.8364173Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3, 2025-08-26T20:13:02.8365390Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:4, 2025-08-26T20:13:02.8366534Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3, 2025-08-26T20:13:02.8367568Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3, 2025-08-26T20:13:02.8368532Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include/torch/all.h:9, 2025-08-26T20:13:02.8369459Z from /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/extension.h:5, 2025-08-26T20:13:02.8370025Z from rng_extension.cpp:1: 2025-08-26T20:13:02.8370882Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/ATen/TensorIterator.h:413:21: note: ‘data’ declared here 2025-08-26T20:13:02.8371677Z 413 | PtrVector data(base, base + ntensor); 2025-08-26T20:13:02.8372020Z | ^~~~ 2025-08-26T20:13:02.8375402Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:13:03.3321857Z running install_lib 2025-08-26T20:13:03.3452649Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:13:03.3531770Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:13:03.3612117Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:13:03.3698827Z running install_egg_info 2025-08-26T20:13:03.3888722Z running egg_info 2025-08-26T20:13:03.3965034Z writing torch_test_cpp_extension.egg-info/PKG-INFO 2025-08-26T20:13:03.3968388Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt 2025-08-26T20:13:03.3970541Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt 2025-08-26T20:13:03.3972809Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt 2025-08-26T20:13:03.4053927Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:13:03.4062716Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:13:03.4064307Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info' (and everything under it) 2025-08-26T20:13:03.4066069Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info 2025-08-26T20:13:03.4071978Z running install_scripts 2025-08-26T20:13:06.4221293Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:13:06.4222883Z import pkg_resources 2025-08-26T20:13:06.4482227Z 2025-08-26T20:13:06.4482360Z Running tests... 2025-08-26T20:13:06.4482695Z ---------------------------------------------------------------------- 2025-08-26T20:13:06.4597382Z . 2025-08-26T20:13:06.4597692Z ---------------------------------------------------------------------- 2025-08-26T20:13:06.4598067Z Ran 1 test in 0.011s 2025-08-26T20:13:06.4598242Z 2025-08-26T20:13:06.4598328Z OK 2025-08-26T20:13:06.4598465Z 2025-08-26T20:13:06.4598584Z Generating XML reports... 2025-08-26T20:13:07.0678730Z Running test_cpp_extensions_aot_ninja 1/1 ... [2025-08-26 20:13:07.067568] 2025-08-26T20:13:09.4094463Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:13:09.4096261Z import pkg_resources 2025-08-26T20:13:09.4741696Z running install 2025-08-26T20:13:09.4743642Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:13:09.4744454Z !! 2025-08-26T20:13:09.4744570Z 2025-08-26T20:13:09.4744709Z ******************************************************************************** 2025-08-26T20:13:09.4745093Z Please avoid running ``setup.py`` directly. 2025-08-26T20:13:09.4745527Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:13:09.4745911Z standards-based tools. 2025-08-26T20:13:09.4746104Z 2025-08-26T20:13:09.4746349Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:13:09.4746850Z or your builds will no longer be supported. 2025-08-26T20:13:09.4747103Z 2025-08-26T20:13:09.4747405Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:13:09.4747962Z ******************************************************************************** 2025-08-26T20:13:09.4748222Z 2025-08-26T20:13:09.4748306Z !! 2025-08-26T20:13:09.4748532Z self.initialize_options() 2025-08-26T20:13:09.4879006Z running build 2025-08-26T20:13:09.4879255Z running build_py 2025-08-26T20:13:09.4963068Z creating build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:13:09.4965315Z copying torch_test_cpp_extension/__init__.py -> build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension 2025-08-26T20:13:09.4968624Z running build_ext 2025-08-26T20:13:09.5299070Z building 'torch_test_cpp_extension.cpp' extension 2025-08-26T20:13:09.5300916Z creating /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313 2025-08-26T20:13:10.3179679Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/extension.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/var/lib/jenkins/workspace/test/cpp_extensions/self_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/extension.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=cpp -std=c++17 2025-08-26T20:13:10.3285574Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:13:10.8046989Z building 'torch_test_cpp_extension.maia' extension 2025-08-26T20:13:11.5801059Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/maia_extension.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/var/lib/jenkins/workspace/test/cpp_extensions/self_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/maia_extension.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/maia_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=maia -std=c++17 2025-08-26T20:13:11.5855384Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/maia_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:13:12.0550537Z building 'torch_test_cpp_extension.rng' extension 2025-08-26T20:13:12.9718547Z [1/1] c++ -MMD -MF /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/rng_extension.o.d -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include -I/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/include/torch/csrc/api/include -I/var/lib/jenkins/workspace/test/cpp_extensions/self_compiler_include_dirs_test -I/opt/conda/envs/py_3.13/include/python3.13 -c -c /var/lib/jenkins/workspace/test/cpp_extensions/rng_extension.cpp -o /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/rng_extension.o -g -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=rng -std=c++17 2025-08-26T20:13:12.9774456Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/build/temp.linux-x86_64-cpython-313/rng_extension.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so 2025-08-26T20:13:13.4522530Z running install_lib 2025-08-26T20:13:13.4651396Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/cpp.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:13:13.4694761Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/maia.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:13:13.4738934Z copying build/lib.linux-x86_64-cpython-313/torch_test_cpp_extension/rng.cpython-313-x86_64-linux-gnu.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension 2025-08-26T20:13:13.4787108Z running install_egg_info 2025-08-26T20:13:13.4973653Z running egg_info 2025-08-26T20:13:13.5049065Z writing torch_test_cpp_extension.egg-info/PKG-INFO 2025-08-26T20:13:13.5052624Z writing dependency_links to torch_test_cpp_extension.egg-info/dependency_links.txt 2025-08-26T20:13:13.5054665Z writing entry points to torch_test_cpp_extension.egg-info/entry_points.txt 2025-08-26T20:13:13.5056930Z writing top-level names to torch_test_cpp_extension.egg-info/top_level.txt 2025-08-26T20:13:13.5137172Z reading manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:13:13.5146338Z writing manifest file 'torch_test_cpp_extension.egg-info/SOURCES.txt' 2025-08-26T20:13:13.5148074Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info' (and everything under it) 2025-08-26T20:13:13.5149635Z Copying torch_test_cpp_extension.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch_test_cpp_extension-0.0.0-py3.13.egg-info 2025-08-26T20:13:13.5155910Z running install_scripts 2025-08-26T20:13:15.5528285Z running install 2025-08-26T20:13:15.5529656Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/setuptools/_distutils/cmd.py:90: SetuptoolsDeprecationWarning: setup.py install is deprecated. 2025-08-26T20:13:15.5530458Z !! 2025-08-26T20:13:15.5530584Z 2025-08-26T20:13:15.5530712Z ******************************************************************************** 2025-08-26T20:13:15.5531112Z Please avoid running ``setup.py`` directly. 2025-08-26T20:13:15.5531529Z Instead, use pypa/build, pypa/installer or other 2025-08-26T20:13:15.5531911Z standards-based tools. 2025-08-26T20:13:15.5532113Z 2025-08-26T20:13:15.5532352Z By 2025-Oct-31, you need to update your project and remove deprecated calls 2025-08-26T20:13:15.5532847Z or your builds will no longer be supported. 2025-08-26T20:13:15.5533095Z 2025-08-26T20:13:15.5533423Z See https://blog.ganssle.io/articles/2021/10/setup-py-deprecated.html for details. 2025-08-26T20:13:15.5533973Z ******************************************************************************** 2025-08-26T20:13:15.5534221Z 2025-08-26T20:13:15.5534301Z !! 2025-08-26T20:13:15.5534530Z self.initialize_options() 2025-08-26T20:13:15.5662980Z running build 2025-08-26T20:13:15.5663236Z running build_ext 2025-08-26T20:13:15.5995296Z building 'no_python_abi_suffix_test' extension 2025-08-26T20:13:15.6581342Z ninja: no work to do. 2025-08-26T20:13:15.6624100Z g++ -pthread -B /opt/conda/envs/py_3.13/share/python_compiler_compat -fno-strict-overflow -Wsign-compare -DNDEBUG -O2 -Wall -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -fPIC -O2 -isystem /opt/conda/envs/py_3.13/include -shared -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib -Wl,--allow-shlib-undefined -Wl,-rpath,/opt/conda/envs/py_3.13/lib -Wl,-rpath-link,/opt/conda/envs/py_3.13/lib -L/opt/conda/envs/py_3.13/lib /var/lib/jenkins/workspace/test/cpp_extensions/no_python_abi_suffix_test/build/temp.linux-x86_64-cpython-313/no_python_abi_suffix_test.o -L/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib -lc10 -ltorch -ltorch_cpu -ltorch_python -o build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so 2025-08-26T20:13:15.7695968Z running install_lib 2025-08-26T20:13:15.7789499Z copying build/lib.linux-x86_64-cpython-313/no_python_abi_suffix_test.so -> ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages 2025-08-26T20:13:15.7795098Z running install_egg_info 2025-08-26T20:13:15.7987558Z running egg_info 2025-08-26T20:13:15.8063473Z writing no_python_abi_suffix_test.egg-info/PKG-INFO 2025-08-26T20:13:15.8067646Z writing dependency_links to no_python_abi_suffix_test.egg-info/dependency_links.txt 2025-08-26T20:13:15.8070640Z writing top-level names to no_python_abi_suffix_test.egg-info/top_level.txt 2025-08-26T20:13:15.8149884Z reading manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt' 2025-08-26T20:13:15.8158700Z writing manifest file 'no_python_abi_suffix_test.egg-info/SOURCES.txt' 2025-08-26T20:13:15.8160323Z removing './install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/no_python_abi_suffix_test-0.0.0-py3.13.egg-info' (and everything under it) 2025-08-26T20:13:15.8161869Z Copying no_python_abi_suffix_test.egg-info to ./install/opt/conda/envs/py_3.13/lib/python3.13/site-packages/no_python_abi_suffix_test-0.0.0-py3.13.egg-info 2025-08-26T20:13:15.8167348Z running install_scripts 2025-08-26T20:13:16.1772738Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:13:16.1775763Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cpp_extensions_aot_ninja.py', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:13:16.177345] 2025-08-26T20:13:19.3352350Z 2025-08-26T20:13:19.3353295Z test_cpp_extensions_aot_ninja 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cpp_extensions_aot_ninja_1.1_8b8d47e9d6883ec3_.log 2025-08-26T20:13:19.3361640Z Running 21 items in this shard: test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_backward, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cublas_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cuda_dlink_libs, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cuda_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_cusolver_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_extension_function, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_extension_module, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_mps_extension, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_no_python_abi_suffix_sets_the_correct_library_name, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_optional, test/test_cpp_extensions_aot_ninja.py::TestCppExtensionAOT::test_sycl_extension, test/test_cpp_extensions_aot_ninja.py::TestPybindTypeCasters::test_pybind_return_types, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_add, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_autocast_apis_for_maia_device, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_conv_backend_override, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_matmul_autocast_default_precision, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_matmul_autocast_float16_precision, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_unregistered, test/test_cpp_extensions_aot_ninja.py::TestMAIATensor::test_zeros, test/test_cpp_extensions_aot_ninja.py::TestRNGExtension::test_rng, test/test_cpp_extensions_aot_ninja.py::TestTorchLibrary::test_torch_library 2025-08-26T20:13:19.3369433Z 2025-08-26T20:13:19.3369709Z Running inductor/test_compile_subprocess 2/2 ... [2025-08-26 20:13:19.335538] 2025-08-26T20:13:19.3370203Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:13:19.3371460Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compile_subprocess.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:13:19.335828] 2025-08-26T20:13:56.0997543Z 2025-08-26T20:13:56.0999080Z inductor/test_compile_subprocess 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_subprocess_2.2_3415576595930858_.log 2025-08-26T20:13:56.1001244Z Running 1 items in this shard: test/inductor/test_compile_subprocess.py::CpuTests::test_large_block_sizes_cpu 2025-08-26T20:13:56.1002169Z 2025-08-26T20:13:56.1002616Z Running inductor/test_memory 1/1 ... [2025-08-26 20:13:56.100103] 2025-08-26T20:13:56.1003323Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:13:56.1008482Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_memory.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:13:56.100521] 2025-08-26T20:14:02.6721364Z 2025-08-26T20:14:02.6722279Z inductor/test_memory 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_memory_1.1_86844522463e9a63_.log 2025-08-26T20:14:02.6722974Z 2025-08-26T20:14:02.6725570Z Running test_jit 1/1 ... [2025-08-26 20:14:02.672346] 2025-08-26T20:14:02.6725996Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:02.6728635Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:02.672659] 2025-08-26T20:14:07.8938598Z 2025-08-26T20:14:07.8939403Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_54bb077692499b46_.log 2025-08-26T20:14:07.8940105Z Running 0 items in this shard: 2025-08-26T20:14:07.8940300Z 2025-08-26T20:14:07.8942270Z Running test_binary_ufuncs 1/1 ... [2025-08-26 20:14:07.894079] 2025-08-26T20:14:07.8942686Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:07.8946101Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_binary_ufuncs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:07.894396] 2025-08-26T20:14:14.0165889Z 2025-08-26T20:14:14.0166760Z test_binary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_binary_ufuncs_1.1_9cd69e8ebebdf4e8_.log 2025-08-26T20:14:14.0167533Z Running 0 items in this shard: 2025-08-26T20:14:14.0167728Z 2025-08-26T20:14:14.0169791Z Running higher_order_ops/test_with_effects 1/1 ... [2025-08-26 20:14:14.016815] 2025-08-26T20:14:14.0170289Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:14.0173424Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_with_effects.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:14.017129] 2025-08-26T20:14:17.5859893Z 2025-08-26T20:14:17.5860865Z higher_order_ops/test_with_effects 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_with_effects_1.1_796b19d01e50de93_.log 2025-08-26T20:14:17.5862063Z Running 0 items in this shard: 2025-08-26T20:14:17.5862368Z 2025-08-26T20:14:17.5863054Z Running test_content_store 1/1 ... [2025-08-26 20:14:17.586172] 2025-08-26T20:14:17.5863474Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:17.5866822Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_content_store.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:17.586471] 2025-08-26T20:14:20.6546365Z 2025-08-26T20:14:20.6547229Z test_content_store 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_content_store_1.1_5d1119ba304bb60d_.log 2025-08-26T20:14:20.6547996Z Running 0 items in this shard: 2025-08-26T20:14:20.6548210Z 2025-08-26T20:14:20.6550195Z Running test_numpy_interop 1/1 ... [2025-08-26 20:14:20.654870] 2025-08-26T20:14:20.6550628Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:20.6553693Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_numpy_interop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:20.655174] 2025-08-26T20:14:23.7233474Z 2025-08-26T20:14:23.7234312Z test_numpy_interop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numpy_interop_1.1_146152f4854dad66_.log 2025-08-26T20:14:23.7235093Z Running 0 items in this shard: 2025-08-26T20:14:23.7235303Z 2025-08-26T20:14:23.7237266Z Running functorch/test_control_flow 1/1 ... [2025-08-26 20:14:23.723591] 2025-08-26T20:14:23.7237871Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:23.7241305Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_control_flow.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:23.723913] 2025-08-26T20:14:27.6932342Z 2025-08-26T20:14:27.6933257Z functorch/test_control_flow 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_control_flow_1.1_135111c4a0cecf37_.log 2025-08-26T20:14:27.6934136Z Running 0 items in this shard: 2025-08-26T20:14:27.6934328Z 2025-08-26T20:14:27.6936437Z Running functorch/test_aotdispatch 1/6 ... [2025-08-26 20:14:27.693492] 2025-08-26T20:14:27.6936917Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:27.6940271Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'serial', '--shard-id=1', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:27.693818] 2025-08-26T20:14:32.7144948Z 2025-08-26T20:14:32.7146519Z functorch/test_aotdispatch 1/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_1.6_6d8c62c7648b81da_.log 2025-08-26T20:14:32.7148192Z Running 0 items in this shard: 2025-08-26T20:14:32.7148562Z 2025-08-26T20:14:32.7150699Z Running functorch/test_aotdispatch 3/6 ... [2025-08-26 20:14:32.714856] 2025-08-26T20:14:32.7151181Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:32.7154598Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'serial', '--shard-id=3', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:32.715209] 2025-08-26T20:14:37.7358594Z 2025-08-26T20:14:37.7359543Z functorch/test_aotdispatch 3/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_3.6_1cac6e98971fe8ea_.log 2025-08-26T20:14:37.7360409Z Running 0 items in this shard: 2025-08-26T20:14:37.7360600Z 2025-08-26T20:14:37.7362572Z Running test_indexing 1/1 ... [2025-08-26 20:14:37.736111] 2025-08-26T20:14:37.7363055Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:37.7366188Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:37.736428] 2025-08-26T20:14:40.8546905Z 2025-08-26T20:14:40.8547932Z test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_indexing_1.1_805692eb029adea0_.log 2025-08-26T20:14:40.8548667Z Running 0 items in this shard: 2025-08-26T20:14:40.8548868Z 2025-08-26T20:14:40.8550819Z Running test_type_promotion 1/1 ... [2025-08-26 20:14:40.854932] 2025-08-26T20:14:40.8551245Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:40.8554583Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_promotion.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:40.855253] 2025-08-26T20:14:43.9735369Z 2025-08-26T20:14:43.9736183Z test_type_promotion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_promotion_1.1_814273a3da31f6c5_.log 2025-08-26T20:14:43.9737177Z Running 0 items in this shard: 2025-08-26T20:14:43.9737505Z 2025-08-26T20:14:43.9739875Z Running functorch/test_eager_transforms 1/1 ... [2025-08-26 20:14:43.973810] 2025-08-26T20:14:43.9740345Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:43.9743392Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_eager_transforms.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:43.974131] 2025-08-26T20:14:48.4942109Z 2025-08-26T20:14:48.4943137Z functorch/test_eager_transforms 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_eager_transforms_1.1_04416473ef13094c_.log 2025-08-26T20:14:48.4944036Z Running 0 items in this shard: 2025-08-26T20:14:48.4944227Z 2025-08-26T20:14:48.4945890Z Running inductor/test_flex_decoding 1/1 ... [2025-08-26 20:14:48.494422] 2025-08-26T20:14:48.4946362Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:48.4949305Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_flex_decoding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:48.494726] 2025-08-26T20:14:51.6129757Z 2025-08-26T20:14:51.6130677Z inductor/test_flex_decoding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_decoding_1.1_29fc20483eafe8d7_.log 2025-08-26T20:14:51.6133556Z Running 4 items in this shard: test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_non_pow_2_headdim_head_dim_121_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_non_pow_2_headdim_head_dim_17_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_non_pow_2_headdim_head_dim_24_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_non_pow_2_headdim_head_dim_94_float32_cpu_float32 2025-08-26T20:14:51.6135593Z 2025-08-26T20:14:51.6135936Z Running export/test_export_training_ir_to_run_decomp 1/1 ... [2025-08-26 20:14:51.613212] 2025-08-26T20:14:51.6136459Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:51.6138310Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_training_ir_to_run_decomp.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:51.613540] 2025-08-26T20:14:58.6369613Z 2025-08-26T20:14:58.6371585Z export/test_export_training_ir_to_run_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_training_ir_to_run_decomp_1.1_078f104fb51753c8_.log 2025-08-26T20:14:58.6373320Z Running 0 items in this shard: 2025-08-26T20:14:58.6373617Z 2025-08-26T20:14:58.6375168Z Running inductor/test_pattern_matcher 1/1 ... [2025-08-26 20:14:58.637329] 2025-08-26T20:14:58.6376033Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:14:58.6380992Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_pattern_matcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:14:58.637767] 2025-08-26T20:15:05.2640729Z 2025-08-26T20:15:05.2641716Z inductor/test_pattern_matcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pattern_matcher_1.1_79a96750ff4422a3_.log 2025-08-26T20:15:05.2642517Z 2025-08-26T20:15:05.2644264Z Running inductor/test_inductor_utils 1/1 ... [2025-08-26 20:15:05.264277] 2025-08-26T20:15:05.2644749Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:05.2648123Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inductor_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:05.264595] 2025-08-26T20:15:08.2696756Z 2025-08-26T20:15:08.2697730Z inductor/test_inductor_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_utils_1.1_39fff00b497afdcf_.log 2025-08-26T20:15:08.2698513Z 2025-08-26T20:15:08.2700474Z Running inductor/test_torchinductor_strided_blocks 1/1 ... [2025-08-26 20:15:08.269892] 2025-08-26T20:15:08.2701045Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:08.2704102Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor_strided_blocks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:08.270200] 2025-08-26T20:15:15.0627254Z 2025-08-26T20:15:15.0628332Z inductor/test_torchinductor_strided_blocks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_strided_blocks_1.1_14628895502327a2_.log 2025-08-26T20:15:15.0629220Z 2025-08-26T20:15:15.0630883Z Running inductor/test_subgraph_choice 1/1 ... [2025-08-26 20:15:15.062945] 2025-08-26T20:15:15.0631368Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:15.0634534Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_subgraph_choice.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:15.063256] 2025-08-26T20:15:21.4283740Z 2025-08-26T20:15:21.4284707Z inductor/test_subgraph_choice 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_subgraph_choice_1.1_ac3caf3df854d203_.log 2025-08-26T20:15:21.4285528Z 2025-08-26T20:15:21.4287257Z Running inductor/test_aot_inductor_package 1/1 ... [2025-08-26 20:15:21.428568] 2025-08-26T20:15:21.4287760Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:21.4291288Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_aot_inductor_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:21.428925] 2025-08-26T20:15:27.7876516Z 2025-08-26T20:15:27.7877922Z inductor/test_aot_inductor_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_package_1.1_dcebf483527de3da_.log 2025-08-26T20:15:27.7879049Z 2025-08-26T20:15:27.7880441Z Running inductor/test_triton_heuristics 1/1 ... [2025-08-26 20:15:27.787885] 2025-08-26T20:15:27.7881050Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:27.7884043Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_triton_heuristics.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:27.788184] 2025-08-26T20:15:34.1686705Z 2025-08-26T20:15:34.1687690Z inductor/test_triton_heuristics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_heuristics_1.1_b8a41ff73a233c83_.log 2025-08-26T20:15:34.1688466Z 2025-08-26T20:15:34.1690430Z Running inductor/test_inplacing_pass 1/1 ... [2025-08-26 20:15:34.168878] 2025-08-26T20:15:34.1690932Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:34.1693888Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:34.169193] 2025-08-26T20:15:40.5589157Z 2025-08-26T20:15:40.5590128Z inductor/test_inplacing_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplacing_pass_1.1_68b7b2f6821b877d_.log 2025-08-26T20:15:40.5590896Z 2025-08-26T20:15:40.5592453Z Running inductor/test_online_softmax 1/1 ... [2025-08-26 20:15:40.559103] 2025-08-26T20:15:40.5592932Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:40.5595947Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_online_softmax.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:40.559402] 2025-08-26T20:15:46.7709080Z 2025-08-26T20:15:46.7710031Z inductor/test_online_softmax 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_online_softmax_1.1_a9d4b629c9fda430_.log 2025-08-26T20:15:46.7710814Z 2025-08-26T20:15:46.7712500Z Running inductor/test_cpu_select_algorithm 4/16 ... [2025-08-26 20:15:46.771105] 2025-08-26T20:15:46.7712997Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:46.7716108Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'serial', '--shard-id=4', '--num-shards=16', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:46.771396] 2025-08-26T20:15:53.9948469Z 2025-08-26T20:15:53.9949600Z inductor/test_cpu_select_algorithm 4/16 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_4.16_d9f1f5077741da2f_.log 2025-08-26T20:15:53.9950535Z Running 0 items in this shard: 2025-08-26T20:15:53.9950728Z 2025-08-26T20:15:53.9951984Z Running inductor/test_cpu_select_algorithm 8/16 ... [2025-08-26 20:15:53.995050] 2025-08-26T20:15:53.9952482Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:15:53.9955615Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'serial', '--shard-id=8', '--num-shards=16', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:15:53.995338] 2025-08-26T20:16:01.1689575Z 2025-08-26T20:16:01.1690547Z inductor/test_cpu_select_algorithm 8/16 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_8.16_3a556e161efdaac1_.log 2025-08-26T20:16:01.1691484Z Running 0 items in this shard: 2025-08-26T20:16:01.1691898Z 2025-08-26T20:16:01.1693629Z Running inductor/test_cpu_select_algorithm 12/16 ... [2025-08-26 20:16:01.169183] 2025-08-26T20:16:01.1694135Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:01.1697065Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'serial', '--shard-id=12', '--num-shards=16', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:01.169493] 2025-08-26T20:16:08.4433063Z 2025-08-26T20:16:08.4434282Z inductor/test_cpu_select_algorithm 12/16 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_12.16_878db3d00c24503e_.log 2025-08-26T20:16:08.4435229Z Running 0 items in this shard: 2025-08-26T20:16:08.4435427Z 2025-08-26T20:16:08.4436936Z Running inductor/test_scatter_optimization 1/1 ... [2025-08-26 20:16:08.443538] 2025-08-26T20:16:08.4437585Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:08.4440716Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_scatter_optimization.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:08.443862] 2025-08-26T20:16:14.7397730Z 2025-08-26T20:16:14.7399486Z inductor/test_scatter_optimization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_scatter_optimization_1.1_aabbf7aedb4809a6_.log 2025-08-26T20:16:14.7400320Z 2025-08-26T20:16:14.7401582Z Running dynamo/test_list 1/1 ... [2025-08-26 20:16:14.739993] 2025-08-26T20:16:14.7402013Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:14.7404989Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_list.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:14.740299] 2025-08-26T20:16:18.0589322Z 2025-08-26T20:16:18.0590217Z dynamo/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_list_1.1_fee98c297eb2c5f9_.log 2025-08-26T20:16:18.0590987Z Running 0 items in this shard: 2025-08-26T20:16:18.0591183Z 2025-08-26T20:16:18.0592816Z Running dynamo/test_sources 1/1 ... [2025-08-26 20:16:18.059146] 2025-08-26T20:16:18.0593240Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:18.0596835Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sources.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:18.059457] 2025-08-26T20:16:21.0776647Z 2025-08-26T20:16:21.0777540Z dynamo/test_sources 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sources_1.1_d8e5bffe71dcb2b9_.log 2025-08-26T20:16:21.0778341Z Running 0 items in this shard: 2025-08-26T20:16:21.0778553Z 2025-08-26T20:16:21.0780623Z Running dynamo/test_model_output 1/1 ... [2025-08-26 20:16:21.077913] 2025-08-26T20:16:21.0781064Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:21.0784107Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_model_output.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:21.078213] 2025-08-26T20:16:24.3967369Z 2025-08-26T20:16:24.3968295Z dynamo/test_model_output 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_model_output_1.1_8e67577f031a7f4c_.log 2025-08-26T20:16:24.3969181Z Running 0 items in this shard: 2025-08-26T20:16:24.3969388Z 2025-08-26T20:16:24.3971059Z Running dynamo/test_profiler 1/1 ... [2025-08-26 20:16:24.396958] 2025-08-26T20:16:24.3971486Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:24.3974909Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_profiler.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:24.397261] 2025-08-26T20:16:27.7158736Z 2025-08-26T20:16:27.7159613Z dynamo/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_profiler_1.1_efb026a1d6a10bf2_.log 2025-08-26T20:16:27.7160632Z Running 0 items in this shard: 2025-08-26T20:16:27.7160828Z 2025-08-26T20:16:27.7162768Z Running export/test_export_opinfo 1/1 ... [2025-08-26 20:16:27.716107] 2025-08-26T20:16:27.7163226Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:27.7166179Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_opinfo.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:27.716409] 2025-08-26T20:16:31.9361942Z 2025-08-26T20:16:31.9362841Z export/test_export_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_opinfo_1.1_217ef00bfefb7e76_.log 2025-08-26T20:16:31.9363916Z Running 0 items in this shard: 2025-08-26T20:16:31.9364107Z 2025-08-26T20:16:31.9365702Z Running nn/test_multihead_attention 1/1 ... [2025-08-26 20:16:31.936423] 2025-08-26T20:16:31.9366169Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:31.9369465Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_multihead_attention.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:31.936726] 2025-08-26T20:16:35.0550373Z 2025-08-26T20:16:35.0551945Z nn/test_multihead_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_multihead_attention_1.1_8c0defbea28c88a8_.log 2025-08-26T20:16:35.0553370Z Running 0 items in this shard: 2025-08-26T20:16:35.0553704Z 2025-08-26T20:16:35.0554414Z Running inductor/test_auto_functionalize 1/1 ... [2025-08-26 20:16:35.055258] 2025-08-26T20:16:35.0555180Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:35.0557828Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_auto_functionalize.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:35.055558] 2025-08-26T20:16:38.3259539Z 2025-08-26T20:16:38.3260537Z inductor/test_auto_functionalize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_auto_functionalize_1.1_8ca78ae8a15b4a7a_.log 2025-08-26T20:16:38.3261456Z Running 0 items in this shard: 2025-08-26T20:16:38.3261683Z 2025-08-26T20:16:38.3263318Z Running dynamo/test_base_hop 1/1 ... [2025-08-26 20:16:38.326186] 2025-08-26T20:16:38.3263750Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:38.3266913Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_base_hop.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:38.326494] 2025-08-26T20:16:41.5948739Z 2025-08-26T20:16:41.5949626Z dynamo/test_base_hop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_base_hop_1.1_b291b6bcdc7174b7_.log 2025-08-26T20:16:41.5950411Z Running 0 items in this shard: 2025-08-26T20:16:41.5950604Z 2025-08-26T20:16:41.5952595Z Running export/test_upgrader 1/1 ... [2025-08-26 20:16:41.595119] 2025-08-26T20:16:41.5953015Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:41.5956673Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_upgrader.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:41.595428] 2025-08-26T20:16:44.6134644Z 2025-08-26T20:16:44.6135793Z export/test_upgrader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_upgrader_1.1_b5c21c731a6e3f52_.log 2025-08-26T20:16:44.6136611Z Running 0 items in this shard: 2025-08-26T20:16:44.6136801Z 2025-08-26T20:16:44.6138969Z Running export/test_export 1/1 ... [2025-08-26 20:16:44.613714] 2025-08-26T20:16:44.6139401Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:44.6142405Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:44.614039] 2025-08-26T20:16:51.1866794Z 2025-08-26T20:16:51.1867719Z export/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_1.1_99b6775c8d5b0602_.log 2025-08-26T20:16:51.1868499Z Running 0 items in this shard: 2025-08-26T20:16:51.1868689Z 2025-08-26T20:16:51.1870446Z Running inductor/test_binary_folding 1/1 ... [2025-08-26 20:16:51.186891] 2025-08-26T20:16:51.1871120Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:51.1874151Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_binary_folding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:51.187207] 2025-08-26T20:16:58.0604922Z 2025-08-26T20:16:58.0605913Z inductor/test_binary_folding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_binary_folding_1.1_821e79e812ab49ad_.log 2025-08-26T20:16:58.0606818Z Running 0 items in this shard: 2025-08-26T20:16:58.0607014Z 2025-08-26T20:16:58.0608664Z Running dynamo/test_backward_higher_order_ops 1/1 ... [2025-08-26 20:16:58.060708] 2025-08-26T20:16:58.0609278Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:16:58.0612612Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_backward_higher_order_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:16:58.061032] 2025-08-26T20:17:01.3796498Z 2025-08-26T20:17:01.3797547Z dynamo/test_backward_higher_order_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_backward_higher_order_ops_1.1_ca0a59d737ee81e6_.log 2025-08-26T20:17:01.3798492Z Running 0 items in this shard: 2025-08-26T20:17:01.3798687Z 2025-08-26T20:17:01.3800335Z Running dynamo/test_deviceguard 1/1 ... [2025-08-26 20:17:01.379863] 2025-08-26T20:17:01.3800823Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:01.3804123Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deviceguard.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:01.380213] 2025-08-26T20:17:04.7989626Z 2025-08-26T20:17:04.7990515Z dynamo/test_deviceguard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deviceguard_1.1_3a1405906a5f5160_.log 2025-08-26T20:17:04.7991341Z Running 0 items in this shard: 2025-08-26T20:17:04.7991536Z 2025-08-26T20:17:04.7993435Z Running export/test_swap 1/1 ... [2025-08-26 20:17:04.799195] 2025-08-26T20:17:04.7993837Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:04.7997159Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_swap.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:04.799514] 2025-08-26T20:17:07.8176417Z 2025-08-26T20:17:07.8177212Z export/test_swap 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_swap_1.1_a4faa528e0b6e199_.log 2025-08-26T20:17:07.8177992Z Running 0 items in this shard: 2025-08-26T20:17:07.8178181Z 2025-08-26T20:17:07.8180282Z Running dynamo/test_export 1/1 ... [2025-08-26 20:17:07.817882] 2025-08-26T20:17:07.8180895Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:07.8183980Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_export.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:07.818191] 2025-08-26T20:17:11.1367093Z 2025-08-26T20:17:11.1367966Z dynamo/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_export_1.1_0fbde9de936075ef_.log 2025-08-26T20:17:11.1368821Z Running 0 items in this shard: 2025-08-26T20:17:11.1369018Z 2025-08-26T20:17:11.1371112Z Running dynamo/test_debug_utils 1/1 ... [2025-08-26 20:17:11.136961] 2025-08-26T20:17:11.1371536Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:11.1374636Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_debug_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:11.137277] 2025-08-26T20:17:14.3556100Z 2025-08-26T20:17:14.3556988Z dynamo/test_debug_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_debug_utils_1.1_c5f06b7a99136e24_.log 2025-08-26T20:17:14.3557796Z Running 0 items in this shard: 2025-08-26T20:17:14.3557986Z 2025-08-26T20:17:14.3559929Z Running dynamo/test_flat_apply 1/1 ... [2025-08-26 20:17:14.355833] 2025-08-26T20:17:14.3560377Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:14.3563388Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_flat_apply.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:14.356153] 2025-08-26T20:17:17.5744731Z 2025-08-26T20:17:17.5745763Z dynamo/test_flat_apply 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_flat_apply_1.1_b489984a5174dccd_.log 2025-08-26T20:17:17.5747149Z Running 0 items in this shard: 2025-08-26T20:17:17.5747344Z 2025-08-26T20:17:17.5748622Z Running dynamo/test_optimizers 1/1 ... [2025-08-26 20:17:17.574703] 2025-08-26T20:17:17.5749053Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:17.5752230Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_optimizers.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:17.575014] 2025-08-26T20:17:20.8433796Z 2025-08-26T20:17:20.8434668Z dynamo/test_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_optimizers_1.1_921fb42629ae2304_.log 2025-08-26T20:17:20.8435491Z Running 0 items in this shard: 2025-08-26T20:17:20.8435695Z 2025-08-26T20:17:20.8438332Z Running dynamo/test_verify_correctness 1/1 ... [2025-08-26 20:17:20.843662] 2025-08-26T20:17:20.8438807Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:20.8443180Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_verify_correctness.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:20.844079] 2025-08-26T20:17:24.2128205Z 2025-08-26T20:17:24.2130052Z dynamo/test_verify_correctness 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_verify_correctness_1.1_cab6dfe3dc6a7176_.log 2025-08-26T20:17:24.2131698Z Running 0 items in this shard: 2025-08-26T20:17:24.2132008Z 2025-08-26T20:17:24.2134123Z Running dynamo/test_sets 1/1 ... [2025-08-26 20:17:24.213218] 2025-08-26T20:17:24.2134770Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:24.2139748Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sets.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:24.213628] 2025-08-26T20:17:27.5323673Z 2025-08-26T20:17:27.5324912Z dynamo/test_sets 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sets_1.1_7b812562268cb7b1_.log 2025-08-26T20:17:27.5326293Z Running 0 items in this shard: 2025-08-26T20:17:27.5326644Z 2025-08-26T20:17:27.5330279Z Running inductor/test_unbacked_symints 1/1 ... [2025-08-26 20:17:27.532758] 2025-08-26T20:17:27.5330999Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:27.5334420Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_unbacked_symints.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:27.533131] 2025-08-26T20:17:34.1061105Z 2025-08-26T20:17:34.1062099Z inductor/test_unbacked_symints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_unbacked_symints_1.1_e7581d92e070137b_.log 2025-08-26T20:17:34.1062994Z Running 0 items in this shard: 2025-08-26T20:17:34.1063187Z 2025-08-26T20:17:34.1065035Z Running dynamo/test_python_dispatcher 1/1 ... [2025-08-26 20:17:34.106341] 2025-08-26T20:17:34.1065491Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:34.1068668Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_dispatcher.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:34.106663] 2025-08-26T20:17:37.4251570Z 2025-08-26T20:17:37.4252588Z dynamo/test_python_dispatcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_dispatcher_1.1_f5c3112633966e52_.log 2025-08-26T20:17:37.4253467Z Running 0 items in this shard: 2025-08-26T20:17:37.4253664Z 2025-08-26T20:17:37.4255309Z Running dynamo/test_cudagraphs 1/1 ... [2025-08-26 20:17:37.425386] 2025-08-26T20:17:37.4255752Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:37.4259078Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:37.425703] 2025-08-26T20:17:40.5638341Z 2025-08-26T20:17:40.5639246Z dynamo/test_cudagraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_1.1_8b6887aa887595d2_.log 2025-08-26T20:17:40.5639957Z 2025-08-26T20:17:40.5641954Z Running export/test_unflatten 1/1 ... [2025-08-26 20:17:40.564046] 2025-08-26T20:17:40.5642375Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:40.5645576Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_unflatten.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:40.564351] 2025-08-26T20:17:43.6325652Z 2025-08-26T20:17:43.6326553Z export/test_unflatten 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_unflatten_1.1_ec41dfab14b91392_.log 2025-08-26T20:17:43.6327695Z Running 0 items in this shard: 2025-08-26T20:17:43.6327890Z 2025-08-26T20:17:43.6329353Z Running inductor/test_efficient_conv_bn_eval 1/1 ... [2025-08-26 20:17:43.632779] 2025-08-26T20:17:43.6329853Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:43.6333140Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_efficient_conv_bn_eval.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:43.633091] 2025-08-26T20:17:50.6564420Z 2025-08-26T20:17:50.6565421Z inductor/test_efficient_conv_bn_eval 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_efficient_conv_bn_eval_1.1_8e5b0d863cb16667_.log 2025-08-26T20:17:50.6566334Z Running 0 items in this shard: 2025-08-26T20:17:50.6566537Z 2025-08-26T20:17:50.6567841Z Running export/test_nativert 1/1 ... [2025-08-26 20:17:50.656640] 2025-08-26T20:17:50.6568298Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:50.6571367Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_nativert.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:50.656945] 2025-08-26T20:17:57.4299774Z 2025-08-26T20:17:57.4300817Z export/test_nativert 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_nativert_1.1_6ad91a8d31baabe2_.log 2025-08-26T20:17:57.4301633Z Running 0 items in this shard: 2025-08-26T20:17:57.4301829Z 2025-08-26T20:17:57.4303406Z Running dynamo/test_activation_checkpointing 1/1 ... [2025-08-26 20:17:57.430172] 2025-08-26T20:17:57.4303914Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:17:57.4306839Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_activation_checkpointing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:17:57.430477] 2025-08-26T20:18:04.0932860Z 2025-08-26T20:18:04.0933954Z dynamo/test_activation_checkpointing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_activation_checkpointing_1.1_01b9f11fb2b48787_.log 2025-08-26T20:18:04.0934943Z Running 0 items in this shard: 2025-08-26T20:18:04.0935141Z 2025-08-26T20:18:04.0936287Z Running dynamo/test_hooks 1/1 ... [2025-08-26 20:18:04.093481] 2025-08-26T20:18:04.0936743Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:04.0940332Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_hooks.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:04.093813] 2025-08-26T20:18:07.4123070Z 2025-08-26T20:18:07.4124114Z dynamo/test_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_hooks_1.1_3aa099db2326fe29_.log 2025-08-26T20:18:07.4124883Z Running 0 items in this shard: 2025-08-26T20:18:07.4125074Z 2025-08-26T20:18:07.4128215Z Running dynamo/test_generator 1/1 ... [2025-08-26 20:18:07.412600] 2025-08-26T20:18:07.4129042Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:07.4132976Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_generator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:07.412995] 2025-08-26T20:18:10.6814719Z 2025-08-26T20:18:10.6815672Z dynamo/test_generator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_generator_1.1_3f08473bc1348b4c_.log 2025-08-26T20:18:10.6816726Z Running 0 items in this shard: 2025-08-26T20:18:10.6816919Z 2025-08-26T20:18:10.6819121Z Running dynamo/test_reorder_logs 1/1 ... [2025-08-26 20:18:10.681749] 2025-08-26T20:18:10.6819569Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:10.6822675Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_reorder_logs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:10.682077] 2025-08-26T20:18:13.9505524Z 2025-08-26T20:18:13.9506469Z dynamo/test_reorder_logs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_reorder_logs_1.1_d7b3e48a21e2fb34_.log 2025-08-26T20:18:13.9507289Z Running 0 items in this shard: 2025-08-26T20:18:13.9507496Z 2025-08-26T20:18:13.9509139Z Running export/test_verifier 1/1 ... [2025-08-26 20:18:13.950770] 2025-08-26T20:18:13.9509571Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:13.9512646Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_verifier.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:13.951075] 2025-08-26T20:18:16.9691070Z 2025-08-26T20:18:16.9692184Z export/test_verifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_verifier_1.1_bf39331a3f3527e3_.log 2025-08-26T20:18:16.9692981Z Running 0 items in this shard: 2025-08-26T20:18:16.9693185Z 2025-08-26T20:18:16.9694947Z Running export/test_sparse 1/1 ... [2025-08-26 20:18:16.969341] 2025-08-26T20:18:16.9695368Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:16.9698204Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_sparse.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:16.969634] 2025-08-26T20:18:20.0878862Z 2025-08-26T20:18:20.0879676Z export/test_sparse 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_sparse_1.1_e9d534a3e948e7fe_.log 2025-08-26T20:18:20.0880457Z Running 0 items in this shard: 2025-08-26T20:18:20.0880658Z 2025-08-26T20:18:20.0882270Z Running dynamo/test_comptime 1/1 ... [2025-08-26 20:18:20.088084] 2025-08-26T20:18:20.0882690Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:20.0885640Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_comptime.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:20.088371] 2025-08-26T20:18:23.4068988Z 2025-08-26T20:18:23.4069876Z dynamo/test_comptime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_comptime_1.1_f72cc862ab144bdf_.log 2025-08-26T20:18:23.4070705Z Running 0 items in this shard: 2025-08-26T20:18:23.4070898Z 2025-08-26T20:18:23.4072608Z Running dynamo/test_python_autograd 1/1 ... [2025-08-26 20:18:23.407112] 2025-08-26T20:18:23.4073073Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:23.4075973Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_autograd.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:23.407409] 2025-08-26T20:18:26.7258758Z 2025-08-26T20:18:26.7259690Z dynamo/test_python_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_autograd_1.1_39a67fb86b355003_.log 2025-08-26T20:18:26.7260527Z Running 0 items in this shard: 2025-08-26T20:18:26.7260733Z 2025-08-26T20:18:26.7262502Z Running test_ao_sparsity 1/1 ... [2025-08-26 20:18:26.726109] 2025-08-26T20:18:26.7263121Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:26.7265917Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ao_sparsity.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:26.726394] 2025-08-26T20:18:30.2451090Z 2025-08-26T20:18:30.2452108Z test_ao_sparsity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ao_sparsity_1.1_606b35ed4897e110_.log 2025-08-26T20:18:30.2452879Z Running 0 items in this shard: 2025-08-26T20:18:30.2453088Z 2025-08-26T20:18:30.2454821Z Running test_package 1/1 ... [2025-08-26 20:18:30.245346] 2025-08-26T20:18:30.2455214Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:30.2458117Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_package.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:30.245631] 2025-08-26T20:18:33.5641202Z 2025-08-26T20:18:33.5642017Z test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_package_1.1_a25e398c581829a5_.log 2025-08-26T20:18:33.5642729Z Running 0 items in this shard: 2025-08-26T20:18:33.5643144Z 2025-08-26T20:18:33.5644754Z Running profiler/test_kineto 1/1 ... [2025-08-26 20:18:33.564332] 2025-08-26T20:18:33.5645189Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:33.5648129Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_kineto.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:33.564624] 2025-08-26T20:18:36.5827448Z 2025-08-26T20:18:36.5828803Z profiler/test_kineto 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_kineto_1.1_28cb0738b963b4ea_.log 2025-08-26T20:18:36.5830313Z Running 0 items in this shard: 2025-08-26T20:18:36.5830624Z 2025-08-26T20:18:36.5833717Z Running higher_order_ops/test_invoke_subgraph 1/1 ... [2025-08-26 20:18:36.583087] 2025-08-26T20:18:36.5834488Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:36.5838071Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_invoke_subgraph.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:36.583459] 2025-08-26T20:18:43.1562401Z 2025-08-26T20:18:43.1563437Z higher_order_ops/test_invoke_subgraph 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_invoke_subgraph_1.1_b902dd0d2258ec1f_.log 2025-08-26T20:18:43.1564376Z Running 0 items in this shard: 2025-08-26T20:18:43.1564569Z 2025-08-26T20:18:43.1566563Z Running test_comparison_utils 1/1 ... [2025-08-26 20:18:43.156496] 2025-08-26T20:18:43.1566988Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:43.1570535Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_comparison_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:43.156833] 2025-08-26T20:18:46.1749571Z 2025-08-26T20:18:46.1750503Z test_comparison_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_comparison_utils_1.1_2bcc9d1fd041661c_.log 2025-08-26T20:18:46.1751288Z Running 0 items in this shard: 2025-08-26T20:18:46.1751496Z 2025-08-26T20:18:46.1754203Z Running functorch/test_ac_logging 1/1 ... [2025-08-26 20:18:46.175207] 2025-08-26T20:18:46.1754655Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:46.1757618Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:46.175533] 2025-08-26T20:18:49.2437573Z 2025-08-26T20:18:49.2438478Z functorch/test_ac_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_logging_1.1_0ceadbdd376d56c4_.log 2025-08-26T20:18:49.2439340Z Running 0 items in this shard: 2025-08-26T20:18:49.2439546Z 2025-08-26T20:18:49.2441741Z Running test_mkl_verbose 1/1 ... [2025-08-26 20:18:49.243996] 2025-08-26T20:18:49.2442155Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:49.2445389Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkl_verbose.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:49.244329] 2025-08-26T20:18:52.2623863Z 2025-08-26T20:18:52.2624846Z test_mkl_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkl_verbose_1.1_5428b175cfe9991a_.log 2025-08-26T20:18:52.2625593Z Running 0 items in this shard: 2025-08-26T20:18:52.2625786Z 2025-08-26T20:18:52.2628452Z Running test_decomp 1/11 ... [2025-08-26 20:18:52.262629] 2025-08-26T20:18:52.2629034Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:52.2631545Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_decomp.py', '-m', 'serial', '--shard-id=1', '--num-shards=11', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:52.262948] 2025-08-26T20:18:57.8844903Z 2025-08-26T20:18:57.8845741Z test_decomp 1/11 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_1.11_967714a4be08528d_.log 2025-08-26T20:18:57.8846451Z Running 0 items in this shard: 2025-08-26T20:18:57.8846660Z 2025-08-26T20:18:57.8848868Z Running test_transformers 1/2 ... [2025-08-26 20:18:57.884733] 2025-08-26T20:18:57.8849345Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:18:57.8852653Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:18:57.885061] 2025-08-26T20:19:02.9061050Z 2025-08-26T20:19:02.9061937Z test_transformers 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_1.2_69eca12df1834ccc_.log 2025-08-26T20:19:02.9062726Z Running 0 items in this shard: 2025-08-26T20:19:02.9062924Z 2025-08-26T20:19:02.9064887Z Running test_transformers 2/2 ... [2025-08-26 20:19:02.906328] 2025-08-26T20:19:02.9065309Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:02.9068915Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:02.906662] 2025-08-26T20:19:07.8276252Z 2025-08-26T20:19:07.8277122Z test_transformers 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_2.2_cef86b00e857a3ad_.log 2025-08-26T20:19:07.8277906Z Running 0 items in this shard: 2025-08-26T20:19:07.8278101Z 2025-08-26T20:19:07.8280313Z Running test_mkldnn_verbose 1/1 ... [2025-08-26 20:19:07.827880] 2025-08-26T20:19:07.8280738Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:07.8284297Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_verbose.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:07.828201] 2025-08-26T20:19:10.9967113Z 2025-08-26T20:19:10.9968192Z test_mkldnn_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_verbose_1.1_3b006f22b29ea83b_.log 2025-08-26T20:19:10.9969076Z Running 0 items in this shard: 2025-08-26T20:19:10.9969277Z 2025-08-26T20:19:10.9971290Z Running test_utils_config_module 1/1 ... [2025-08-26 20:19:10.996961] 2025-08-26T20:19:10.9971761Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:10.9975211Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils_config_module.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:10.997296] 2025-08-26T20:19:14.1659085Z 2025-08-26T20:19:14.1659988Z test_utils_config_module 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_config_module_1.1_5c6781194fa526c0_.log 2025-08-26T20:19:14.1660854Z Running 0 items in this shard: 2025-08-26T20:19:14.1661049Z 2025-08-26T20:19:14.1663072Z Running test_ops_jit 1/2 ... [2025-08-26 20:19:14.166143] 2025-08-26T20:19:14.1663470Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:14.1666710Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_jit.py', '-m', 'serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:14.166465] 2025-08-26T20:19:18.5365673Z 2025-08-26T20:19:18.5366455Z test_ops_jit 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_jit_1.2_ff14771af25e7e9b_.log 2025-08-26T20:19:18.5367183Z Running 0 items in this shard: 2025-08-26T20:19:18.5367379Z 2025-08-26T20:19:18.5369756Z Running functorch/test_ops 4/6 ... [2025-08-26 20:19:18.536798] 2025-08-26T20:19:18.5370182Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:18.5373316Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'serial', '--shard-id=4', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:18.537119] 2025-08-26T20:19:24.8599626Z 2025-08-26T20:19:24.8600479Z functorch/test_ops 4/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_4.6_80b62c490a73f40f_.log 2025-08-26T20:19:24.8601272Z Running 0 items in this shard: 2025-08-26T20:19:24.8601478Z 2025-08-26T20:19:24.8603466Z Running test_ops 3/7 ... [2025-08-26 20:19:24.860199] 2025-08-26T20:19:24.8603846Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:24.8607193Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'serial', '--shard-id=3', '--num-shards=7', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:24.860511] 2025-08-26T20:19:38.7431007Z 2025-08-26T20:19:38.7431763Z test_ops 3/7 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_3.7_78d3bc3d8df8c41c_.log 2025-08-26T20:19:38.7432441Z Running 0 items in this shard: 2025-08-26T20:19:38.7432652Z 2025-08-26T20:19:38.7434630Z Running test_ops 6/7 ... [2025-08-26 20:19:38.743326] 2025-08-26T20:19:38.7435021Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:38.7438317Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'serial', '--shard-id=6', '--num-shards=7', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:38.743619] 2025-08-26T20:19:52.5760352Z 2025-08-26T20:19:52.5761105Z test_ops 6/7 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_6.7_f776f0591fafa550_.log 2025-08-26T20:19:52.5761785Z Running 0 items in this shard: 2025-08-26T20:19:52.5761975Z 2025-08-26T20:19:52.5763846Z Running test_jiterator 1/1 ... [2025-08-26 20:19:52.576260] 2025-08-26T20:19:52.5764362Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:52.5767807Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jiterator.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:52.576586] 2025-08-26T20:19:55.6369735Z 2025-08-26T20:19:55.6370738Z test_jiterator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jiterator_1.1_c6f273a1e20191dc_.log 2025-08-26T20:19:55.6371477Z Running 0 items in this shard: 2025-08-26T20:19:55.6371684Z 2025-08-26T20:19:55.6373230Z Running test_ops_gradients 2/2 ... [2025-08-26 20:19:55.637201] 2025-08-26T20:19:55.6373655Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:19:55.6376884Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_gradients.py', '-m', 'serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:19:55.637500] 2025-08-26T20:20:00.7582912Z 2025-08-26T20:20:00.7583771Z test_ops_gradients 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_gradients_2.2_8d0bc23156b06c76_.log 2025-08-26T20:20:00.7584822Z Running 0 items in this shard: 2025-08-26T20:20:00.7585014Z 2025-08-26T20:20:00.7587277Z Running lazy/test_step_closures 1/1 ... [2025-08-26 20:20:00.758523] 2025-08-26T20:20:00.7587728Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:00.7590094Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_step_closures.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:00.758825] 2025-08-26T20:20:04.1276806Z 2025-08-26T20:20:04.1277768Z lazy/test_step_closures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_step_closures_1.1_300ce9b271ad47bb_.log 2025-08-26T20:20:04.1278611Z Running 0 items in this shard: 2025-08-26T20:20:04.1278811Z 2025-08-26T20:20:04.1280381Z Running test_sparse_semi_structured 1/1 ... [2025-08-26 20:20:04.127892] 2025-08-26T20:20:04.1280839Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:04.1284010Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_semi_structured.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:04.128206] 2025-08-26T20:20:10.8012299Z 2025-08-26T20:20:10.8013382Z test_sparse_semi_structured 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_semi_structured_1.1_56d9d8d084694452_.log 2025-08-26T20:20:10.8014216Z Running 0 items in this shard: 2025-08-26T20:20:10.8014446Z 2025-08-26T20:20:10.8016147Z Running nn/test_packed_sequence 1/1 ... [2025-08-26 20:20:10.801475] 2025-08-26T20:20:10.8016581Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:10.8020273Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:10.801777] 2025-08-26T20:20:13.8700117Z 2025-08-26T20:20:13.8701069Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_54eafbdf0e3f4a4d_.log 2025-08-26T20:20:13.8701873Z Running 0 items in this shard: 2025-08-26T20:20:13.8702080Z 2025-08-26T20:20:13.8703692Z Running profiler/test_record_function 1/1 ... [2025-08-26 20:20:13.870225] 2025-08-26T20:20:13.8704163Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:13.8707241Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_record_function.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:13.870516] 2025-08-26T20:20:16.9385540Z 2025-08-26T20:20:16.9386495Z profiler/test_record_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_record_function_1.1_d6c3f984c0fcde5a_.log 2025-08-26T20:20:16.9387619Z Running 0 items in this shard: 2025-08-26T20:20:16.9387821Z 2025-08-26T20:20:16.9389505Z Running nn/test_lazy_modules 1/1 ... [2025-08-26 20:20:16.938805] 2025-08-26T20:20:16.9389930Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:16.9392767Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_lazy_modules.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:16.939092] 2025-08-26T20:20:20.0073020Z 2025-08-26T20:20:20.0073803Z nn/test_lazy_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_lazy_modules_1.1_8154cc611ad21d8d_.log 2025-08-26T20:20:20.0074586Z Running 0 items in this shard: 2025-08-26T20:20:20.0074981Z 2025-08-26T20:20:20.0076569Z Running test_fx_reinplace_pass 1/1 ... [2025-08-26 20:20:20.007514] 2025-08-26T20:20:20.0077002Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:20.0079859Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_reinplace_pass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:20.007800] 2025-08-26T20:20:23.1260064Z 2025-08-26T20:20:23.1260925Z test_fx_reinplace_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_reinplace_pass_1.1_e497ee33052576a6_.log 2025-08-26T20:20:23.1261781Z Running 0 items in this shard: 2025-08-26T20:20:23.1261982Z 2025-08-26T20:20:23.1264118Z Running profiler/test_cpp_thread 1/1 ... [2025-08-26 20:20:23.126231] 2025-08-26T20:20:23.1264609Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:23.1267327Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_cpp_thread.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:23.126521] 2025-08-26T20:20:27.2460720Z 2025-08-26T20:20:27.2461676Z profiler/test_cpp_thread 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_cpp_thread_1.1_fc567cd68afaa47a_.log 2025-08-26T20:20:27.2462513Z Running 0 items in this shard: 2025-08-26T20:20:27.2462708Z 2025-08-26T20:20:27.2464958Z Running test_cuda_expandable_segments 1/1 ... [2025-08-26 20:20:27.246363] 2025-08-26T20:20:27.2465562Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:27.2469341Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_expandable_segments.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:27.246730] 2025-08-26T20:20:31.4272823Z 2025-08-26T20:20:31.4273928Z test_cuda_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_expandable_segments_1.1_b667a6b387b657c5_.log 2025-08-26T20:20:31.4274690Z 2025-08-26T20:20:31.4276752Z Running test_numba_integration 1/1 ... [2025-08-26 20:20:31.427539] 2025-08-26T20:20:31.4277200Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:31.4280945Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_numba_integration.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:31.427882] 2025-08-26T20:20:34.4960924Z 2025-08-26T20:20:34.4961944Z test_numba_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numba_integration_1.1_464f8272e640cc05_.log 2025-08-26T20:20:34.4962756Z Running 0 items in this shard: 2025-08-26T20:20:34.4962959Z 2025-08-26T20:20:34.4964649Z Running test_segment_reductions 1/1 ... [2025-08-26 20:20:34.496337] 2025-08-26T20:20:34.4965287Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:34.4968691Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:34.496679] 2025-08-26T20:20:37.5648924Z 2025-08-26T20:20:37.5650540Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_5bf0ed588416712c_.log 2025-08-26T20:20:37.5651865Z Running 0 items in this shard: 2025-08-26T20:20:37.5652181Z 2025-08-26T20:20:37.5653216Z Running test_logging 1/1 ... [2025-08-26 20:20:37.565153] 2025-08-26T20:20:37.5653819Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:37.5657308Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_logging.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:37.565493] 2025-08-26T20:20:40.6337273Z 2025-08-26T20:20:40.6338243Z test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_logging_1.1_d827cf5bb1c265eb_.log 2025-08-26T20:20:40.6338960Z Running 0 items in this shard: 2025-08-26T20:20:40.6339153Z 2025-08-26T20:20:40.6342020Z Running test_functionalization_of_rng_ops 1/1 ... [2025-08-26 20:20:40.634026] 2025-08-26T20:20:40.6342549Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:40.6345950Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_functionalization_of_rng_ops.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:40.634378] 2025-08-26T20:20:43.9027800Z 2025-08-26T20:20:43.9028810Z test_functionalization_of_rng_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_functionalization_of_rng_ops_1.1_c5e52357cf353df8_.log 2025-08-26T20:20:43.9029733Z Running 0 items in this shard: 2025-08-26T20:20:43.9029933Z 2025-08-26T20:20:43.9031680Z Running functorch/test_aot_joint_with_descriptors 1/1 ... [2025-08-26 20:20:43.903015] 2025-08-26T20:20:43.9032221Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:43.9035354Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aot_joint_with_descriptors.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:43.903321] 2025-08-26T20:20:47.1717648Z 2025-08-26T20:20:47.1718640Z functorch/test_aot_joint_with_descriptors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aot_joint_with_descriptors_1.1_e87adf31826cf4f7_.log 2025-08-26T20:20:47.1719635Z Running 0 items in this shard: 2025-08-26T20:20:47.1719840Z 2025-08-26T20:20:47.1720962Z Running test_subclass 1/1 ... [2025-08-26 20:20:47.171940] 2025-08-26T20:20:47.1721368Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:47.1724270Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_subclass.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:47.172240] 2025-08-26T20:20:50.2403427Z 2025-08-26T20:20:50.2404486Z test_subclass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_subclass_1.1_90ff680cde2b48ab_.log 2025-08-26T20:20:50.2405239Z Running 0 items in this shard: 2025-08-26T20:20:50.2405448Z 2025-08-26T20:20:50.2407261Z Running test_itt 1/1 ... [2025-08-26 20:20:50.240579] 2025-08-26T20:20:50.2407655Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:50.2410933Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_itt.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:50.240887] 2025-08-26T20:20:53.2589864Z 2025-08-26T20:20:53.2590632Z test_itt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_itt_1.1_e04041b04b608158_.log 2025-08-26T20:20:53.2591304Z Running 0 items in this shard: 2025-08-26T20:20:53.2591513Z 2025-08-26T20:20:53.2593554Z Running profiler/test_torch_tidy 1/1 ... [2025-08-26 20:20:53.259209] 2025-08-26T20:20:53.2594003Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:53.2597187Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_torch_tidy.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:53.259510] 2025-08-26T20:20:56.2775367Z 2025-08-26T20:20:56.2776223Z profiler/test_torch_tidy 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_torch_tidy_1.1_dbab6ce8d567d849_.log 2025-08-26T20:20:56.2777035Z Running 0 items in this shard: 2025-08-26T20:20:56.2777242Z 2025-08-26T20:20:56.2779010Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-08-26 20:20:56.277740] 2025-08-26T20:20:56.2779520Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:56.2782559Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:56.278049] 2025-08-26T20:20:59.3962502Z 2025-08-26T20:20:59.3963553Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_efdcfddaaa788f9f_.log 2025-08-26T20:20:59.3964519Z Running 0 items in this shard: 2025-08-26T20:20:59.3964722Z 2025-08-26T20:20:59.3966117Z Running test_bundled_inputs 1/1 ... [2025-08-26 20:20:59.396475] 2025-08-26T20:20:59.3966536Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:20:59.3970290Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_bundled_inputs.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:20:59.396819] 2025-08-26T20:21:02.5653261Z 2025-08-26T20:21:02.5654124Z test_bundled_inputs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_bundled_inputs_1.1_31d3f219954e0b04_.log 2025-08-26T20:21:02.5654883Z Running 0 items in this shard: 2025-08-26T20:21:02.5655106Z 2025-08-26T20:21:02.5657083Z Running test_masked 1/1 ... [2025-08-26 20:21:02.565557] 2025-08-26T20:21:02.5657488Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:02.5660672Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_masked.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:02.565878] 2025-08-26T20:21:06.6857044Z 2025-08-26T20:21:06.6857853Z test_masked 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_masked_1.1_951dc9f8e7ab3ed9_.log 2025-08-26T20:21:06.6858850Z Running 0 items in this shard: 2025-08-26T20:21:06.6859063Z 2025-08-26T20:21:06.6860662Z Running test_monitor 1/1 ... [2025-08-26 20:21:06.685926] 2025-08-26T20:21:06.6861059Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:06.6864298Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_monitor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:06.686233] 2025-08-26T20:21:09.7043806Z 2025-08-26T20:21:09.7044634Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_2eafec3f0a1a0def_.log 2025-08-26T20:21:09.7045364Z Running 0 items in this shard: 2025-08-26T20:21:09.7045573Z 2025-08-26T20:21:09.7047772Z Running test_sympy_utils 1/1 ... [2025-08-26 20:21:09.704619] 2025-08-26T20:21:09.7048186Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:09.7051391Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sympy_utils.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:09.704938] 2025-08-26T20:21:12.7730889Z 2025-08-26T20:21:12.7731727Z test_sympy_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sympy_utils_1.1_8ca6a8e769bf20e4_.log 2025-08-26T20:21:12.7732497Z Running 0 items in this shard: 2025-08-26T20:21:12.7732689Z 2025-08-26T20:21:12.7735276Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-08-26 20:21:12.773338] 2025-08-26T20:21:12.7735818Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:12.7738852Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:12.773661] 2025-08-26T20:21:15.8918219Z 2025-08-26T20:21:15.8919254Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_eda8ab5d015eb7e9_.log 2025-08-26T20:21:15.8920254Z Running 0 items in this shard: 2025-08-26T20:21:15.8920447Z 2025-08-26T20:21:15.8922276Z Running functorch/test_vmap_registrations 1/1 ... [2025-08-26 20:21:15.892070] 2025-08-26T20:21:15.8922768Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:15.8925914Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:15.892393] 2025-08-26T20:21:19.1106949Z 2025-08-26T20:21:19.1107938Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_1fae7adf78be1df7_.log 2025-08-26T20:21:19.1108855Z Running 0 items in this shard: 2025-08-26T20:21:19.1109050Z 2025-08-26T20:21:19.1111003Z Running torch_np/test_indexing 1/1 ... [2025-08-26 20:21:19.110959] 2025-08-26T20:21:19.1111431Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:19.1114655Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:19.111276] 2025-08-26T20:21:22.1293195Z 2025-08-26T20:21:22.1294072Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_d9530b449940c454_.log 2025-08-26T20:21:22.1294870Z Running 0 items in this shard: 2025-08-26T20:21:22.1295259Z 2025-08-26T20:21:22.1297801Z Running cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 ... [2025-08-26 20:21:22.129596] 2025-08-26T20:21:22.1298461Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:22.1301292Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:22.129913] 2025-08-26T20:21:25.1980611Z 2025-08-26T20:21:25.1981908Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.libtorch_agnostic_extension.test.test_libtorch_agnostic_1.1_b75fcb6e2a7de6b2_.log 2025-08-26T20:21:25.1983178Z Running 0 items in this shard: 2025-08-26T20:21:25.1983394Z 2025-08-26T20:21:25.1984490Z Running test_mkldnn_fusion 1/1 ... [2025-08-26 20:21:25.198310] 2025-08-26T20:21:25.1984909Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:25.1988333Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_fusion.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:25.198633] 2025-08-26T20:21:28.2166492Z 2025-08-26T20:21:28.2167322Z test_mkldnn_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_fusion_1.1_47e033ddc6ca2233_.log 2025-08-26T20:21:28.2168089Z Running 0 items in this shard: 2025-08-26T20:21:28.2168286Z 2025-08-26T20:21:28.2170747Z Running test_import_stats 1/1 ... [2025-08-26 20:21:28.216934] 2025-08-26T20:21:28.2171163Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:28.2174409Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_import_stats.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:28.217255] 2025-08-26T20:21:31.2352745Z 2025-08-26T20:21:31.2353509Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_7931217cc46aaab3_.log 2025-08-26T20:21:31.2354278Z Running 0 items in this shard: 2025-08-26T20:21:31.2354470Z 2025-08-26T20:21:31.2356891Z Running test_tensorboard 1/1 ... [2025-08-26 20:21:31.235548] 2025-08-26T20:21:31.2357317Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:31.2360624Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorboard.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:31.235866] 2025-08-26T20:21:34.6043819Z 2025-08-26T20:21:34.6044685Z test_tensorboard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorboard_1.1_27aac3cd8455fdd3_.log 2025-08-26T20:21:34.6045443Z Running 0 items in this shard: 2025-08-26T20:21:34.6045656Z 2025-08-26T20:21:34.6047778Z Running nn/test_embedding 1/1 ... [2025-08-26 20:21:34.604622] 2025-08-26T20:21:34.6048203Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:34.6051623Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_embedding.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:34.604956] 2025-08-26T20:21:37.6230050Z 2025-08-26T20:21:37.6230902Z nn/test_embedding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_embedding_1.1_e95702328da3056c_.log 2025-08-26T20:21:37.6231637Z Running 0 items in this shard: 2025-08-26T20:21:37.6232040Z 2025-08-26T20:21:37.6234134Z Running nn/test_dropout 1/1 ... [2025-08-26 20:21:37.623258] 2025-08-26T20:21:37.6234548Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:37.6237831Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_dropout.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:37.623581] 2025-08-26T20:21:40.5915302Z 2025-08-26T20:21:40.5916278Z nn/test_dropout 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_dropout_1.1_f3214d2f2a57844a_.log 2025-08-26T20:21:40.5917125Z Running 0 items in this shard: 2025-08-26T20:21:40.5917337Z 2025-08-26T20:21:40.5919753Z Running torch_np/numpy_tests/lib/test_type_check 1/1 ... [2025-08-26 20:21:40.591773] 2025-08-26T20:21:40.5920295Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:40.5923020Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_type_check.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:40.592102] 2025-08-26T20:21:43.6101414Z 2025-08-26T20:21:43.6102793Z torch_np/numpy_tests/lib/test_type_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_type_check_1.1_cf163c82c3905df9_.log 2025-08-26T20:21:43.6104494Z Running 0 items in this shard: 2025-08-26T20:21:43.6104770Z 2025-08-26T20:21:43.6105159Z Running test_public_bindings 1/1 ... [2025-08-26 20:21:43.610366] 2025-08-26T20:21:43.6105860Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:43.6109090Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_public_bindings.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:43.610681] 2025-08-26T20:21:46.5786666Z 2025-08-26T20:21:46.5787742Z test_public_bindings 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_public_bindings_1.1_424289ec15908bb0_.log 2025-08-26T20:21:46.5788524Z Running 0 items in this shard: 2025-08-26T20:21:46.5788716Z 2025-08-26T20:21:46.5790743Z Running torch_np/numpy_tests/core/test_indexing 1/1 ... [2025-08-26 20:21:46.578903] 2025-08-26T20:21:46.5791389Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:46.5794549Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_indexing.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:46.579219] 2025-08-26T20:21:49.6473579Z 2025-08-26T20:21:49.6474944Z torch_np/numpy_tests/core/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_indexing_1.1_40c3c13de0e9b00d_.log 2025-08-26T20:21:49.6475912Z Running 0 items in this shard: 2025-08-26T20:21:49.6476123Z 2025-08-26T20:21:49.6477596Z Running test_maskedtensor 1/1 ... [2025-08-26 20:21:49.647587] 2025-08-26T20:21:49.6478258Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:49.6481607Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_maskedtensor.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:49.647917] 2025-08-26T20:21:53.8174842Z 2025-08-26T20:21:53.8175955Z test_maskedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_maskedtensor_1.1_40ac2b1e2e880f0f_.log 2025-08-26T20:21:53.8176725Z Running 0 items in this shard: 2025-08-26T20:21:53.8176921Z 2025-08-26T20:21:53.8178998Z Running torch_np/numpy_tests/lib/test_histograms 1/1 ... [2025-08-26 20:21:53.817742] 2025-08-26T20:21:53.8179931Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:53.8182943Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_histograms.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:53.818061] 2025-08-26T20:21:56.8861410Z 2025-08-26T20:21:56.8862885Z torch_np/numpy_tests/lib/test_histograms 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_histograms_1.1_70d6fefa736a92dc_.log 2025-08-26T20:21:56.8863847Z Running 0 items in this shard: 2025-08-26T20:21:56.8864052Z 2025-08-26T20:21:56.8865395Z Running lazy/test_ts_opinfo 1/1 ... [2025-08-26 20:21:56.886391] 2025-08-26T20:21:56.8866051Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:21:56.8869440Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:21:56.886707] 2025-08-26T20:22:01.0061488Z 2025-08-26T20:22:01.0062343Z lazy/test_ts_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_ts_opinfo_1.1_7c975c3ab1fbce64_.log 2025-08-26T20:22:01.0063321Z Running 0 items in this shard: 2025-08-26T20:22:01.0063526Z 2025-08-26T20:22:01.0065255Z Running test_schema_check 1/1 ... [2025-08-26 20:22:01.006392] 2025-08-26T20:22:01.0065730Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:22:01.0069286Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_schema_check.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:22:01.006722] 2025-08-26T20:22:06.0776090Z 2025-08-26T20:22:06.0776913Z test_schema_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_schema_check_1.1_fe1905e4e4170dae_.log 2025-08-26T20:22:06.0777718Z Running 0 items in this shard: 2025-08-26T20:22:06.0777927Z 2025-08-26T20:22:06.0779911Z Running optim/test_optim 1/1 ... [2025-08-26 20:22:06.077848] 2025-08-26T20:22:06.0780386Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:22:06.0783823Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'optim/test_optim.py', '-m', 'serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:22:06.078180] 2025-08-26T20:22:08.9489768Z 2025-08-26T20:22:08.9490792Z optim/test_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_optim_1.1_cf567c76f7d4c7ab_.log 2025-08-26T20:22:08.9491428Z 2025-08-26T20:22:08.9493797Z Running test_quantization 2/4 ... [2025-08-26 20:22:08.949235] 2025-08-26T20:22:08.9494269Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:22:08.9497473Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:22:08.949552] 2025-08-26T20:22:13.6697760Z 2025-08-26T20:22:13.6698606Z test_quantization 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_2.4_a682355e816c8c59_.log 2025-08-26T20:22:13.6699376Z Running 0 items in this shard: 2025-08-26T20:22:13.6699587Z 2025-08-26T20:22:16.1594400Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:22:16.1596312Z import pkg_resources 2025-08-26T20:22:16.1658616Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:22:16.1660297Z import pkg_resources 2025-08-26T20:22:16.1705545Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:22:16.1707068Z import pkg_resources 2025-08-26T20:22:16.2838943Z Running inductor/test_compile_subprocess 2/2 ... [2025-08-26 20:22:16.283557] 2025-08-26T20:22:16.2839493Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:22:16.2842275Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_compile_subprocess.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:22:16.283950] 2025-08-26T20:22:16.2893919Z Running inductor/test_memory 1/1 ... [2025-08-26 20:22:16.289196] 2025-08-26T20:22:16.2894365Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:22:16.2897427Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_memory.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:22:16.289542] 2025-08-26T20:22:16.2950312Z Running test_jit 1/1 ... [2025-08-26 20:22:16.294830] 2025-08-26T20:22:16.2950708Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:22:16.2953737Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:22:16.295147] 2025-08-26T20:22:23.4002301Z 2025-08-26T20:22:23.4003523Z inductor/test_memory 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_memory_1.1_c4e980737d7e1ae9_.log 2025-08-26T20:22:23.4004384Z 2025-08-26T20:22:27.2223010Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:22:27.2226297Z import pkg_resources 2025-08-26T20:22:27.4519643Z Running test_binary_ufuncs 1/1 ... [2025-08-26 20:22:27.451555] 2025-08-26T20:22:27.4520523Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:22:27.4524468Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_binary_ufuncs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:22:27.452101] 2025-08-26T20:23:47.6434547Z 2025-08-26T20:23:47.6435401Z test_jit 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jit_1.1_18082511a058ea77_.log 2025-08-26T20:23:47.7113429Z Running 2461 items in this shard: test/test_jit.py::TestTracer::test_call_traced_fn_from_traced_module, test/test_jit.py::TestTracer::test_call_traced_module_from_traced_module, test/test_jit.py::TestTracer::test_canonicalize_tensor_iterator, test/test_jit.py::TestTracer::test_constant, test/test_jit.py::TestTracer::test_conv, test/test_jit.py::TestTracer::test_export_no_reorder, test/test_jit.py::TestTracer::test_force_outplace_check_fill, test/test_jit.py::TestTracer::test_force_outplace_check_zero, test/test_jit.py::TestTracer::test_ge, test/test_jit.py::TestTracer::test_ge_cuda, test/test_jit.py::TestTracer::test_ge_optimized, test/test_jit.py::TestTracer::test_ge_unoptimized, test/test_jit.py::TestTracer::test_index_put, test/test_jit.py::TestTracer::test_index_put_trace_with_view, test/test_jit.py::TestTracer::test_index_put_trace_without_view, test/test_jit.py::TestTracer::test_inplace_check, test/test_jit.py::TestTracer::test_inplace_copy, test/test_jit.py::TestTracer::test_inplace_copy_force_outplace, test/test_jit.py::TestTracer::test_inplace_flags, test/test_jit.py::TestTracer::test_inplace_transplant, test/test_jit.py::TestTracer::test_inplace_warn, test/test_jit.py::TestTracer::test_input_dict_checkTrace_mut, test/test_jit.py::TestTracer::test_input_dict_empty, test/test_jit.py::TestTracer::test_input_dict_empty_list, test/test_jit.py::TestTracer::test_input_dict_insertion_order, test/test_jit.py::TestTracer::test_input_dict_of_dicts, test/test_jit.py::TestTracer::test_input_dict_of_lists, test/test_jit.py::TestTracer::test_input_dict_recursive, test/test_jit.py::TestTracer::test_input_dict_remembers_keys, test/test_jit.py::TestTracer::test_input_dict_unify, test/test_jit.py::TestTracer::test_input_flatten, test/test_jit.py::TestTracer::test_input_list_mixed_type, test/test_jit.py::TestTracer::test_input_list_of_tuples, test/test_jit.py::TestTracer::test_input_list_toplevel_flatten, test/test_jit.py::TestTracer::test_input_list_toplevel_flatten_direct, test/test_jit.py::TestTracer::test_input_tuple_of_dicts, test/test_jit.py::TestTracer::test_interpolate_trace, test/test_jit.py::TestTracer::test_large_nbr_kernel_args, test/test_jit.py::TestTracer::test_lhs_index_fails, test/test_jit.py::TestTracer::test_lhs_index_trivial, test/test_jit.py::TestTracer::test_max_pool, test/test_jit.py::TestTracer::test_nested_inplace, test/test_jit.py::TestTracer::test_non_tensor_tracing, test/test_jit.py::TestTracer::test_output_unflatten, test/test_jit.py::TestTracer::test_python_function, test/test_jit.py::TestTracer::test_python_function_tup, test/test_jit.py::TestTracer::test_repeated_input, test/test_jit.py::TestTracer::test_repeated_output, test/test_jit.py::TestTracer::test_shared_param, test/test_jit.py::TestTracer::test_simple, test/test_jit.py::TestTracer::test_tensor_with_grad_as_constant, test/test_jit.py::TestTracer::test_trace_aliased_parameter, test/test_jit.py::TestTracer::test_trace_annotation, test/test_jit.py::TestTracer::test_trace_arange, test/test_jit.py::TestTracer::test_trace_arange_with_grad, test/test_jit.py::TestTracer::test_trace_autograd_function, test/test_jit.py::TestTracer::test_trace_casts, test/test_jit.py::TestTracer::test_trace_checker_control_flow, test/test_jit.py::TestTracer::test_trace_checker_dot_data, test/test_jit.py::TestTracer::test_trace_checker_dropout_notrain, test/test_jit.py::TestTracer::test_trace_checker_dropout_train, test/test_jit.py::TestTracer::test_trace_checker_inplace_on_view, test/test_jit.py::TestTracer::test_trace_checker_memoization, test/test_jit.py::TestTracer::test_trace_checker_slice_lhs, test/test_jit.py::TestTracer::test_trace_checking_with_deprecated_name, test/test_jit.py::TestTracer::test_trace_checking_with_global_name, test/test_jit.py::TestTracer::test_trace_contiguous, test/test_jit.py::TestTracer::test_trace_contiguous_short_circuit, test/test_jit.py::TestTracer::test_trace_detach, test/test_jit.py::TestTracer::test_trace_detach_inplace, test/test_jit.py::TestTracer::test_trace_detach_inplace_redispatch, test/test_jit.py::TestTracer::test_trace_detach_redispatch, test/test_jit.py::TestTracer::test_trace_dict_input, test/test_jit.py::TestTracer::test_trace_dict_output, test/test_jit.py::TestTracer::test_trace_export_fns, test/test_jit.py::TestTracer::test_trace_export_fns_recursive, test/test_jit.py::TestTracer::test_trace_fork_join_and_module, test/test_jit.py::TestTracer::test_trace_full_dynamic_shape, test/test_jit.py::TestTracer::test_trace_func_argument_names_captured, test/test_jit.py::TestTracer::test_trace_index, test/test_jit.py::TestTracer::test_trace_index_constant, test/test_jit.py::TestTracer::test_trace_indexed_assignment, test/test_jit.py::TestTracer::test_trace_inline_shape, test/test_jit.py::TestTracer::test_trace_inverse, test/test_jit.py::TestTracer::test_trace_invert_module_hierarchy, test/test_jit.py::TestTracer::test_trace_legacy_ctor, test/test_jit.py::TestTracer::test_trace_module_argument_names_captured, test/test_jit.py::TestTracer::test_trace_modulelist, test/test_jit.py::TestTracer::test_trace_multi_output_function, test/test_jit.py::TestTracer::test_trace_namedtuple, test/test_jit.py::TestTracer::test_trace_nested_datatypes, test/test_jit.py::TestTracer::test_trace_nested_fn, test/test_jit.py::TestTracer::test_trace_no_duplicated_lifted_input_output, test/test_jit.py::TestTracer::test_trace_numel, test/test_jit.py::TestTracer::test_trace_optioanl_dtype, test/test_jit.py::TestTracer::test_trace_optional, test/test_jit.py::TestTracer::test_trace_out_operator_with_two_output, test/test_jit.py::TestTracer::test_trace_partial_func_argument_names_captured, test/test_jit.py::TestTracer::test_trace_random, test/test_jit.py::TestTracer::test_trace_records_names, test/test_jit.py::TestTracer::test_trace_save, test/test_jit.py::TestTracer::test_trace_save_load_copy, test/test_jit.py::TestTracer::test_trace_single_tuple, test/test_jit.py::TestTracer::test_trace_size, test/test_jit.py::TestTracer::test_trace_size_with_grad, test/test_jit.py::TestTracer::test_trace_skip_none_submodule, test/test_jit.py::TestTracer::test_trace_slice, test/test_jit.py::TestTracer::test_trace_slice_expr_complete_type, test/test_jit.py::TestTracer::test_trace_slice_full_dim, test/test_jit.py::TestTracer::test_trace_slice_setitem_dynamic_shape, test/test_jit.py::TestTracer::test_trace_slice_with_grad, test/test_jit.py::TestTracer::test_trace_tensor_factory, test/test_jit.py::TestTracer::test_trace_topk, test/test_jit.py::TestTracer::test_trace_tuple, test/test_jit.py::TestTracer::test_trace_variable_instantiation, test/test_jit.py::TestTracer::test_trace_warn, test/test_jit.py::TestTracer::test_trace_with_conditional_property, test/test_jit.py::TestTracer::test_trace_with_nested_strided_tensor_output, test/test_jit.py::TestTracer::test_trace_with_nested_tensor_list_output, test/test_jit.py::TestTracer::test_trace_with_number_list_output, test/test_jit.py::TestTracer::test_trace_with_tensor_list_output, test/test_jit.py::TestTracer::test_trace_with_tuple_tensor, test/test_jit.py::TestTracer::test_traced_module_cuda, test/test_jit.py::TestTracer::test_tracing_backward_hook_error, test/test_jit.py::TestTracer::test_tracing_hooks, test/test_jit.py::TestTracer::test_tracing_multiple_methods, test/test_jit.py::TestTracer::test_type_same_device, test/test_jit.py::TestTracer::test_typeas_trace_check, test/test_jit.py::TestTracer::test_wrapped_number, test/test_jit.py::TestMixTracingScripting::test_call_script_fn_from_traced_module, test/test_jit.py::TestMixTracingScripting::test_call_script_module_from_traced_module, test/test_jit.py::TestMixTracingScripting::test_call_traced_fn_from_script_fn, test/test_jit.py::TestMixTracingScripting::test_call_traced_mod_from_script_fn, test/test_jit.py::TestMixTracingScripting::test_call_tracing_fn_from_script_module, test/test_jit.py::TestMixTracingScripting::test_call_tracing_mod_from_script_module, test/test_jit.py::TestMixTracingScripting::test_jit_trace_callfunction_return_shapes, test/test_jit.py::TestMixTracingScripting::test_script_inline_trace_multiple_args, test/test_jit.py::TestMixTracingScripting::test_trace_dict_mix_script, test/test_jit.py::TestMixTracingScripting::test_trace_hierarchy, test/test_jit.py::TestMixTracingScripting::test_trace_linear, test/test_jit.py::TestMixTracingScripting::test_trace_mixed_by_script_with_dict_output, test/test_jit.py::TestMixTracingScripting::test_trace_of_script, test/test_jit.py::TestMixTracingScripting::test_trace_parameter, test/test_jit.py::TestMixTracingScripting::test_trace_returning_dict_with_tensor_tuples, test/test_jit.py::TestMixTracingScripting::test_trace_script, test/test_jit.py::TestMixTracingScripting::test_trace_script_returning_complex_dict, test/test_jit.py::TestMixTracingScripting::test_trace_with_size, test/test_jit.py::TestMixTracingScripting::test_traced_module_contains_scripted_interface_types, test/test_jit.py::TestMixTracingScripting::test_traced_module_implements_interface, test/test_jit.py::TestMixTracingScripting::test_tracing_indexing, test/test_jit.py::TestMixTracingScripting::test_tracing_slicing, test/test_jit.py::TestRecursiveScript::test_attributes, test/test_jit.py::TestRecursiveScript::test_class_compile, test/test_jit.py::TestRecursiveScript::test_constants_with_final, test/test_jit.py::TestRecursiveScript::test_dir, test/test_jit.py::TestRecursiveScript::test_error_stack, test/test_jit.py::TestRecursiveScript::test_error_stack_annotation, test/test_jit.py::TestRecursiveScript::test_error_stack_class, test/test_jit.py::TestRecursiveScript::test_error_stack_module, test/test_jit.py::TestRecursiveScript::test_failed_function_compilation, test/test_jit.py::TestRecursiveScript::test_function_attribute_in_submodule, test/test_jit.py::TestRecursiveScript::test_ignore_class, test/test_jit.py::TestRecursiveScript::test_inferred_nonetype, test/test_jit.py::TestRecursiveScript::test_init_error, test/test_jit.py::TestRecursiveScript::test_inner_traced_module, test/test_jit.py::TestRecursiveScript::test_iterable_modules, test/test_jit.py::TestRecursiveScript::test_method_call, test/test_jit.py::TestRecursiveScript::test_module_basic, test/test_jit.py::TestRecursiveScript::test_module_function_export, test/test_jit.py::TestRecursiveScript::test_module_name, test/test_jit.py::TestRecursiveScript::test_module_repr, test/test_jit.py::TestRecursiveScript::test_optional_module, test/test_jit.py::TestRecursiveScript::test_override_instance_method_ignore, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_basic, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_cycle, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_escape_hatch, test/test_jit.py::TestRecursiveScript::test_prepare_scriptable_iterable_modules, test/test_jit.py::TestRecursiveScript::test_python_function_attribute, test/test_jit.py::TestRecursiveScript::test_repeated_error_stack, test/test_jit.py::TestRecursiveScript::test_script_after_eval, test/test_jit.py::TestRecursiveScript::test_script_basic, test/test_jit.py::TestRecursiveScript::test_script_function_attribute, test/test_jit.py::TestRecursiveScript::test_script_loaded_module, test/test_jit.py::TestRecursiveScript::test_thread_safe_error_stacks, test/test_jit.py::TestTypeSharing::test_assign_python_attr, test/test_jit.py::TestTypeSharing::test_basic, test/test_jit.py::TestTypeSharing::test_builtin_function_different, test/test_jit.py::TestTypeSharing::test_builtin_function_same, test/test_jit.py::TestTypeSharing::test_constants, test/test_jit.py::TestTypeSharing::test_diff_attr_values, test/test_jit.py::TestTypeSharing::test_failed_attribute_compilation, test/test_jit.py::TestTypeSharing::test_ignored_fns, test/test_jit.py::TestTypeSharing::test_linear, test/test_jit.py::TestTypeSharing::test_loaded_modules_work, test/test_jit.py::TestTypeSharing::test_module_dict_same_type_different_name, test/test_jit.py::TestTypeSharing::test_mutate_attr_value, test/test_jit.py::TestTypeSharing::test_param_vs_attribute, test/test_jit.py::TestTypeSharing::test_python_function_attribute_different, test/test_jit.py::TestTypeSharing::test_python_function_attribute_same, test/test_jit.py::TestTypeSharing::test_same_but_different_classes, test/test_jit.py::TestTypeSharing::test_script_function_attribute_different, test/test_jit.py::TestTypeSharing::test_script_function_attribute_same, test/test_jit.py::TestTypeSharing::test_script_module_containing_traced_module, test/test_jit.py::TestTypeSharing::test_submodules, test/test_jit.py::TestTypeSharing::test_tracing_gives_different_types, test/test_jit.py::TestTypeSharing::test_type_not_shared_ignored_attributes, test/test_jit.py::TestTypeSharing::test_type_shared_ignored_attributes, test/test_jit.py::TestTypeSharing::test_type_sharing_define_in_init, test/test_jit.py::TestTypeSharing::test_type_sharing_disabled, test/test_jit.py::TestLogging::test_bump_numeric_counter, test/test_jit.py::TestLogging::test_counter_aggregation, test/test_jit.py::TestLogging::test_logging_levels_set, test/test_jit.py::TestLogging::test_time_measurement_counter, test/test_jit.py::TestLogging::test_time_measurement_counter_script, test/test_jit.py::TestLogging::test_trace_numeric_counter, test/test_jit.py::TestBackends::test_errors, test/test_jit.py::TestBackends::test_execution, test/test_jit.py::TestBackends::test_save_load, test/test_jit.py::TestBackendsWithCompiler::test_errors, test/test_jit.py::TestBackendsWithCompiler::test_execution, test/test_jit.py::TestNnapiBackend::test_adaptive_avg_pool2d, test/test_jit.py::TestNnapiBackend::test_avg_pool2d, test/test_jit.py::TestNnapiBackend::test_cat, test/test_jit.py::TestNnapiBackend::test_compile_spec_santiy, test/test_jit.py::TestNnapiBackend::test_conv2d, test/test_jit.py::TestNnapiBackend::test_conv2d_transpose, test/test_jit.py::TestNnapiBackend::test_dequantize, test/test_jit.py::TestNnapiBackend::test_detach, test/test_jit.py::TestNnapiBackend::test_flatten, test/test_jit.py::TestNnapiBackend::test_hardtanh, test/test_jit.py::TestNnapiBackend::test_linear, test/test_jit.py::TestNnapiBackend::test_log_softmax, test/test_jit.py::TestNnapiBackend::test_max_pool2d, test/test_jit.py::TestNnapiBackend::test_mean, test/test_jit.py::TestNnapiBackend::test_multi_output, test/test_jit.py::TestNnapiBackend::test_pointwise_binary, test/test_jit.py::TestNnapiBackend::test_pointwise_binary_const, test/test_jit.py::TestNnapiBackend::test_pointwise_unary, test/test_jit.py::TestNnapiBackend::test_prelu, test/test_jit.py::TestNnapiBackend::test_qadd, test/test_jit.py::TestNnapiBackend::test_qlinear, test/test_jit.py::TestNnapiBackend::test_quantize, test/test_jit.py::TestNnapiBackend::test_reshape, test/test_jit.py::TestNnapiBackend::test_seblock_mul, test/test_jit.py::TestNnapiBackend::test_slice, test/test_jit.py::TestNnapiBackend::test_softmax, test/test_jit.py::TestNnapiBackend::test_tensor_input, test/test_jit.py::TestNnapiBackend::test_to, test/test_jit.py::TestNnapiBackend::test_unsqueeze, test/test_jit.py::TestNnapiBackend::test_upsample_nearest2d, test/test_jit.py::TestList::test_comprehension_iterable, test/test_jit.py::TestList::test_comprehension_out_type_not_in_type, test/test_jit.py::TestList::test_comprehensions_basic, test/test_jit.py::TestList::test_comprehensions_basic_float, test/test_jit.py::TestList::test_comprehensions_two_comps, test/test_jit.py::TestList::test_copy_list_immutable, test/test_jit.py::TestList::test_copy_list_mutable, test/test_jit.py::TestList::test_del, test/test_jit.py::TestList::test_dict_keyword_is_correctly_typed, test/test_jit.py::TestList::test_dict_keyword_with_dict_comprehension, test/test_jit.py::TestList::test_dict_keyword_with_dict_comprehension_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_empty_dict_comprehension, test/test_jit.py::TestList::test_dict_keyword_with_empty_iterable, test/test_jit.py::TestList::test_dict_keyword_with_internal_aggregate_function, test/test_jit.py::TestList::test_dict_keyword_with_iterable, test/test_jit.py::TestList::test_dict_keyword_with_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_kwargs_using_container_values, test/test_jit.py::TestList::test_dict_keyword_with_mapping, test/test_jit.py::TestList::test_dict_keyword_with_mapping_and_kwargs, test/test_jit.py::TestList::test_dict_keyword_with_mismatched_annotations, test/test_jit.py::TestList::test_dict_keyword_with_nested_call, test/test_jit.py::TestList::test_dict_keyword_with_previously_declared_variable, test/test_jit.py::TestList::test_dict_keyword_with_previously_declared_variable_and_kwargs, test/test_jit.py::TestList::test_extend_list_immutable, test/test_jit.py::TestList::test_extend_list_mutable, test/test_jit.py::TestList::test_in_check, test/test_jit.py::TestList::test_list_bool_conversion, test/test_jit.py::TestList::test_list_count, test/test_jit.py::TestList::test_list_count_not_existing, test/test_jit.py::TestList::test_list_gather, test/test_jit.py::TestList::test_list_index, test/test_jit.py::TestList::test_list_index_not_existing, test/test_jit.py::TestList::test_list_keyword, test/test_jit.py::TestList::test_list_len, test/test_jit.py::TestList::test_list_literal, test/test_jit.py::TestList::test_list_none, test/test_jit.py::TestList::test_list_ops, test/test_jit.py::TestList::test_list_slice, test/test_jit.py::TestList::test_list_sort, test/test_jit.py::TestList::test_list_unification_hint, test/test_jit.py::TestList::test_list_variance, test/test_jit.py::TestList::test_min_bool_list, test/test_jit.py::TestList::test_min_max_list, test/test_jit.py::TestList::test_min_max_single_list, test/test_jit.py::TestList::test_mutable_list_append, test/test_jit.py::TestList::test_mutable_list_append_2, test/test_jit.py::TestList::test_mutable_list_append_if, test/test_jit.py::TestList::test_mutable_list_append_if_else, test/test_jit.py::TestList::test_mutable_list_append_loop, test/test_jit.py::TestList::test_mutable_list_append_loop_if, test/test_jit.py::TestList::test_mutable_list_clear, test/test_jit.py::TestList::test_mutable_list_clear_empty, test/test_jit.py::TestList::test_mutable_list_function_inline, test/test_jit.py::TestList::test_mutable_list_insert, test/test_jit.py::TestList::test_mutable_list_insert_neg_out_of_bounds, test/test_jit.py::TestList::test_mutable_list_insert_negative, test/test_jit.py::TestList::test_mutable_list_insert_out_of_bounds, test/test_jit.py::TestList::test_mutable_list_nested_loop, test/test_jit.py::TestList::test_mutable_list_pop, test/test_jit.py::TestList::test_mutable_list_pop2, test/test_jit.py::TestList::test_mutable_list_pop_at, test/test_jit.py::TestList::test_mutable_list_pop_at2, test/test_jit.py::TestList::test_mutable_list_pop_at_negative, test/test_jit.py::TestList::test_mutable_list_pop_at_negative2, test/test_jit.py::TestList::test_mutable_list_pop_empty, test/test_jit.py::TestList::test_mutable_list_pop_slice, test/test_jit.py::TestList::test_mutable_list_remove, test/test_jit.py::TestList::test_mutable_list_remove2, test/test_jit.py::TestList::test_mutable_list_remove_not_existing, test/test_jit.py::TestList::test_mutable_list_remove_tensor, test/test_jit.py::TestList::test_mutable_list_reverse, test/test_jit.py::TestList::test_mutable_list_reverse_empty, test/test_jit.py::TestList::test_mutable_tensor_list_reverse, test/test_jit.py::TestList::test_no_element_type_annotation, test/test_jit.py::TestList::test_slice_index, test/test_jit.py::TestList::test_tensor_list_count, test/test_jit.py::TestList::test_tensor_list_count_not_existing, test/test_jit.py::TestList::test_tensor_list_index, test/test_jit.py::TestList::test_tensor_list_index_not_existing, test/test_jit.py::TestList::test_to_list, test/test_jit.py::TestList::test_to_list_gpu, test/test_jit.py::TestDict::test_aug_assign, test/test_jit.py::TestDict::test_basic, test/test_jit.py::TestDict::test_clear, test/test_jit.py::TestDict::test_copy, test/test_jit.py::TestDict::test_del, test/test_jit.py::TestDict::test_dict_bool_conversion, test/test_jit.py::TestDict::test_dict_preserves_order, test/test_jit.py::TestDict::test_dict_to_python, test/test_jit.py::TestDict::test_dict_variance, test/test_jit.py::TestDict::test_get, test/test_jit.py::TestDict::test_get_boolkey, test/test_jit.py::TestDict::test_items, test/test_jit.py::TestDict::test_key_type, test/test_jit.py::TestDict::test_keys, test/test_jit.py::TestDict::test_len, test/test_jit.py::TestDict::test_loop, test/test_jit.py::TestDict::test_membership, test/test_jit.py::TestDict::test_mutability, test/test_jit.py::TestDict::test_optional_dict_construct, test/test_jit.py::TestDict::test_ordered_dict, test/test_jit.py::TestDict::test_pop, test/test_jit.py::TestDict::test_popitem, test/test_jit.py::TestDict::test_setdefault, test/test_jit.py::TestDict::test_type_annotation_missing_contained_type, test/test_jit.py::TestDict::test_update, test/test_jit.py::TestDict::test_update_existing_key, test/test_jit.py::TestDict::test_values, test/test_jit.py::TestDict::test_view, test/test_jit.py::TestNamedTuple::test_namedtuple, test/test_jit.py::TestNamedTuple::test_namedtuple_as_attr, test/test_jit.py::TestNamedTuple::test_namedtuple_constant, test/test_jit.py::TestNamedTuple::test_namedtuple_input_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_inside_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_kwarg_construct, test/test_jit.py::TestNamedTuple::test_namedtuple_lower, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution, test/test_jit.py::TestNamedTuple::test_namedtuple_resolution_forwardref, test/test_jit.py::TestNamedTuple::test_namedtuple_serialization, test/test_jit.py::TestNamedTuple::test_namedtuple_slice_unpack, test/test_jit.py::TestNamedTuple::test_namedtuple_type_annotation, test/test_jit.py::TestNamedTuple::test_namedtuple_wrong_types, test/test_jit.py::TestNamedTuple::test_return_named_tuple, test/test_jit.py::TestScriptDict::test_bool, test/test_jit.py::TestScriptDict::test_contains, test/test_jit.py::TestScriptDict::test_delitem, 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test/test_jit.py::TestClassType::test_optional_type_promotion, test/test_jit.py::TestClassType::test_out_of_order_methods, test/test_jit.py::TestClassType::test_overloaded_fn, test/test_jit.py::TestClassType::test_properties, test/test_jit.py::TestClassType::test_py_class_to_ivalue_missing_attribute, test/test_jit.py::TestClassType::test_python_interop, test/test_jit.py::TestClassType::test_recursive_class, test/test_jit.py::TestClassType::test_recursive_script_builtin_type_resolution, test/test_jit.py::TestClassType::test_recursive_script_module_builtin_type_resolution, test/test_jit.py::TestClassType::test_recursive_scripting, test/test_jit.py::TestClassType::test_recursive_scripting_failed, test/test_jit.py::TestClassType::test_reference_semantics, test/test_jit.py::TestClassType::test_save_load_with_classes, test/test_jit.py::TestClassType::test_save_load_with_classes_nested, test/test_jit.py::TestClassType::test_save_load_with_classes_returned, test/test_jit.py::TestClassType::test_schema_human_readable, test/test_jit.py::TestClassType::test_self_referential_method, test/test_jit.py::TestClassType::test_set_attr_in_method, test/test_jit.py::TestClassType::test_set_attr_non_initialized, test/test_jit.py::TestClassType::test_set_attr_type_mismatch, test/test_jit.py::TestClassType::test_staticmethod, test/test_jit.py::TestClassType::test_type_annotation, test/test_jit.py::TestClassType::test_type_annotations, test/test_jit.py::TestClassType::test_unresolved_class_attributes, test/test_jit.py::TestClassType::test_unused_method, test/test_jit.py::TestBuiltins::test_del, test/test_jit.py::TestBuiltins::test_del_multiple_operands, test/test_jit.py::TestBuiltins::test_has_attr, test/test_jit.py::TestBuiltins::test_has_attr_invalid_args, test/test_jit.py::TestBuiltins::test_torch_check, test/test_jit.py::TestBuiltins::test_torch_check_invalid_args, test/test_jit.py::TestTensorBuiltins::test_method_on_number, test/test_jit.py::TestTensorBuiltins::test_scalar_to_num_conversions, test/test_jit.py::TestTensorBuiltins::test_tensor_item, test/test_jit.py::TestTensorBuiltins::test_tensor_properties, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign, test/test_jit.py::TestTensorBuiltins::test_tensor_subscript_assign_device, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_inp_out, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_inp, test/test_jit.py::TestIgnoreContextManager::test_with_ignore_context_manager_with_just_out, test/test_jit.py::TestSymbolicShapeAnalysis::test_adaptive_avg_pool2d, test/test_jit.py::TestSymbolicShapeAnalysis::test_arange_shape, test/test_jit.py::TestSymbolicShapeAnalysis::test_binary_shape_fns_inplace, test/test_jit.py::TestSymbolicShapeAnalysis::test_binary_shape_functions, test/test_jit.py::TestSymbolicShapeAnalysis::test_conv_deconv, test/test_jit.py::TestSymbolicShapeAnalysis::test_convolution_backward, test/test_jit.py::TestSymbolicShapeAnalysis::test_cross_entropy_loss, test/test_jit.py::TestSymbolicShapeAnalysis::test_if_propagation, test/test_jit.py::TestSymbolicShapeAnalysis::test_partial_eval_graph_conv, test/test_jit.py::TestSymbolicShapeAnalysis::test_partial_eval_stitching, test/test_jit.py::TestSymbolicShapeAnalysis::test_refinement_through_graph_stitching, test/test_jit.py::TestSymbolicShapeAnalysis::test_register_function_error_checking, test/test_jit.py::TestSymbolicShapeAnalysis::test_returning_input_symbolic_shapes, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_analysis, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_concat, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_embedding_bag, test/test_jit.py::TestSymbolicShapeAnalysis::test_shape_function_includes, test/test_jit.py::TestSymbolicShapeAnalysis::test_shared_shape_graph, test/test_jit.py::TestSymbolicShapeAnalysis::test_size_and_sizes, test/test_jit.py::TestSymbolicShapeAnalysis::test_squeeze_dims, test/test_jit.py::TestSymbolicShapeAnalysis::test_stitching_concat, test/test_jit.py::TestSymbolicShapeAnalysis::test_stitching_multi_output, test/test_jit.py::TestSymbolicShapeAnalysis::test_sym_ir_parsing, test/test_jit.py::TestSymbolicShapeAnalysis::test_unary_shape_fns_inplace, test/test_jit.py::TestSymbolicShapeAnalysis::test_unary_shape_functions, test/test_jit.py::TestSymbolicShapeAnalysis::test_write, test/test_jit.py::TestOpDecompositions::test_op_decomposition, test/test_jit.py::TestOpDecompositions::test_registered_decomposition, test/test_jit.py::TestUnsupportedOps::test_factory_ops_requires_grad_fail, test/test_jit.py::TestUnsupportedOps::test_init_ops, test/test_jit.py::TestFreezing::test_freeze_interface_swapping_two_methods, test/test_jit.py::TestFreezing::test_freeze_interface_within_object, test/test_jit.py::TestFreezing::test_freeze_module, test/test_jit.py::TestFreezing::test_freeze_module_detach_gradient, test/test_jit.py::TestFreezing::test_freeze_module_in_training_mode, test/test_jit.py::TestFreezing::test_freeze_module_inlining, test/test_jit.py::TestFreezing::test_freeze_module_no_forward, test/test_jit.py::TestFreezing::test_freeze_module_return_self, test/test_jit.py::TestFreezing::test_freeze_module_return_sub_module, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr2, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_attr3, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr2, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr3, test/test_jit.py::TestFreezing::test_freeze_module_with_aliased_tensor_attr4, test/test_jit.py::TestFreezing::test_freeze_module_with_call_method, test/test_jit.py::TestFreezing::test_freeze_module_with_fork, test/test_jit.py::TestFreezing::test_freeze_module_with_fork2, test/test_jit.py::TestFreezing::test_freeze_module_with_fork_calling_module_method, test/test_jit.py::TestFreezing::test_freeze_module_with_helperfunction, test/test_jit.py::TestFreezing::test_freeze_module_with_inplace_mutable, test/test_jit.py::TestFreezing::test_freeze_module_with_list, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_dict, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_list, test/test_jit.py::TestFreezing::test_freeze_module_with_mutable_tensor, test/test_jit.py::TestFreezing::test_freeze_module_with_nested_fork, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasing, test/test_jit.py::TestFreezing::test_freeze_module_with_nestedaliasingscalar, test/test_jit.py::TestFreezing::test_freeze_module_with_non_static_module_container_index, test/test_jit.py::TestFreezing::test_freeze_module_with_overlapping_attrs, test/test_jit.py::TestFreezing::test_freeze_module_with_preserve_sub_module, test/test_jit.py::TestFreezing::test_freeze_module_with_preserve_sub_module_and_mutation, test/test_jit.py::TestFreezing::test_freeze_module_with_sharedclasstype, test/test_jit.py::TestFreezing::test_freeze_module_with_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_tensor, test/test_jit.py::TestFreezing::test_freeze_module_with_tuple, test/test_jit.py::TestFreezing::test_freeze_module_with_tupleoutput_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attr, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attribute_on_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_attribute_on_unused_submodule, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method2, test/test_jit.py::TestFreezing::test_freeze_module_with_user_preserved_method_on_submodule, test/test_jit.py::TestFreezing::test_freeze_no_forward, test/test_jit.py::TestFreezing::test_freeze_non_interface_module_swap, test/test_jit.py::TestFreezing::test_freeze_non_module_class_getattr, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces_same_name, test/test_jit.py::TestFreezing::test_freeze_recursive_interfaces_with_reassignment, test/test_jit.py::TestFreezing::test_freeze_with_interface_mutable, test/test_jit.py::TestFreezing::test_freeze_with_swapping_interfaces, test/test_jit.py::TestFreezing::test_module_getattr_indirection, test/test_jit.py::TestFreezing::test_module_with_shared_type_instances, test/test_jit.py::TestFrozenOptimizations::test_bn_not_broadcast_with_linear, test/test_jit.py::TestFrozenOptimizations::test_collapse_adjacent_conversions, test/test_jit.py::TestFrozenOptimizations::test_conv_add_folding, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding_autocast_scenario_cuda, test/test_jit.py::TestFrozenOptimizations::test_conv_bn_folding_not_forward, test/test_jit.py::TestFrozenOptimizations::test_conv_hardswish, test/test_jit.py::TestFrozenOptimizations::test_conv_mul_add_bn, test/test_jit.py::TestFrozenOptimizations::test_conv_to_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_conv_to_mkldnn_no_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion, test/test_jit.py::TestFrozenOptimizations::test_freeze_conv_relu_fusion_not_forward, test/test_jit.py::TestFrozenOptimizations::test_freeze_mkdlnn, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_dropout, test/test_jit.py::TestFrozenOptimizations::test_freeze_remove_feature_dropout, test/test_jit.py::TestFrozenOptimizations::test_hardswish_hardsigmoid, test/test_jit.py::TestFrozenOptimizations::test_incompatible_perf_formats, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding, test/test_jit.py::TestFrozenOptimizations::test_linear_bn_folding_autocast_scenario_cuda, test/test_jit.py::TestFrozenOptimizations::test_linear_concat, test/test_jit.py::TestFrozenOptimizations::test_linear_concat_complex, test/test_jit.py::TestFrozenOptimizations::test_linear_concat_different_input, test/test_jit.py::TestFrozenOptimizations::test_linear_multiple_blocks, test/test_jit.py::TestFrozenOptimizations::test_linear_non_constant_weight, test/test_jit.py::TestFrozenOptimizations::test_linear_transpose, test/test_jit.py::TestFrozenOptimizations::test_maxpool_mkldnn, test/test_jit.py::TestFrozenOptimizations::test_mkldnn_fuser_broadcasting, test/test_jit.py::TestFrozenOptimizations::test_mkldnn_inplace_removal, test/test_jit.py::TestFrozenOptimizations::test_numel_less_than_size_with_padding, test/test_jit.py::TestFrozenOptimizations::test_optimize_freeze_module, test/test_jit.py::TestFrozenOptimizations::test_pool2d_batchnorm, test/test_jit.py::TestFrozenOptimizations::test_pool3d_batchnorm, test/test_jit.py::TestFrozenOptimizations::test_remove_detach, test/test_jit.py::TestFrozenOptimizations::test_remove_detach_not_applied, test/test_jit.py::TestFrozenOptimizations::test_scalar_mul, test/test_jit.py::TestMKLDNNReinplacing::test_always_alive_values, test/test_jit.py::TestMKLDNNReinplacing::test_merge_liveness, test/test_jit.py::TestMKLDNNReinplacing::test_successful, test/test_jit.py::TestMKLDNNReinplacing::test_switch_inputs_to_inplace, test/test_jit.py::TestPeephole::test_conv_dim_folding, test/test_jit.py::TestPeephole::test_integer_refinement, test/test_jit.py::TestPeephole::test_noop_peephole, test/test_jit.py::TestPeephole::test_normalized_is_op, test/test_jit.py::TestPeephole::test_normalized_isnot_op, test/test_jit.py::TestPeephole::test_normalized_rsub, test/test_jit.py::TestPeephole::test_optimize_out_comparison_same_value, test/test_jit.py::TestPeephole::test_peephole, test/test_jit.py::TestPeephole::test_peephole_add_zero, test/test_jit.py::TestPeephole::test_peephole_arith, test/test_jit.py::TestPeephole::test_peephole_cuda, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_dict_modified, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_get_input_arg, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_missing_key, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_overlapping_keys, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dict_getitem_simple, test/test_jit.py::TestPeephole::test_peephole_dict_len, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_keys_might_overlap, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_overlapping_keys, test/test_jit.py::TestPeephole::test_peephole_dict_len_no_optimization_unsupported_type, test/test_jit.py::TestPeephole::test_peephole_dynamic, test/test_jit.py::TestPeephole::test_peephole_int, test/test_jit.py::TestPeephole::test_peephole_len_list, test/test_jit.py::TestPeephole::test_peephole_list_len, test/test_jit.py::TestPeephole::test_peephole_list_ops, test/test_jit.py::TestPeephole::test_peephole_no_output_aliasing, test/test_jit.py::TestPeephole::test_peephole_optional_refine, test/test_jit.py::TestPeephole::test_peephole_slice_all_three_args, test/test_jit.py::TestPeephole::test_peephole_slice_one_empty_arg, test/test_jit.py::TestPeephole::test_peephole_slice_optimization_not_applied_list_modified, test/test_jit.py::TestPeephole::test_peephole_slice_optimization_not_applied_non_const_args, test/test_jit.py::TestPeephole::test_peephole_slice_two_empty_args, test/test_jit.py::TestPeephole::test_peephole_type_refinements, test/test_jit.py::TestPeephole::test_peephole_with_non_output_writes, test/test_jit.py::TestPeephole::test_peephole_with_writes, test/test_jit.py::TestPeephole::test_refine_integer_values, test/test_jit.py::TestPeephole::test_short_circuit_optimization, test/test_jit.py::TestAliasAnalysis::test_becomes_wildcard_annotations, test/test_jit.py::TestAliasAnalysis::test_multiple_compilation_units, test/test_jit.py::TestAliasAnalysis::test_nested_list_construct_not_wildcard, test/test_jit.py::TestAliasAnalysis::test_recursive_calls, test/test_jit.py::TestSaveLoad::test_different_functions, test/test_jit.py::TestSaveLoad::test_different_interfaces, test/test_jit.py::TestSaveLoad::test_different_modules, test/test_jit.py::TestSaveLoad::test_many_collisions, test/test_jit.py::TestSaveLoad::test_save_load_large_string_attribute, test/test_jit.py::TestSaveLoad::test_save_load_meta_tensors, test/test_jit.py::TestSaveLoad::test_save_load_meta_tensors_to_device, test/test_jit.py::TestSaveLoad::test_save_load_params_buffers_submodules, test/test_jit.py::TestSaveLoad::test_save_load_using_pathlib, test/test_jit.py::TestSaveLoad::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoad::test_save_load_with_saved_traced_inputs, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoad::test_save_namedtuple_input_only_forwardref, test/test_jit.py::TestSaveLoad::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoad::test_save_nonexit_file, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_functions, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_interfaces, test/test_jit.py::TestSaveLoadFlatbuffer::test_different_modules, test/test_jit.py::TestSaveLoadFlatbuffer::test_many_collisions, test/test_jit.py::TestSaveLoadFlatbuffer::test_module_info_flatbuffer, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_params_buffers_submodules, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_using_pathlib, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_load_with_extra_files, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_input_only, test/test_jit.py::TestSaveLoadFlatbuffer::test_save_namedtuple_output_only, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_inplace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_reciprocal, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_scalar_scalar, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor_inplace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_div_tensor_out, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_linspace_out, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_logspace, test/test_jit.py::TestSaveLoadForOpVersion::test_versioned_logspace_out, test/test_jit.py::TestModuleContainers::test_custom_container_forward, test/test_jit.py::TestModuleContainers::test_empty_dict_override_contains, test/test_jit.py::TestModuleContainers::test_module_inplace_construct, test/test_jit.py::TestModuleContainers::test_module_interface_special_methods, test/test_jit.py::TestModuleContainers::test_module_properties, test/test_jit.py::TestModuleContainers::test_moduledict, test/test_jit.py::TestModuleContainers::test_moduledict_getitem, test/test_jit.py::TestModuleContainers::test_moduledict_keyerror, test/test_jit.py::TestModuleContainers::test_normal_list_attribute_with_modules_error, test/test_jit.py::TestModuleContainers::test_parameterdict_script_getitem, test/test_jit.py::TestModuleContainers::test_parameterlist_script_getitem, test/test_jit.py::TestModuleContainers::test_parameterlist_script_iter, test/test_jit.py::TestModuleContainers::test_script_module_list_sequential, test/test_jit.py::TestModuleContainers::test_script_modulelist_index, test/test_jit.py::TestModuleContainers::test_sequential_intermediary_types, test/test_jit.py::TestModuleContainers::test_special_method_with_override, test/test_jit.py::TestModuleContainers::test_typed_module_dict, test/test_jit.py::TestModuleContainers::test_typed_module_list, test/test_jit.py::TestPythonBindings::test_add_input, test/test_jit.py::TestPythonBindings::test_aliasdb, test/test_jit.py::TestPythonBindings::test_canonicalize, test/test_jit.py::TestPythonBindings::test_cu_create_function, test/test_jit.py::TestPythonBindings::test_cu_get_functions, test/test_jit.py::TestPythonBindings::test_graph_create, test/test_jit.py::TestPythonBindings::test_graph_iterator_keepalive, test/test_jit.py::TestPythonBindings::test_invalidation, test/test_jit.py::TestPythonIr::test_param_strides, test/test_jit.py::TestPythonIr::test_permute_inputs_binding, test/test_jit.py::TestPythonIr::test_python_ir_utils, test/test_jit.py::TestPythonIr::test_python_ir_utils_graph, test/test_jit.py::TestFunctionalBlocks::test_subgraph_creation, test/test_jit.py::TestRemoveMutation::test_aten_inplace, test/test_jit.py::TestRemoveMutation::test_common_pytorch_list_ops, test/test_jit.py::TestRemoveMutation::test_if_output, test/test_jit.py::TestRemoveMutation::test_if_output_fail, test/test_jit.py::TestRemoveMutation::test_list_indexing_removal, test/test_jit.py::TestRemoveMutation::test_lists_append, test/test_jit.py::TestRemoveMutation::test_lists_insert, test/test_jit.py::TestRemoveMutation::test_special_mapped_op, test/test_jit.py::TestTorchbind::test_default_args, test/test_jit.py::TestTorchbind::test_hasattr, test/test_jit.py::TestTorchbind::test_lambda_as_constructor, test/test_jit.py::TestTorchbind::test_profiler_custom_op, test/test_jit.py::TestTorchbind::test_staticmethod, test/test_jit.py::TestTorchbind::test_torchbind, test/test_jit.py::TestTorchbind::test_torchbind_attr_exception, test/test_jit.py::TestTorchbind::test_torchbind_class_attr_recursive, test/test_jit.py::TestTorchbind::test_torchbind_class_attribute, test/test_jit.py::TestTorchbind::test_torchbind_deepcopy, test/test_jit.py::TestTorchbind::test_torchbind_def_property_getter_setter, test/test_jit.py::TestTorchbind::test_torchbind_def_property_just_getter, test/test_jit.py::TestTorchbind::test_torchbind_def_property_readwrite, test/test_jit.py::TestTorchbind::test_torchbind_getattr, test/test_jit.py::TestTorchbind::test_torchbind_getstate, test/test_jit.py::TestTorchbind::test_torchbind_instantiate_missing_class, test/test_jit.py::TestTorchbind::test_torchbind_lambda_method, test/test_jit.py::TestTorchbind::test_torchbind_no_init, test/test_jit.py::TestTorchbind::test_torchbind_optional_explicit_attr, test/test_jit.py::TestTorchbind::test_torchbind_pass_wrong_type, test/test_jit.py::TestTorchbind::test_torchbind_pickle_serialization, test/test_jit.py::TestTorchbind::test_torchbind_python_deepcopy, test/test_jit.py::TestTorchbind::test_torchbind_return_instance, test/test_jit.py::TestTorchbind::test_torchbind_return_instance_from_method, test/test_jit.py::TestTorchbind::test_torchbind_return_tuple, test/test_jit.py::TestTorchbind::test_torchbind_save_load, test/test_jit.py::TestTorchbind::test_torchbind_take_as_arg, test/test_jit.py::TestTorchbind::test_torchbind_take_instance_as_method_arg, test/test_jit.py::TestTorchbind::test_torchbind_tracing, test/test_jit.py::TestTorchbind::test_torchbind_tracing_nested, test/test_jit.py::TestModuleInterface::test_freeze_module_with_inplace_mutation_in_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_interface_and_fork, test/test_jit.py::TestModuleInterface::test_freeze_module_with_mutated_interface, test/test_jit.py::TestModuleInterface::test_freeze_module_with_setattr_in_interface, test/test_jit.py::TestModuleInterface::test_module_apis_interface, test/test_jit.py::TestModuleInterface::test_module_doc_string, test/test_jit.py::TestModuleInterface::test_module_interface, test/test_jit.py::TestModuleInterface::test_module_interface_inheritance, test/test_jit.py::TestModuleInterface::test_module_interface_subtype, test/test_jit.py::TestModuleInterface::test_module_swap, test/test_jit.py::TestModuleInterface::test_module_swap_no_lazy_compile, test/test_jit.py::TestModuleInterface::test_module_swap_no_module_interface, test/test_jit.py::TestModuleInterface::test_module_swap_wrong_module, test/test_jit.py::TestModuleInterface::test_not_submodule_interface_call, test/test_jit.py::TestModuleInterface::test_script_module_as_interface_swap, test/test_jit.py::TestWith::test_with_as, test/test_jit.py::TestWith::test_with_errors, test/test_jit.py::TestWith::test_with_exceptions, test/test_jit.py::TestWith::test_with_no_as, test/test_jit.py::TestWith::test_with_no_grad, test/test_jit.py::TestWith::test_with_record_function, test/test_jit.py::TestEnum::test_closed_over_enum_constant, test/test_jit.py::TestEnum::test_enum_as_const, test/test_jit.py::TestEnum::test_enum_as_module_attribute, test/test_jit.py::TestEnum::test_enum_comp, test/test_jit.py::TestEnum::test_enum_comp_diff_classes, test/test_jit.py::TestEnum::test_enum_explicit_script, test/test_jit.py::TestEnum::test_enum_iterate, test/test_jit.py::TestEnum::test_enum_ivalue_type, test/test_jit.py::TestEnum::test_enum_module_return, test/test_jit.py::TestEnum::test_enum_name, test/test_jit.py::TestEnum::test_enum_return, test/test_jit.py::TestEnum::test_enum_value, test/test_jit.py::TestEnum::test_enum_value_types, test/test_jit.py::TestEnum::test_heterogenous_value_type_enum_error, test/test_jit.py::TestEnum::test_non_existent_enum_value, test/test_jit.py::TestEnum::test_string_enum_as_module_attribute, test/test_jit.py::TestEnum::test_typed_enum, test/test_jit.py::TestStringFormatting::test_modulo_operator, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_alternate_digit_placeholder, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_capital_exponent_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_char_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_char_placeholder_and_true_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_digit_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_double_percent_in_string, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_exponent_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_float_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_float_placeholder_and_float_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_lowercase_exponent_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_multiple_placeholders, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_percent_in_string, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_digit_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_format_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_string_placeholder_and_string_variable, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_subscript, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_too_few_arguments, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_too_many_arguments, test/test_jit.py::TestStringFormatting::test_string_interpolation_with_unknown_format_specifier, test/test_jit.py::TestProfiler::test_aliasing_merge, test/test_jit.py::TestProfiler::test_autograd_fallback_graph, test/test_jit.py::TestProfiler::test_fallback_graph_not_specialized, test/test_jit.py::TestProfiler::test_iterative_fusion, test/test_jit.py::TestProfiler::test_local_fusion_strategy, test/test_jit.py::TestProfiler::test_not_fusing_scalar_ops, test/test_jit.py::TestProfiler::test_not_optimizing_property, test/test_jit.py::TestProfiler::test_specialize_backward, test/test_jit.py::TestProfiler::test_specialized_types, test/test_jit.py::TestProfiler::test_tensor_constant, test/test_jit.py::TestProfiler::test_tensor_type_not_determined_by_inputs, test/test_jit.py::TestProfiler::test_use_not_profiled, test/test_jit.py::TestSlice::test_module_list_slicing, test/test_jit.py::TestSlice::test_slice_as_variable, test/test_jit.py::TestSlice::test_slice_dynamic_index, test/test_jit.py::TestSlice::test_slice_kwarg, test/test_jit.py::TestSlice::test_slice_one_none, test/test_jit.py::TestSlice::test_slice_start_stop, test/test_jit.py::TestSlice::test_slice_start_stop_step, test/test_jit.py::TestSlice::test_slice_start_stop_with_none, test/test_jit.py::TestSlice::test_slice_stop_clipped, test/test_jit.py::TestSlice::test_slice_stop_only, test/test_jit.py::TestSlice::test_slice_stop_only_with_nones, test/test_jit.py::TestSlice::test_slice_string, test/test_jit.py::TestSlice::test_slice_tensor, test/test_jit.py::TestSlice::test_slice_tensor_multidim, test/test_jit.py::TestSlice::test_slice_tensor_multidim_with_dots, test/test_jit.py::TestSlice::test_slice_three_nones, test/test_jit.py::TestSlice::test_slice_two_nones, test/test_jit.py::TestSlice::test_tuple_slicing, test/test_jit.py::TestIgnorableArgs::test_add_out_ignorable_args, test/test_jit.py::TestIgnorableArgs::test_slice_ignorable_args_for_slice, test/test_jit.py::TestHooks::test_forward_tuple_input, test/test_jit.py::TestHooks::test_hook_compilation_hint, test/test_jit.py::TestHooks::test_hook_hook_name_collision, test/test_jit.py::TestHooks::test_hook_method_name_collision, test/test_jit.py::TestHooks::test_module_direct_forward_invocation, test/test_jit.py::TestHooks::test_module_forward_multiple_inputs, test/test_jit.py::TestHooks::test_module_forward_single_input, test/test_jit.py::TestHooks::test_module_hook_return_nothing, test/test_jit.py::TestHooks::test_module_multiple_hooks_multiple_inputs, test/test_jit.py::TestHooks::test_module_multiple_hooks_single_input, test/test_jit.py::TestHooks::test_module_no_forward_input, test/test_jit.py::TestHooks::test_module_same_hook_repeated, test/test_jit.py::TestHooks::test_submodule_called_directly_with_hooks, test/test_jit.py::TestHooks::test_submodule_direct_forward_invocation, test/test_jit.py::TestHooks::test_submodule_forward_multiple_inputs, test/test_jit.py::TestHooks::test_submodule_forward_single_input, test/test_jit.py::TestHooks::test_submodule_forward_single_input_return_not_tupled, test/test_jit.py::TestHooks::test_submodule_hook_return_nothing, test/test_jit.py::TestHooks::test_submodule_multiple_hooks_multiple_inputs, test/test_jit.py::TestHooks::test_submodule_multiple_hooks_single_input, test/test_jit.py::TestHooks::test_submodule_no_forward_input, test/test_jit.py::TestHooks::test_submodule_same_hook_repeated, test/test_jit.py::TestHooks::test_wrong_hook_signatures, test/test_jit.py::TestHooks::test_wrong_pre_hook_signatures, test/test_jit.py::TestWarn::test_warn, test/test_jit.py::TestWarn::test_warn_multiple_calls_multiple_warnings, test/test_jit.py::TestWarn::test_warn_multiple_calls_same_func_diff_stack, test/test_jit.py::TestWarn::test_warn_once_per_func, test/test_jit.py::TestWarn::test_warn_once_per_func_in_loop, test/test_jit.py::TestWarn::test_warn_only_once, test/test_jit.py::TestWarn::test_warn_only_once_in_loop_func, test/test_jit.py::TestIsinstance::test_bool, test/test_jit.py::TestIsinstance::test_dict, test/test_jit.py::TestIsinstance::test_dict_nested, test/test_jit.py::TestIsinstance::test_dict_no_contained_type, test/test_jit.py::TestIsinstance::test_dict_tensor, test/test_jit.py::TestIsinstance::test_empty_container_special_cases, test/test_jit.py::TestIsinstance::test_empty_container_throws_warning_in_eager, test/test_jit.py::TestIsinstance::test_float, test/test_jit.py::TestIsinstance::test_if_else, test/test_jit.py::TestIsinstance::test_in_if, test/test_jit.py::TestIsinstance::test_in_while_loop, test/test_jit.py::TestIsinstance::test_int, test/test_jit.py::TestIsinstance::test_list, test/test_jit.py::TestIsinstance::test_list_nested, test/test_jit.py::TestIsinstance::test_list_no_contained_type, test/test_jit.py::TestIsinstance::test_list_tensor, test/test_jit.py::TestIsinstance::test_list_tensor_type_true, test/test_jit.py::TestIsinstance::test_nontuple_container_rhs_throws_in_eager, test/test_jit.py::TestIsinstance::test_optional, test/test_jit.py::TestIsinstance::test_optional_nested, test/test_jit.py::TestIsinstance::test_optional_no_contained_type, test/test_jit.py::TestIsinstance::test_optional_none, test/test_jit.py::TestIsinstance::test_tensor_type_false, test/test_jit.py::TestIsinstance::test_tuple, test/test_jit.py::TestIsinstance::test_tuple_nested, test/test_jit.py::TestIsinstance::test_tuple_no_contained_type, test/test_jit.py::TestIsinstance::test_tuple_rhs, test/test_jit.py::TestIsinstance::test_tuple_tensor, test/test_jit.py::TestIsinstance::test_type_refinement, test/test_jit.py::TestPythonBuiltinOP::test_add, test/test_jit.py::TestPythonBuiltinOP::test_adv_indexing_list, test/test_jit.py::TestPythonBuiltinOP::test_advancedindex, test/test_jit.py::TestPythonBuiltinOP::test_gather, test/test_jit.py::TestPythonBuiltinOP::test_index, test/test_jit.py::TestPythonBuiltinOP::test_index_ellipses, test/test_jit.py::TestPythonBuiltinOP::test_inf, test/test_jit.py::TestPythonBuiltinOP::test_matmul_py3, test/test_jit.py::TestPythonBuiltinOP::test_mul, test/test_jit.py::TestPythonBuiltinOP::test_pow, test/test_jit.py::TestPythonBuiltinOP::test_random, test/test_jit.py::TestPythonBuiltinOP::test_slice, test/test_jit.py::TestPythonBuiltinOP::test_stepped_tuple_slicing, test/test_jit.py::TestPythonBuiltinOP::test_str_to_float, test/test_jit.py::TestPythonBuiltinOP::test_triple, test/test_jit.py::TestTyping::test_bool_list_io, test/test_jit.py::TestTyping::test_dict_comprehension, test/test_jit.py::TestTyping::test_dict_comprehension_scope, test/test_jit.py::TestTyping::test_dict_comprehension_with_type_annotation, test/test_jit.py::TestTyping::test_dict_in_not_in, test/test_jit.py::TestTyping::test_dict_invalid_annotations, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_key_mismatch, test/test_jit.py::TestTyping::test_dict_type_refinement_annotation_value_mismatch, test/test_jit.py::TestTyping::test_for_in_dict, test/test_jit.py::TestTyping::test_for_in_string, test/test_jit.py::TestTyping::test_for_tuple_assign, test/test_jit.py::TestTyping::test_for_tuple_unpack, test/test_jit.py::TestTyping::test_inherited_annotations_python_310, test/test_jit.py::TestTyping::test_list_io, test/test_jit.py::TestTyping::test_list_iterables, test/test_jit.py::TestTyping::test_list_sum, test/test_jit.py::TestTyping::test_list_type_refinement_annotation_element_mismatch, test/test_jit.py::TestTyping::test_list_unification, test/test_jit.py::TestTyping::test_multiple_assign, test/test_jit.py::TestTyping::test_namedtuple_error_source_attribution, test/test_jit.py::TestTyping::test_namedtuple_good_error, test/test_jit.py::TestTyping::test_namedtuple_py2, test/test_jit.py::TestTyping::test_namedtuple_redefine, test/test_jit.py::TestTyping::test_nested_list, test/test_jit.py::TestTyping::test_opt_opt_refinement, test/test_jit.py::TestTyping::test_optional_conversion, test/test_jit.py::TestTyping::test_optional_refinement, test/test_jit.py::TestTyping::test_optional_tuple, test/test_jit.py::TestTyping::test_singleton_tuple_unpack, test/test_jit.py::TestTyping::test_sum_list_diff_elms, test/test_jit.py::TestTyping::test_sum_list_empty, test/test_jit.py::TestTyping::test_sum_list_literal, test/test_jit.py::TestTyping::test_sum_list_one, test/test_jit.py::TestTyping::test_sum_list_wrong_type, test/test_jit.py::TestTyping::test_tuple_assignments, test/test_jit.py::TestTyping::test_tuple_create_return, test/test_jit.py::TestTyping::test_tuple_io, test/test_jit.py::TestTyping::test_tuple_keyword, test/test_jit.py::TestTyping::test_tuple_specialization, test/test_jit.py::TestHash::test_hash_bool, test/test_jit.py::TestHash::test_hash_device, test/test_jit.py::TestHash::test_hash_float, test/test_jit.py::TestHash::test_hash_int, test/test_jit.py::TestHash::test_hash_none, test/test_jit.py::TestHash::test_hash_string, test/test_jit.py::TestHash::test_hash_tensor, test/test_jit.py::TestHash::test_hash_tuple, test/test_jit.py::TestHash::test_hash_tuple_nested_unhashable_type, test/test_jit.py::TestComplex::test_binary_op_complex_tensor, test/test_jit.py::TestComplex::test_comparison_ops, test/test_jit.py::TestComplex::test_complex_constants_and_ops, test/test_jit.py::TestComplex::test_complex_constructor, test/test_jit.py::TestComplex::test_complex_list_sum, test/test_jit.py::TestComplex::test_complex_parse, test/test_jit.py::TestComplex::test_complexdict, test/test_jit.py::TestComplex::test_complexlist, test/test_jit.py::TestComplex::test_div, test/test_jit.py::TestComplex::test_infj_nanj_pickle, test/test_jit.py::TestComplex::test_pickle, test/test_jit.py::TestComplex::test_script, test/test_jit.py::TestComplex::test_tensor_attributes, test/test_jit.py::TestComplex::test_torch_complex_constructor_with_tensor, test/test_jit.py::TestJitUtils::test_checkscriptassertraisesregex, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_hybrid, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_keyword_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_only, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_positional_or_keyword, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_var_keyword, test/test_jit.py::TestJitUtils::test_get_callable_argument_names_var_positional, test/test_jit.py::TestJitUtils::test_no_tracer_warn_context_manager, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_annotation_and_init_annotation, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_annotation_only, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_class_level_jit_annotation, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_dict, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_dict_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_list_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_optional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_empty_tensor, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_falsy_base_type, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_nonempty_container, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_attribute, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_dict, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_dict_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_list_lowercase, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_jit_empty_optional, test/test_jit.py::TestScriptModuleInstanceAttributeTypeAnnotation::test_annotated_with_torch_jit_import, test/test_jit.py::TestTypesAndAnnotation::test_annotate_outside_init, test/test_jit.py::TestTypesAndAnnotation::test_bad_types, test/test_jit.py::TestTypesAndAnnotation::test_ignore_with_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_fn_with_nonscriptable_types, test/test_jit.py::TestTypesAndAnnotation::test_ignoring_module_attributes, test/test_jit.py::TestTypesAndAnnotation::test_inferred_type_error_message, test/test_jit.py::TestTypesAndAnnotation::test_mismatched_annotation, test/test_jit.py::TestTypesAndAnnotation::test_optional_no_element_type_annotation, test/test_jit.py::TestTypesAndAnnotation::test_parser_bug, test/test_jit.py::TestTypesAndAnnotation::test_pep585_type, test/test_jit.py::TestTypesAndAnnotation::test_python_callable, test/test_jit.py::TestTypesAndAnnotation::test_reannotate, test/test_jit.py::TestTypesAndAnnotation::test_tuple_no_element_type_annotation, test/test_jit.py::TestTypesAndAnnotation::test_type_annotate_py3, test/test_jit.py::TestTypesAndAnnotation::test_types_as_values, test/test_jit.py::TestTypesAndAnnotation::test_unimported_type_resolution, test/test_jit.py::TestMisc::test_broadcasting_list, test/test_jit.py::TestMisc::test_export_opnames_interface, test/test_jit.py::TestMisc::test_future_isinstance, test/test_jit.py::TestMisc::test_hacked_twin, test/test_jit.py::TestMisc::test_if_returning_any, test/test_jit.py::TestMisc::test_jit_get_operation_order, test/test_jit.py::TestMisc::test_joined_str, test/test_jit.py::TestMisc::test_kwarg_support, test/test_jit.py::TestMisc::test_legacy_tensor_constructor, test/test_jit.py::TestMisc::test_list_literal_infer, test/test_jit.py::TestMisc::test_math_inf, test/test_jit.py::TestMisc::test_parse_ir_annotate, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_negative, test/test_jit.py::TestMisc::test_parse_ir_single_element_tensor_positive, test/test_jit.py::TestMisc::test_pow_multiple_dtype, test/test_jit.py::TestMisc::test_script_many_decorators, test/test_jit.py::TestMisc::test_str_refine_any, test/test_jit.py::TestMisc::test_subexpression_Dict_int_Future, test/test_jit.py::TestMisc::test_subexpression_Future_annotate, test/test_jit.py::TestMisc::test_subexpression_List_Future, test/test_jit.py::TestMisc::test_subexpression_Optional, test/test_jit.py::TestMisc::test_subexpression_Tuple_int_int_Future, test/test_jit.py::TestMisc::test_tuple_subscripted_assign, test/test_jit.py::TestMisc::test_unsafe_hacked_twin, test/test_jit.py::TestUpgraders::test_add_value_to_version_map, test/test_jit.py::TestUpgraders::test_aten_div_scalar_at_3, test/test_jit.py::TestUpgraders::test_aten_div_tensor_at_3, test/test_jit.py::TestUpgraders::test_aten_div_tensor_out_at_3, test/test_jit.py::TestUpgraders::test_aten_full_at_4, test/test_jit.py::TestUpgraders::test_aten_full_other_variants, test/test_jit.py::TestUpgraders::test_aten_full_out_at_4, test/test_jit.py::TestUpgraders::test_aten_linspace, test/test_jit.py::TestUpgraders::test_aten_linspace_out, test/test_jit.py::TestUpgraders::test_aten_logspace, test/test_jit.py::TestUpgraders::test_aten_logspace_out, test/test_jit.py::TestUpgraders::test_aten_test_serialization, test/test_jit.py::TestUpgraders::test_populated_test_upgrader_graph, test/test_jit.py::TestUpgraders::test_populated_upgrader_graph, test/test_jit.py::TestTensorCreationOps::test_randperm_default_dtype, test/test_jit.py::TestTensorCreationOps::test_randperm_specifed_dtype, test/test_jit.py::TestTensorCreationOps::test_tril_indices_default_dtype, test/test_jit.py::TestTensorCreationOps::test_tril_indices_specified_dtype, test/test_jit.py::TestTensorCreationOps::test_triu_indices_default_dtype, test/test_jit.py::TestTensorCreationOps::test_triu_indices_specified_dtype, test/test_jit.py::TestModuleAPIs::test_customized_state_dict_methods, test/test_jit.py::TestModuleAPIs::test_default_state_dict_methods, test/test_jit.py::TestModuleAPIs::test_submodule_customized_state_dict_methods, test/test_jit.py::TestScriptProfile::test_basic, test/test_jit.py::TestScriptProfile::test_empty, test/test_jit.py::TestScriptProfile::test_multi, test/test_jit.py::TestScriptProfile::test_script, test/test_jit.py::TestScriptProfile::test_section, test/test_jit.py::TestFunctionalToInplaceActivation::test_check_no_type_promotion, test/test_jit.py::TestFunctionalToInplaceActivation::test_functional_to_inplace_activation, test/test_jit.py::TestFunctionalToInplaceActivation::test_no_functional_to_inplace, test/test_jit.py::TestFunctionalToInplaceActivation::test_resnet18_correctness, test/test_jit.py::TestInplaceToFunctionalActivation::test_inplace_to_functional_activation, test/test_jit.py::TestInplaceToFunctionalActivation::test_resnet18_correctness, test/test_jit.py::TestParametrization::test_scriptable, test/test_jit.py::TestParametrization::test_traceable, test/test_jit.py::TestGetDefaultAttr::test_getattr_named_tuple, test/test_jit.py::TestGetDefaultAttr::test_getattr_tuple, test/test_jit.py::TestGetDefaultAttr::test_getattr_with_default, test/test_jit.py::TestAtenPow::test_aten_pow_zero_negative_exponent, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_1, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_2, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_3, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_fuse_activation_with_pack_ops_linear_conv2d_4, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_insert_pre_packed_linear_before_inline_and_conv_2d_op, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_insert_pre_packed_linear_op, test/test_jit.py::TestOptimizeForMobilePreserveDebugInfo::test_replace_conv1d_with_conv2d, test/test_jit.py::TestUnion::test_check_union_annotation, test/test_jit.py::TestUnion::test_union_T_None_is_equivalent_to_optional_T, test/test_jit.py::TestUnion::test_union_argument_order_is_ignored, test/test_jit.py::TestUnion::test_union_argument_order_is_ignored_container, test/test_jit.py::TestUnion::test_union_as_annotation, test/test_jit.py::TestUnion::test_union_as_annotation_in_typed_container, test/test_jit.py::TestUnion::test_union_as_annotation_py2, test/test_jit.py::TestUnion::test_union_as_dict_key, test/test_jit.py::TestUnion::test_union_as_dict_value, test/test_jit.py::TestUnion::test_union_as_internal_tuple_type, test/test_jit.py::TestUnion::test_union_branching_does_not_autoinfer_undeclared_union, test/test_jit.py::TestUnion::test_union_branching_does_not_widen_existing_inferred_type, test/test_jit.py::TestUnion::test_union_branching_with_union_return_and_homogenous_types, test/test_jit.py::TestUnion::test_union_does_not_replace_existing_annotated_type, test/test_jit.py::TestUnion::test_union_does_not_replace_existing_annotated_type_empty_container, test/test_jit.py::TestUnion::test_union_does_not_replace_existing_annotated_type_union, test/test_jit.py::TestUnion::test_union_in_class_constructor, test/test_jit.py::TestUnion::test_union_memory_aliasing, test/test_jit.py::TestUnion::test_union_module_with_union_class_variable, test/test_jit.py::TestUnion::test_union_module_with_union_instance_variable, test/test_jit.py::TestUnion::test_union_optional_of_union_is_flattened, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped_container, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped_optional, test/test_jit.py::TestUnion::test_union_redundant_arguments_are_skipped_subtyping, test/test_jit.py::TestUnion::test_union_return_type, test/test_jit.py::TestUnion::test_union_schema_matching_on_internal_type, test/test_jit.py::TestUnion::test_union_serialization_preserves_type_annotations, test/test_jit.py::TestUnion::test_union_subclasses_larger_union, test/test_jit.py::TestUnion::test_union_subtractive_refinement, test/test_jit.py::TestUnion::test_union_subtractive_refinement_with_container, test/test_jit.py::TestUnion::test_union_type_refinement, test/test_jit.py::TestUnion::test_union_type_refinement_internal_declaration, test/test_jit.py::TestUnion::test_union_type_refinement_partial_static_refinement_tuple_rhs, test/test_jit.py::TestUnion::test_union_type_refinement_partial_static_refinement_union_rhs, test/test_jit.py::TestUnion::test_union_type_refinement_statically_false, test/test_jit.py::TestUnion::test_union_type_refinement_statically_true, test/test_jit.py::TestUnion::test_union_type_refinement_tuple_rhs, test/test_jit.py::TestUnion::test_union_type_refinement_tuple_rhs_noncontained_type, test/test_jit.py::TestUnion::test_union_type_refinement_tuple_rhs_union, test/test_jit.py::TestUnion::test_union_type_refinement_union_rhs, test/test_jit.py::TestUnion::test_union_variable_can_be_reassigned, test/test_jit.py::TestUnion::test_union_with_collections, test/test_jit.py::TestUnion::test_union_with_dict_assignment, test/test_jit.py::TestUnion::test_union_with_enum, test/test_jit.py::TestUnion::test_union_with_list_assignment, test/test_jit.py::TestUnion::test_union_with_scalar_values, test/test_jit.py::TestUnion::test_unions_of_a_single_argument_vanish, test/test_jit.py::TestUnion::test_unions_of_unions_are_flattened, test/test_jit.py::TestBatchMM::test_batch_mm_no_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_permitted_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_prohibited_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_prohibited_mutation_if_node, test/test_jit.py::TestBatchMM::test_batch_mm_prohibited_mutation_multiple_adds, test/test_jit.py::TestBatchMM::test_batch_mm_side_permitted_mutation, test/test_jit.py::TestBatchMM::test_batch_mm_side_prohibited_mutation_common_side, test/test_jit.py::TestBatchMM::test_batch_mm_side_prohibited_mutation_uncommon_side, test/test_jit.py::TestDtypeAnalysis::test_binary_scalar, test/test_jit.py::TestDtypeAnalysis::test_binary_tensors, 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test/test_jit.py::TestScript::test_unicode_comments, test/test_jit.py::TestScript::test_uninitialized, test/test_jit.py::TestScript::test_union_to_number, test/test_jit.py::TestScript::test_unknown_builtin, test/test_jit.py::TestScript::test_unmatched_type_annotation, test/test_jit.py::TestScript::test_unspecialized_any_binding, test/test_jit.py::TestScript::test_unsqueeze_guard_elimination, test/test_jit.py::TestScript::test_unsupported_builtin_error, test/test_jit.py::TestScript::test_unused_decorator, test/test_jit.py::TestScript::test_unwrap_optional_builtin, test/test_jit.py::TestScript::test_var_aug_assign, test/test_jit.py::TestScript::test_vararg_zeros, test/test_jit.py::TestScript::test_view_listconstruct_shape_prop, test/test_jit.py::TestScript::test_view_shape_prop, test/test_jit.py::TestScript::test_view_write, test/test_jit.py::TestScript::test_weak_cuda, test/test_jit.py::TestScript::test_where, test/test_jit.py::TestScript::test_where_method, test/test_jit.py::TestScript::test_while, test/test_jit.py::TestScript::test_while_nest_if, test/test_jit.py::TestScript::test_while_nonexistent_cond_value, test/test_jit.py::TestScript::test_while_nonexistent_value, test/test_jit.py::TestScript::test_while_write_outer_then_read, test/test_jit.py::TestScript::test_wrong_attr_lookup, test/test_jit.py::TestScript::test_wrong_implicit_expand, test/test_jit.py::TestScript::test_wrong_method_call_inputs, test/test_jit.py::TestScript::test_wrong_module_attr_lookup, test/test_jit.py::TestScript::test_wrong_return_type, test/test_jit.py::TestScript::test_wrong_use_as_callable, test/test_jit.py::TestScript::test_wrong_use_as_tuple, test/test_jit.py::TestScript::test_zero_dimension_tensor_trace, test/test_jit.py::TestScript::test_zeros, test/test_jit.py::TestScript::test_zip_enumerate_modulelist, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_BCELoss_weights_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_legacy_enum, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_BCEWithLogitsLoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_Bilinear, test/test_jit.py::TestJitGeneratedModule::test_nn_CELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_circular_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad1, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad1size1, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad2size1, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_same_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_pad_valid, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_reflect_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_stride, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv1d_zeros_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_circular_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_padded, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_depthwise_with_multiplier, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_groups_thnn, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_pad_same, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_pad_same_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_pad_valid, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_padding, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_reflect_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv2d_zeros_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_1x1x1_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_circular_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_dilated_strided, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_pad_same, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_pad_same_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_pad_valid, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_replicate_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_stride, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_stride_padding, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_zero_batch, test/test_jit.py::TestJitGeneratedModule::test_nn_Conv3d_zeros_stride2_pad2, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose1d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_groups, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose2d_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose3d, test/test_jit.py::TestJitGeneratedModule::test_nn_ConvTranspose3d_dilated, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_CosineEmbeddingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_CrossMapLRN2d, test/test_jit.py::TestJitGeneratedModule::test_nn_ELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_max, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_max_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_mean_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sparse, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_EmbeddingBag_sum_padding_idx, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding_discontiguous, test/test_jit.py::TestJitGeneratedModule::test_nn_Embedding_sparse, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten, test/test_jit.py::TestJitGeneratedModule::test_nn_Flatten_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_input, test/test_jit.py::TestJitGeneratedModule::test_nn_Fold_no_batch_dim_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_GELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_GLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_GRUCell, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardsigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardswish_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Hardtanh_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_margin_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_HingeEmbeddingLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_delta, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_HuberLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_log_target, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_no_reduce_scalar_log_target, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_with_log_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_KLDivLoss_with_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce_complex, test/test_jit.py::TestJitGeneratedModule::test_nn_L1Loss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_LSTMCell, test/test_jit.py::TestJitGeneratedModule::test_nn_LayerNorm_3d_no_affine_large_feature, test/test_jit.py::TestJitGeneratedModule::test_nn_LeakyReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Linear_no_bias, test/test_jit.py::TestJitGeneratedModule::test_nn_LogSigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MSELoss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MarginRankingLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_Mish_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_0d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_index_neg, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiLabelSoftMarginLoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_1d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_margin_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_p_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiMarginLoss_weights_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_MultiheadAttention, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss2d_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLossNd_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights_ignore_index, test/test_jit.py::TestJitGeneratedModule::test_nn_NLLLoss_no_reduce_weights_ignore_index_neg, test/test_jit.py::TestJitGeneratedModule::test_nn_PReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_broadcast_lhs, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_broadcast_rhs, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_PairwiseDistance_with_non_default_args, test/test_jit.py::TestJitGeneratedModule::test_nn_PixelShuffle, test/test_jit.py::TestJitGeneratedModule::test_nn_PixelUnshuffle, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_PoissonNLLLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_RNNCell, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_with_up_down, test/test_jit.py::TestJitGeneratedModule::test_nn_RReLU_with_up_down_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_ReLU6_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_ReLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d_complex, test/test_jit.py::TestJitGeneratedModule::test_nn_ReplicationPad3d_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SELU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SiLU_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Sigmoid_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_beta, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_no_reduce_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_SmoothL1Loss_zero_beta, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_SoftMarginLoss_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_Softplus_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Softshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Softsign_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanh_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Tanhshrink_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Threshold_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Transformer, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerDecoderLayer_gelu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerDecoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerEncoderLayer_gelu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_TransformerEncoderLayer_relu_activation, test/test_jit.py::TestJitGeneratedModule::test_nn_Transformer_multilayer_coder, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_mean, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_none, test/test_jit.py::TestJitGeneratedModule::test_nn_TripletMarginLoss_no_batch_dim_sum, test/test_jit.py::TestJitGeneratedModule::test_nn_Unflatten_no_batch_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold, test/test_jit.py::TestJitGeneratedModule::test_nn_Unfold_int_input, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_shared_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_skewed_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_scale_tuple_skewed_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bicubic_tuple_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_shared_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_skewed_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_scale_tuple_skewed_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_bilinear_tuple_2d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_1d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_scale_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_scale_1d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_linear_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_1d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d_launch_configs, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_2d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_3d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_scale_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_1d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_2d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_nearest_tuple_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_3d_zero_dim, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_scale_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_scale_3d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_tuple_3d, test/test_jit.py::TestJitGeneratedModule::test_nn_interpolate_trilinear_tuple_3d_align_corners, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_dim0, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_dim3, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_lastdim, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_log_softmax_spatial_special, test/test_jit.py::TestJitGeneratedModule::test_nn_multimarginloss_1d_input_0d_target_no_reduce, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_dim0, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_dim3, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_functional_scalar, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_lastdim, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_lastdim_dtype, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial_dtype, test/test_jit.py::TestJitGeneratedModule::test_nn_softmax_spatial_special, test/test_jit.py::TestProducerVersion::test_version 2025-08-26T20:23:47.7775076Z 2025-08-26T20:23:50.8810632Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:23:50.8813629Z import pkg_resources 2025-08-26T20:23:51.0053243Z Running higher_order_ops/test_with_effects 1/1 ... [2025-08-26 20:23:51.004934] 2025-08-26T20:23:51.0054213Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:23:51.0056360Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_with_effects.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:23:51.005250] 2025-08-26T20:24:11.1013030Z 2025-08-26T20:24:11.1014643Z higher_order_ops/test_with_effects 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_with_effects_1.1_00a5c613e3c6869b_.log 2025-08-26T20:24:11.1023583Z Running 18 items in this shard: test/higher_order_ops/test_with_effects.py::TestWithEffects::test_alias_op, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_aot_eager, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_aot_eager_requires_grad, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_inductor, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_compile_inductor_external_op_return_none, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effectful_custom_op_with_subclasses, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effectful_op_in_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_aliased_outputs, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_mutation_is_output, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_mutation_return, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_effects_and_input_output_view_simple, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print_with_buffer_mutations, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_print_with_input_mutations, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_register_effectful_custom_op, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_regular_effectful_op_in_forward_and_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_regular_effectful_op_only_in_backward, test/higher_order_ops/test_with_effects.py::TestWithEffects::test_torchbind_custom_op 2025-08-26T20:24:11.1031209Z 2025-08-26T20:24:15.3660522Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:24:15.3663668Z import pkg_resources 2025-08-26T20:24:15.4895088Z Running test_content_store 1/1 ... [2025-08-26 20:24:15.489191] 2025-08-26T20:24:15.4895556Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:24:15.4897249Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_content_store.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:24:15.489516] 2025-08-26T20:24:26.4802553Z 2025-08-26T20:24:26.4803693Z test_content_store 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_content_store_1.1_4d3d11d83c20bf9e_.log 2025-08-26T20:24:26.4805628Z Running 4 items in this shard: test/test_content_store.py::TestContentStoreCPU::test_basic_cpu, test/test_content_store.py::TestContentStoreCPU::test_load_tensor_cpu, test/test_content_store.py::TestContentStoreCPU::test_repeated_hash_cpu, test/test_content_store.py::TestContentStoreCPU::test_scalar_cpu 2025-08-26T20:24:26.4806970Z 2025-08-26T20:24:29.8426527Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:24:29.8429722Z import pkg_resources 2025-08-26T20:24:29.9679372Z Running test_numpy_interop 1/1 ... [2025-08-26 20:24:29.967638] 2025-08-26T20:24:29.9679856Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:24:29.9682191Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_numpy_interop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:24:29.967985] 2025-08-26T20:24:31.3702305Z 2025-08-26T20:24:31.3703706Z test_binary_ufuncs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_binary_ufuncs_1.1_15d444442671d5ec_.log 2025-08-26T20:24:32.0333704Z Running 12862 items in this shard: test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___add___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___and___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___eq___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___floordiv___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ge___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___gt___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iadd___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___iand___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ifloordiv___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___ilshift___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imod___not_implemented_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test___imul___not_implemented_cpu_int16, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_eq_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_float_power_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_floor_divide_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmax_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmin_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_fmod_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gcd_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gcd_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gcd_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gcd_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gcd_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ge_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_gt_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_heaviside_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_hypot_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_hypot_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_hypot_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_hypot_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igamma_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igamma_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igamma_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igamma_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igammac_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igammac_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igammac_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_igammac_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_isclose_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_jiterator_binary_return_by_ref_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_lcm_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_lcm_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_lcm_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_lcm_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_lcm_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_ldexp_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_le_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logaddexp_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logaddexp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logaddexp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logaddexp_cpu_float16, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_and_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_and_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_and_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_and_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_and_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_logical_or_cpu_float16, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_chebyshev_polynomial_w_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_h_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_hermite_polynomial_he_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_laguerre_polynomial_l_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_legendre_polynomial_p_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_special_shifted_chebyshev_polynomial_t_cpu_int8, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_true_divide_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_every_other_xlogy_cpu_bfloat16, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_atan2_cpu_uint8, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_right_shift_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_right_shift_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_right_shift_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_bitwise_xor_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_clamp_max_cpu_uint8, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_copysign_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_floor_rounding_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_no_rounding_mode_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_div_trunc_rounding_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_complex32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_eq_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_float_power_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_floor_divide_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmax_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmin_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_fmod_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gcd_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ge_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_gt_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_heaviside_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_hypot_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_hypot_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_hypot_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_hypot_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igamma_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igamma_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igamma_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igamma_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igammac_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igammac_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igammac_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_igammac_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_isclose_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_jiterator_binary_return_by_ref_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lcm_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lcm_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lcm_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lcm_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lcm_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ldexp_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_le_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logaddexp_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logaddexp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logaddexp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logaddexp_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logaddexp_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logaddexp_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_and_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_or_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_logical_xor_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_lt_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_max_binary_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_maximum_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_min_binary_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_minimum_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_complex32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_mul_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_ne_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_nextafter_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_polar_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_polar_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_pow_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_remainder_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_rsub_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_contig_vs_transposed_special_chebyshev_polynomial_t_cpu_int8, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_int8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_bfloat16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_copysign_subgradient_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cpow_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cpu_tensor_pow_cuda_scalar_tensor_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cremainder_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cross_device_binary_ops_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cross_device_inplace_error_msg_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_csub_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cuda_tensor_pow_scalar_tensor_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_cumulative_trapezoid_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_and_floordiv_script_vs_python_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_and_floordiv_vs_python_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_modes_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_nonfinite_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_nonfinite_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_nonfinite_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_nonfinite_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_div_rounding_numpy_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_divide_by_zero_rounding_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_divide_by_zero_rounding_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_divide_by_zero_rounding_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_divide_by_zero_rounding_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_divmul_scalar_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex128_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_complex64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_float64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_int8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_power_exceptions_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_scalar_pow_float_tensor_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_float_scalar_pow_float_tensor_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_div_extremal_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_div_extremal_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_div_extremal_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_div_extremal_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_scalar_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_tensor_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_zero_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_zero_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_zero_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_zero_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_floor_divide_zero_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_float_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_float_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_float_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_by_zero_integral_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_fmod_remainder_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_gcd_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_gcd_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_gcd_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_gcd_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_gcd_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_complex_cpu_complex128_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_complex_cpu_complex128_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_complex_cpu_complex64_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_complex_cpu_complex64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_bool_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_float64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_int8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_heaviside_cross_device_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_hypot_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_hypot_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_hypot_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_hypot_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_idiv_and_ifloordiv_vs_python_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_inplace_division_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_inplace_dunders_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_int_and_float_pow_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_int_tensor_pow_neg_ints_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lcm_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lcm_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lcm_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_ldexp_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_lowp_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_lowp_cpu_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_lowp_cpu_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_lowp_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_scalar_tensor_promotion_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_scalar_tensor_promotion_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_scalar_tensor_promotion_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_scalar_tensor_promotion_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_tensor_promotion_error_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_tensor_promotion_error_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_lerp_weight_tensor_promotion_error_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp2_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp2_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logaddexp2_cpu_float64, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_logical_xor_with_nontrivial_alignment_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_long_tensor_pow_floats_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_bfloat16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_and_minimum_subgradient_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex128_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_complex_cpu_complex64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_cross_device_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_nan_and_inf_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_nan_and_inf_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_nan_and_inf_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_float_nan_and_inf_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_forward_ad_float32_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_int_and_bool_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_int_and_bool_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_int_and_bool_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_int_and_bool_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_int_and_bool_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_int_and_bool_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bfloat16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_bool_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_float64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_int8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_maximum_minimum_type_promotion_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_min_max_binary_op_nan_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_min_max_binary_op_nan_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_mul_chalf_tensor_and_cpu_scalar_cpu_complex32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_mul_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_mul_intertype_scalar_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_mul_intertype_scalar_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_complex128, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_complex64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_muldiv_scalar_cpu_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_nextafter_bfloat16_cpu_bfloat16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_nextafter_cpu_float16, 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test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_float64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_int8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_float16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_cpu_uint8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_gradients_cpu_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_xlogy_xlog1py_scalar_type_promotion_cpu, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_bool_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_float64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int16_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int32_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int64_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_int8_uint8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_bool, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_float32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_float64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_int16, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_int32, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_int64, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_int8, test/test_binary_ufuncs.py::TestBinaryUfuncsCPU::test_zeta_cpu_uint8_uint8 2025-08-26T20:24:32.5546695Z 2025-08-26T20:24:34.0392262Z 2025-08-26T20:24:34.0393571Z test_numpy_interop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numpy_interop_1.1_97466ee8b9267e5b_.log 2025-08-26T20:24:34.0409881Z Running 44 items in this shard: test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_bool, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_complex128, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_complex64, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_float16, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_float32, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_float64, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_int16, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_int32, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_int64, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_int8, test/test_numpy_interop.py::TestNumPyInteropCPU::test___eq___cpu_uint8, test/test_numpy_interop.py::TestNumPyInteropCPU::test_ctor_with_invalid_numpy_array_sequence_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_ctor_with_numpy_scalar_ctor_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_empty_tensors_interop_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_from_list_of_ndarray_warning_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_from_numpy_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_from_numpy_no_leak_on_invalid_dtype_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_from_numpy_zero_element_type_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_has_storage_numpy_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_multiplication_numpy_scalar_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_ndarray_astype_object_graph_break_2_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_ndarray_astype_object_graph_break_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_array_interface_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_index_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_index_multi_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_non_writeable_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_bfloat16, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_bool, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_complex128, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_complex64, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_float16, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_float32, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_float64, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_int16, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_int32, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_int64, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_int8, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_scalar_cmp_cpu_uint8, test/test_numpy_interop.py::TestNumPyInteropCPU::test_numpy_unresizable_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_parse_numpy_int_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_parse_numpy_int_overflow_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_to_numpy_bool_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_to_numpy_cpu, test/test_numpy_interop.py::TestNumPyInteropCPU::test_to_numpy_force_argument_cpu 2025-08-26T20:24:34.0425005Z 2025-08-26T20:24:34.7759437Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:24:34.7762540Z import pkg_resources 2025-08-26T20:24:34.9576535Z Running functorch/test_control_flow 1/1 ... [2025-08-26 20:24:34.957243] 2025-08-26T20:24:34.9577496Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:24:34.9580397Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_control_flow.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:24:34.957697] 2025-08-26T20:24:37.2667127Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:24:37.2668720Z import pkg_resources 2025-08-26T20:24:37.3912177Z Running functorch/test_aotdispatch 1/6 ... [2025-08-26 20:24:37.390923] 2025-08-26T20:24:37.3912664Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:24:37.3915423Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'not serial', '--shard-id=1', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:24:37.391287] 2025-08-26T20:27:30.0218196Z 2025-08-26T20:27:30.0219431Z functorch/test_control_flow 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_control_flow_1.1_bf70107b5a76b0d5_.log 2025-08-26T20:27:30.1067887Z Running 1334 items in this shard: test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_complex, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_different_pytree_output, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_gpu, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_grad_through_cond, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_inner_fn, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_inner_tensor, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_mixed_require_grad, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_nested, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_pytree_input, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_pytree_not_all_inputs_used, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_same_pytree_output, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_simple, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_torch_nn_module, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_user_nn_module, test/functorch/test_control_flow.py::TestControlFlow::test_cond_autograd_zeros_unused_branch_complex_compile_fail_compile_mode_compile_dynamic_shape_scalar_False, test/functorch/test_control_flow.py::TestControlFlow::test_cond_gpu, test/functorch/test_control_flow.py::TestControlFlow::test_cond_in_forloop, test/functorch/test_control_flow.py::TestControlFlow::test_cond_no_trace, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_higher_order, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_nested_list, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_no_grad_output, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_simple, test/functorch/test_control_flow.py::TestControlFlow::test_map_autograd_simple_partial_grad, test/functorch/test_control_flow.py::TestControlFlow::test_map_dict_in_out, test/functorch/test_control_flow.py::TestControlFlow::test_map_gpu, test/functorch/test_control_flow.py::TestControlFlow::test_map_illegal_inputs, test/functorch/test_control_flow.py::TestControlFlow::test_map_illegal_outputs, test/functorch/test_control_flow.py::TestControlFlow::test_map_list_in_out, test/functorch/test_control_flow.py::TestControlFlow::test_scan_associative_scan, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_binary_operator_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_carry_carry_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_carry_output_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_eager_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_eager_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_none_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_compile_mode_none_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_eager_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_False_compile_mode_none_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_eager_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_additional_inputs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_additional_inputs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_complex_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_complex_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_init_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_init_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_random_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_random_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_xs_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_RNN_partial_autograd_reverse_True_compile_mode_none_partial_grad_xs_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_carries_ys_same_grad_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_all_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_additional_inputs_partial_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_closure_combine_fn_with_no_grad_for_out_reverse_False_compile_mode_eager_cuda_autograd_False, 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test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_False_compile_mode_none_cpu_int64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_False_compile_mode_none_cuda_complex64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_False_compile_mode_none_cuda_float16, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_False_compile_mode_none_cuda_float32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_False_compile_mode_none_cuda_int32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_False_compile_mode_none_cuda_int64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cpu_complex64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cpu_float16, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cpu_float32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cpu_int32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cpu_int64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cuda_complex64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cuda_float16, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cuda_float32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cuda_int32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_eager_cuda_int64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cpu_complex64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cpu_float16, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cpu_float32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cpu_int32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cpu_int64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cuda_complex64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cuda_float16, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cuda_float32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cuda_int32, test/functorch/test_control_flow.py::TestControlFlow::test_scan_dtype_reverse_True_compile_mode_none_cuda_int64, test/functorch/test_control_flow.py::TestControlFlow::test_scan_float_output, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_non_tensor, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_pytree_complex_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_scanned_0, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_carry_shape, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_False_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_False_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_True_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_complex_reverse_True_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_init_longer_carry, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_pytree_init_shorter_carry, test/functorch/test_control_flow.py::TestControlFlow::test_scan_init_wrong_shape, test/functorch/test_control_flow.py::TestControlFlow::test_scan_input_carry_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_input_mutation, test/functorch/test_control_flow.py::TestControlFlow::test_scan_input_output_alias, test/functorch/test_control_flow.py::TestControlFlow::test_scan_multiple_layers_gradient_layers_1_device_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_multiple_layers_gradient_layers_1_device_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_multiple_layers_gradient_layers_2_device_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_multiple_layers_gradient_layers_2_device_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_multiple_layers_gradient_layers_3_device_cpu, test/functorch/test_control_flow.py::TestControlFlow::test_scan_multiple_layers_gradient_layers_3_device_cuda, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_non_pointwise_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_one_return, test/functorch/test_control_flow.py::TestControlFlow::test_scan_pytree_output, test/functorch/test_control_flow.py::TestControlFlow::test_scan_simple_graph, test/functorch/test_control_flow.py::TestControlFlow::test_scan_simple_graph_wrong_dtype, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_False_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_eager_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cpu_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cpu_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cuda_autograd_False, test/functorch/test_control_flow.py::TestControlFlow::test_scan_tuple_reverse_True_compile_mode_none_cuda_autograd_True, test/functorch/test_control_flow.py::TestControlFlow::test_scan_wrong_pytree, test/functorch/test_control_flow.py::TestControlFlow::test_scan_y_less_ndim_then_dim, test/functorch/test_control_flow.py::TestControlFlow::test_while_loop_gpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_binary_operator_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_combine_fn_wrong_meta_in_combine_fn, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_compile_dynamic_shape_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_eager_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_False_compile_mode_none_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_compile_reverse_True_compile_mode_compile_combine_mode_generic_cpu, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_complex_pytree_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_cond_in_combine_fn_compile_mode_compile_reverse_False_cuda, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_combine_mode_pointwise_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_combine_mode_pointwise_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_dynamic_shape_combine_mode_generic_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_dynamic_shape_combine_mode_generic_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_dim_reverse_True_compile_mode_compile_dynamic_shape_combine_mode_pointwise_cpu, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_generic_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_matmul_combine_mode_pointwise_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_generic_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_combine_mode_pointwise_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_compile_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_eager_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_generic_compile_mode_none_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_dynamic_shape_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_compile_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_eager_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_False_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_downstream_scan_scan_different_dim_combine_mode_pointwise_compile_mode_none_reverse_first_True_same_direction_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_expand_in_combine_fn_compile_mode_none_combine_mode_generic_reverse_False_cuda, 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test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_shape_check_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_freevars_simple_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_input_mutation, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_input_output_alias, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_dynamic_shape_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_compile_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_eager_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_compile_mode_none_loop_type_for_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_loop_in_combine_fn_failure, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_map_in_combine_fn, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_nested, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_contiguous_tensor_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_dynamic_shape_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_compile_dynamic_shape_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_eager_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_eager_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_none_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_False_compile_mode_none_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_dynamic_shape_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_compile_dynamic_shape_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_eager_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_eager_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_none_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_non_pointwise_generic_reverse_True_compile_mode_none_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_output_output_alias, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_pytree_output, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_sparse_tensor, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_compile_dynamic_shape_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_eager_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_generic_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_tuple_compile_mode_none_combine_mode_pointwise_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_dynamic_shape_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_compile_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_eager_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_False_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_False_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_True_cpu, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_vmap_in_combine_fn_compile_mode_none_reverse_True_cuda, test/functorch/test_control_flow.py::AssociativeScanTests::test_associative_scan_wrong_pytree, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_accepts_torch_function_as_inputs, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_autograd_backward, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_eager_run_with_item, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_aot_func_check_functional, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_data_dependent_pred, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_input_aliasing_with_aot_func, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_input_mutation_on_false_branch, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_input_mutation_on_true_branch, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_nested_input_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_nested_input_mutation_with_aot_func, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_functionalized_output_alias_input, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_make_fx_preserve_stack_trace_for_nodes_in_subgraph, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_merge_graph_preserves_ph_meta, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_output_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_mismatched_branch_strided_output_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_multi, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_multi_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_other_inputs, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_traced_other_inputs_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_with_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_nested_with_closure_graph_module, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_no_dynamo_cache_limit, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_retrace_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_simple_with_linear_compile_check_graph, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_subgraph_same_shape_env_as_parent, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_symint_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_symint_operands_requires_grad_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_symint_operands_requires_grad_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_trace_set__and_mutate_input, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_trace_set__and_mutate_intermediate, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_traced_not_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_traced_not_nested_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_function_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_bool_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_floatTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_function_nOperands_0_nClosure_1_nesting_2, 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test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_0_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_tracing_with_valid_inputs_predType_intTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_unbacked_symint_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_args_with_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_inputs, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_outputs_nClosure_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_multiple_outputs_nClosure_1, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_2_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_function_nOperands_2_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_2_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_module_nOperands_2_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_1_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_2_nClosure_0_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_predType_boolTensor_innerFnType_object_nOperands_2_nClosure_1_nesting_0, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_vmap_single_input_with_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_consecutive_make_fx_symbolic, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_module_param_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_module_python_scalar_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_sym_pred, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_tensor_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_tensor_closure_graph_module, test/functorch/test_control_flow.py::TestControlFlowTraced::test_cond_with_unbacked_sym_pred, test/functorch/test_control_flow.py::TestControlFlowTraced::test_hop_raises_if_not_overriding_call, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_input_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_mutation_inference_mode_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_mutation_inference_mode_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_input_output_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_aot_func, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_arg_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_elem_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_functionalized_elem_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_map_unfunc_boolean_tensor_for_nested_map_cond, test/functorch/test_control_flow.py::TestControlFlowTraced::test_merge_output, test/functorch/test_control_flow.py::TestControlFlowTraced::test_nested_cond_map_cond_symbolic, test/functorch/test_control_flow.py::TestControlFlowTraced::test_nested_map_cond_real, test/functorch/test_control_flow.py::TestControlFlowTraced::test_nested_map_cond_symbolic, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_tensor_size, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_tensor_size_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_type_size, test/functorch/test_control_flow.py::TestControlFlowTraced::test_raise_error_on_mismatch_type_size_fake_tensor, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_functionalized_elem_alias, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_functionalized_elem_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_scan_pytree_closure, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_aot_functionalized, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_symbolic_dict, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_symbolic_list, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_autograd_symbolic_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_real, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_symbolic_dict, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_symbolic_list, test/functorch/test_control_flow.py::TestControlFlowTraced::test_tracing_map_symbolic_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_two_hops_not_sharing_code_obj, test/functorch/test_control_flow.py::TestControlFlowTraced::test_vmap_vmap_boolcond_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_vmap_vmap_boolcond_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_const_and_symint_output, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_nested_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_pytree_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_aot_eager_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_const_and_symint_output, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_nested_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_pytree_int_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_compile_backend_eager_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_cpp_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_functorch_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_no_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_functionalize_func_type_python_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_nested2_traced, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_nested_traced, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_compile_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_False_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_False_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_True_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_constant_and_symint_output_export_strict_True_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_compile_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_export_strict_False_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_export_strict_False_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_export_strict_True_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_int_carry_export_strict_True_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_mismatch_in_meta, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_False_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_False_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_True_backend_aot_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_compile_dynamic_True_backend_eager, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_False_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_False_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_True_dynamic_False, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_op_pytree_int_carry_export_strict_True_dynamic_True, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_cpp, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_functorch, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_no, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_functionalize_check_graph_func_type_python, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_simple_with_linear_compile_check_graph, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_nested, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_nested2, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_nested_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple_with_linear, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple_with_mutation, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_tracing_while_loop_test_simple_with_pytree_carry, test/functorch/test_control_flow.py::TestControlFlowTraced::test_while_loop_unbacked_bindings, test/functorch/test_control_flow.py::TestHopSchema::test_associative_scan_gen_schema_multiple_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_associative_scan_gen_schema_tensor_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_associative_scan_gen_schema_with_additional_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_cond_gen_schema_symbool_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_cond_gen_schema_tensor_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_function_schema_gen, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_GraphModule, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_ScriptObj, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_SymBool, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_SymInt, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_Tensor, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_bool, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_float, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_int, test/functorch/test_control_flow.py::TestHopSchema::test_list_gen_schema_type_str, test/functorch/test_control_flow.py::TestHopSchema::test_scan_gen_schema_multiple_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_scan_gen_schema_tensor_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_scan_gen_schema_with_additional_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_schema_tree_spec, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_GraphModule, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_ScriptObj, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_SymBool, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_SymInt, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_Tensor, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_bool, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_float, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_int, test/functorch/test_control_flow.py::TestHopSchema::test_type_gen_schema_type_str, test/functorch/test_control_flow.py::TestHopSchema::test_while_loop_gen_schema_tensor_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_while_loop_gen_schema_with_additional_inputs, test/functorch/test_control_flow.py::TestHopSchema::test_while_loop_gen_schema_with_input_mutation, test/functorch/test_control_flow.py::TestHopSchema::test_while_loop_gen_schema_with_int_carries 2025-08-26T20:27:30.1895536Z 2025-08-26T20:27:33.2256387Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:27:33.2259456Z import pkg_resources 2025-08-26T20:27:33.3507840Z Running functorch/test_aotdispatch 3/6 ... [2025-08-26 20:27:33.350425] 2025-08-26T20:27:33.3508708Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:27:33.3510942Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aotdispatch.py', '-m', 'not serial', '--shard-id=3', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:27:33.350750] 2025-08-26T20:32:12.6260788Z 2025-08-26T20:32:12.6264324Z inductor/test_compile_subprocess 2/2 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_compile_subprocess_2.2_ebc55b81b58feeb0_.log 2025-08-26T20:32:12.6588193Z Running 438 items in this shard: test/inductor/test_compile_subprocess.py::TestSubprocess::test_async, test/inductor/test_compile_subprocess.py::CpuTests::test__dyn_quant_matmul_4bit_cpu, test/inductor/test_compile_subprocess.py::CpuTests::test__dyn_quant_pack_4bit_weight_cpu, test/inductor/test_compile_subprocess.py::CpuTests::test__unsafe_masked_index_cpu, test/inductor/test_compile_subprocess.py::CpuTests::test__unsafe_masked_index_put_accumulate_cpu, test/inductor/test_compile_subprocess.py::CpuTests::test_abs_cpu, test/inductor/test_compile_subprocess.py::CpuTests::test_adaptive_avg_pool2d2_cpu, test/inductor/test_compile_subprocess.py::CpuTests::test_adaptive_avg_pool_errors_with_long_cpu, 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test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_duplicated_arguments_on_tensor_overlap, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_grad_context, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_alias_everything, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_aliases_and_none_require_gradients, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_metadata2, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_noncontiguous, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_storage_resize_before_set_, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_inputs_overlapping_with_mutation_guard_base, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_invalid_dupe_left_bias, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_list_codegen, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mark_activations_dynamic, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mark_activations_dynamic_with_nested, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mark_outputs_dynamic_use_autograd_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mutations_in_bw_detached_from_tangent, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_non_tensor_and_none_inputs, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_input_multi_output_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_mutation_linear, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_all_alias_types, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_saved_tensors_hooks_mutations_raise, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_subclasses_mixed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_view_detach, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_alias_of_intermediate_detach_backend_inductor_view_replay_for_aliased_outputs_False_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_backward_mutation_data, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_complex_linear, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_composite_impl_compile, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_custom_autograd, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_duplicated_arguments_on_tensor_overlap, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_grad_context, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_inference_mode, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_aliased_with_mutation_output_alias, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_inplace_requires_grad_true, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_set__nop, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_storage_resize_down_and_set_, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_output_aliase_custom_autograd_function, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_output_view_simple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_inputs_overlapping_unsqueeze_with_mutation, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_invalid_requires_grad_fake, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_mark_outputs_dynamic_use_autograd_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_nested_subclasses_complicated_inps_mixed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_and_returned_flipped, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_no_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_returned_multiple_times, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_view_meta_replay, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_all_alias_types, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_set__not_allowed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_subclass_metadata_mutation_req_grad_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_subclasses_mixed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_view_detach 2025-08-26T20:32:15.4497192Z 2025-08-26T20:32:15.8623880Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:32:15.8625651Z import pkg_resources 2025-08-26T20:32:16.0145897Z Running test_indexing 1/1 ... [2025-08-26 20:32:16.014242] 2025-08-26T20:32:16.0146683Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:32:16.0150220Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:32:16.014692] 2025-08-26T20:32:18.9343363Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:32:18.9346516Z import pkg_resources 2025-08-26T20:32:19.0564261Z Running test_type_promotion 1/1 ... [2025-08-26 20:32:19.056126] 2025-08-26T20:32:19.0564730Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:32:19.0567031Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_type_promotion.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:32:19.056472] 2025-08-26T20:32:23.4406903Z 2025-08-26T20:32:23.4407958Z test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_indexing_1.1_ec84b3aa2dc298b9_.log 2025-08-26T20:32:23.4465427Z Running 184 items in this shard: test/test_indexing.py::TestIndexingCPU::test_advancedindex_big_cpu, test/test_indexing.py::TestIndexingCPU::test_advancedindex_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_advancedindex_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_basic_advanced_combined_cpu, test/test_indexing.py::TestIndexingCPU::test_bool_indices_accumulate_cpu, test/test_indexing.py::TestIndexingCPU::test_bool_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_bool_mask_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_mask2d_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_mask_accumulate_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_byte_tensor_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_cpu_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_cuda_broadcast_index_use_deterministic_algorithms_cpu, test/test_indexing.py::TestIndexingCPU::test_ellipsis_tensor_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_index_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_ndim_index_bool_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_ndim_index_cpu, test/test_indexing.py::TestIndexingCPU::test_empty_slice_cpu, test/test_indexing.py::TestIndexingCPU::test_errors_index_copy_cpu, test/test_indexing.py::TestIndexingCPU::test_gather_take_along_dim_cross_device_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_getitem_scalars_cpu, test/test_indexing.py::TestIndexingCPU::test_index_add_deterministic_cpu, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_complex128, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_complex64, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_copy_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_copy_deterministic_cpu, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_complex128, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_complex64, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_copy_scalars_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_cpu, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_complex128, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_complex64, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_fill_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_getitem_copy_bools_slices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_ind_dtype_cpu, test/test_indexing.py::TestIndexingCPU::test_index_limits_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_duplicate_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_empty_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_expanded_values_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_large_tensor_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_accumulate_non_contiguous_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_deterministic_with_optional_tensors_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_large_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_non_accumulate_deterministic_cpu, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_complex128, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_complex64, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_put_src_datatype_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amax_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_amin_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_mean_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_reduce_reduce_prod_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_scalar_with_bool_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_complex128, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_complex64, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_float16, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_float64, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_float8_e4m3fn, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_float8_e4m3fnuz, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_float8_e5m2, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_float8_e5m2fnuz, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_int16, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_int32, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_int8, test/test_indexing.py::TestIndexingCPU::test_index_select_cpu_uint8, test/test_indexing.py::TestIndexingCPU::test_index_setitem_bools_slices_cpu, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_bfloat16, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_bool, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_index_src_datatype_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_int_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_int_indices2d_cpu, test/test_indexing.py::TestIndexingCPU::test_int_indices_broadcast_cpu, test/test_indexing.py::TestIndexingCPU::test_int_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_invalid_device_cpu, test/test_indexing.py::TestIndexingCPU::test_invalid_index_cpu, test/test_indexing.py::TestIndexingCPU::test_jit_indexing_cpu, test/test_indexing.py::TestIndexingCPU::test_list_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_multi_dimensional_bool_mask_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_multi_dimensional_bool_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_multiple_bool_indices_cpu, test/test_indexing.py::TestIndexingCPU::test_multiple_byte_mask_cpu, test/test_indexing.py::TestIndexingCPU::test_multiple_int_cpu, test/test_indexing.py::TestIndexingCPU::test_none_cpu, test/test_indexing.py::TestIndexingCPU::test_out_of_bound_index_cpu, test/test_indexing.py::TestIndexingCPU::test_set_item_to_scalar_tensor_cpu, test/test_indexing.py::TestIndexingCPU::test_setitem_expansion_error_cpu, test/test_indexing.py::TestIndexingCPU::test_setitem_scalars_cpu, test/test_indexing.py::TestIndexingCPU::test_single_int_cpu, test/test_indexing.py::TestIndexingCPU::test_step_assignment_cpu, test/test_indexing.py::TestIndexingCPU::test_step_cpu, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_invalid_cpu_float32, test/test_indexing.py::TestIndexingCPU::test_take_along_dim_invalid_cpu_int64, test/test_indexing.py::TestIndexingCPU::test_unravel_index_errors_cpu, test/test_indexing.py::TestIndexingCPU::test_variable_slicing_cpu, test/test_indexing.py::TestIndexingCPU::test_zero_dim_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_assignment_value_mismatch_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_alldims_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_onedim_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_twodim_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_weirdness_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_indexing_weirdness_tensors_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_list_indexing_cpu, test/test_indexing.py::NumpyTestsCPU::test_boolean_shape_mismatch_cpu, test/test_indexing.py::NumpyTestsCPU::test_broadcast_subspace_cpu, test/test_indexing.py::NumpyTestsCPU::test_broaderrors_indexing_cpu, test/test_indexing.py::NumpyTestsCPU::test_ellipsis_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_empty_fancy_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_empty_tuple_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_everything_returns_views_cpu, test/test_indexing.py::NumpyTestsCPU::test_index_is_larger_cpu, test/test_indexing.py::NumpyTestsCPU::test_index_no_floats_cpu, test/test_indexing.py::NumpyTestsCPU::test_none_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_single_bool_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_single_int_index_cpu, test/test_indexing.py::NumpyTestsCPU::test_trivial_fancy_out_of_bounds_cpu, test/test_indexing.py::NumpyTestsCPU::test_truncate_leading_1s_cpu 2025-08-26T20:32:23.4521707Z 2025-08-26T20:32:25.7300142Z 2025-08-26T20:32:25.7300919Z test_type_promotion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_type_promotion_1.1_b46faea8760813c6_.log 2025-08-26T20:32:25.7478389Z Running 423 items in this shard: test/test_type_promotion.py::TestTypePromotionCPU::test_add_wrapped_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_alpha_mismatch_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_alternate_result_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_bfloat16_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_booleans_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_can_cast_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_cat_different_dtypes_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_cat_out_different_dtypes_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_bool_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_bool_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_bool_bool, 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test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float32_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_bool_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_bool_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_clamp_type_promotion_cpu_float64_bool_float64, 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test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int32_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int32_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int32_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int64_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_int8_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_numpy_array_binary_ufunc_promotion_cpu_uint8_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_promote_self_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_promote_types_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bfloat16_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_bool_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex128_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_complex64_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float16_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float32_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_float64_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int16_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int32_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int64_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_int8_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_bfloat16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_float16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_int8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_cpu_uint8_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_result_type_tensor_vs_scalar_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_add_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_bool, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_int16, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_int32, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_div_promotion_cpu_uint8, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_mul_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_sparse_sub_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_ternary_out_promotion_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_transpose_cpu, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex128_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_complex64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float32_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_float64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_complex128, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_complex64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_float32, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_float64, test/test_type_promotion.py::TestTypePromotionCPU::test_unary_op_out_casting_cpu_int64_int64, test/test_type_promotion.py::TestTypePromotionCPU::test_unsigned_cpu 2025-08-26T20:32:25.7651192Z 2025-08-26T20:32:26.8545781Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:32:26.8547343Z import pkg_resources 2025-08-26T20:32:26.9762708Z Running functorch/test_eager_transforms 1/1 ... [2025-08-26 20:32:26.975982] 2025-08-26T20:32:26.9763227Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:32:26.9765359Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_eager_transforms.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:32:26.976295] 2025-08-26T20:32:28.8996650Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:32:28.8999580Z import pkg_resources 2025-08-26T20:32:29.0211242Z Running inductor/test_flex_decoding 1/1 ... [2025-08-26 20:32:29.020705] 2025-08-26T20:32:29.0212152Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:32:29.0214605Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_flex_decoding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:32:29.021115] 2025-08-26T20:32:35.2945324Z 2025-08-26T20:32:35.2946392Z inductor/test_flex_decoding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_flex_decoding_1.1_9e509b5fbe482cb5_.log 2025-08-26T20:32:35.3221348Z Running 483 items in this shard: test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_builtin_score_mods_bfloat16_score_mod0_head_dims0_cpu_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_builtin_score_mods_bfloat16_score_mod0_head_dims1_cpu_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_builtin_score_mods_bfloat16_score_mod0_head_dims2_cpu_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_builtin_score_mods_bfloat16_score_mod1_head_dims0_cpu_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_builtin_score_mods_bfloat16_score_mod1_head_dims1_cpu_bfloat16, 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test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod7_head_dims0_page_size_64_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod7_head_dims1_page_size_128_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod7_head_dims1_page_size_256_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod7_head_dims1_page_size_64_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod7_head_dims2_page_size_128_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod7_head_dims2_page_size_256_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod7_head_dims2_page_size_64_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims0_page_size_128_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims0_page_size_256_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims0_page_size_64_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims1_page_size_128_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims1_page_size_256_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims1_page_size_64_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims2_page_size_128_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims2_page_size_256_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_paged_attention_page_size_float32_score_mod8_head_dims2_page_size_64_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_recompile_changed_score_mod_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_seq_masking_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_silu_on_score_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_skip_odd_keys_bfloat16_cpu_bfloat16, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_skip_odd_keys_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s0_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s0_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s0_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s1_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s1_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s1_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s2_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s2_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s2_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s3_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s3_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s0_v_s3_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s0_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s0_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s0_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s1_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s1_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s1_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s2_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s2_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s2_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s3_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s3_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s1_v_s3_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s0_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s0_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s0_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s1_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s1_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s1_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s2_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s2_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s2_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s3_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s3_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s2_v_s3_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s0_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s0_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s0_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s1_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s1_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s1_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s2_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s2_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s2_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s3_head_dims0_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s3_head_dims1_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_strided_inputs_float32_k_s3_v_s3_head_dims2_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_subgraph_respect_decompostion_float32_cpu_float32, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_windowed_full_mask_vs_sdpa_cpu, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_windowed_full_mask_vs_sdpa_paged_attention_cpu, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_windowed_no_mask_vs_sdpa_cpu, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_windowed_no_mask_vs_sdpa_paged_attention_cpu, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_windowed_partial_block_vs_sdpa_cpu, test/inductor/test_flex_decoding.py::TestFlexDecodingCPU::test_windowed_partial_block_vs_sdpa_paged_attention_cpu 2025-08-26T20:32:35.3486655Z 2025-08-26T20:32:39.5348980Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:32:39.5350800Z import pkg_resources 2025-08-26T20:32:39.6570927Z Running export/test_export_training_ir_to_run_decomp 1/1 ... [2025-08-26 20:32:39.656747] 2025-08-26T20:32:39.6571478Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:32:39.6573965Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_training_ir_to_run_decomp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:32:39.657121] 2025-08-26T20:32:46.9191642Z 2025-08-26T20:32:46.9192641Z functorch/test_eager_transforms 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_eager_transforms_1.1_26fcfd3dc279deb0_.log 2025-08-26T20:32:46.9356318Z Running 355 items in this shard: test/functorch/test_eager_transforms.py::TestSliceArgnums::test_argnums_reorders, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_duplicate_argnums, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_flat_args_with_negative_int_argnum, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_flat_args_with_positive_int_argnum, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_flat_args_with_tuple_argnum, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_invalid_argnum_type, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_not_enough_argnums, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_out_of_bounds_argnum_values, test/functorch/test_eager_transforms.py::TestSliceArgnums::test_pytree_args, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_buffer_tying, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_combine_state_for_ensemble_error, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_combine_state_for_ensemble_smoke, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_correctness_mnist_mechanism_functional_call, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_correctness_mnist_mechanism_make_functional, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_disable_autograd_tracking_disable_autograd_tracking_False, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_disable_autograd_tracking_disable_autograd_tracking_True, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_make_functional_state_correctly_returned_after_forward_mechanism_functional_call, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_make_functional_state_correctly_returned_after_forward_mechanism_make_functional, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_parameter_tying, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_parameter_tying_ensemble, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_parameter_tying_grad, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_stack_module_state_error, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_stack_module_state_leaf, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_stack_module_state_mismatch_error, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_stack_module_state_smoke, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_using_detach_functional_call_detach_params_False, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_using_detach_functional_call_detach_params_True, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_with_buffers_disable_autograd_tracking_disable_autograd_tracking_False, test/functorch/test_eager_transforms.py::TestMakeFunctional::test_with_buffers_disable_autograd_tracking_disable_autograd_tracking_True, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_advanced_indexing_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_argnums_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_composed_with_autograd_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_composite_complicated_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_composite_simple_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_composite_two_ops_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_conj_bit_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_dtype_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_escaped_wrappers_are_ignored_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_escaped_wrappers_are_marked_as_dead_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_fn_with_kwargs_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_functional_init_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_functional_init_with_buffers_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_grad_aux_pytree_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_grad_aux_tensor_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_grad_of_vjp_composition_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_grad_of_vjp_of_grad_composition_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_grad_pytree_inputs_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_inplace_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_inplace_on_captures_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_inplace_on_view_base_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_inplace_on_view_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_invalid_argnums_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_is_cuda_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_manual_seed_inside_grad_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_negative_argnums_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_nesting_simple_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_inside_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_mixed_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_nested_complicated_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_nested_simple_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_outside_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_outside_vjp_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_outside_vjp_fn_cpu, test/functorch/test_eager_transforms.py::TestGradTransformCPU::test_no_grad_outside_vjp_only_cpu, 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test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_find_learning_rate_ensembling_FeatureAlphaDropout_mechanism_make_functional_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_lennard_jones_batched_jac_jac_jacfwd_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_lennard_jones_batched_jac_jac_jacrev_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_maml_omniglot_mechanism_functional_call_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_maml_omniglot_mechanism_make_functional_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_maml_regression_mechanism_functional_call_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_maml_regression_mechanism_make_functional_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_resnet18_per_sample_grads_mechanism_functional_call_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_resnet18_per_sample_grads_mechanism_make_functional_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_update_batch_norm_mechanism_functional_call_originally_track_running_stats_False_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_update_batch_norm_mechanism_functional_call_originally_track_running_stats_True_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_update_batch_norm_mechanism_make_functional_originally_track_running_stats_False_cpu, test/functorch/test_eager_transforms.py::TestExamplesCorrectnessCPU::test_update_batch_norm_mechanism_make_functional_originally_track_running_stats_True_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_basic_sum_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_functional_call_multiple_dicts_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_grad_grad_sum_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_grad_name_wrapping_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_grad_sum_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_no_grad_inside_grad_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_no_grad_outside_grad_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_vmap_grad_sum_cpu, test/functorch/test_eager_transforms.py::TestHigherOrderOperatorInteractionCPU::test_vmap_sum_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_fake_tensors_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_fx_multi_out_op_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_fx_out_op_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_fx_reapply_views_simple_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_fx_simple_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_fx_transpose_simple_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_grad_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_nonfunctional_output_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_opt_tensor_list_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_optional_tensorlist1_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_functionalize_optional_tensorlist2_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_inplace_view_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_linear_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_multioutput_inplace_slice_view_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_multioutput_view_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_resize_program_inputs_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_simple_view_cpu, test/functorch/test_eager_transforms.py::TestFunctionalizeCPU::test_vmap_functionalize_jvp_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_jvp_save_tensors_input_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_jvp_save_tensors_input_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_jvp_save_tensors_neither_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_jvp_save_tensors_neither_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_jvp_save_tensors_output_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_jvp_save_tensors_output_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_vjp_save_tensors_input_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_vjp_save_tensors_input_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_vjp_save_tensors_neither_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_vjp_save_tensors_neither_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_vjp_save_tensors_output_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_False_save_for_vjp_save_tensors_output_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_jvp_save_tensors_input_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_jvp_save_tensors_input_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_jvp_save_tensors_neither_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_jvp_save_tensors_neither_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_jvp_save_tensors_output_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_jvp_save_tensors_output_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_vjp_save_tensors_input_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_vjp_save_tensors_input_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_vjp_save_tensors_neither_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_vjp_save_tensors_neither_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_vjp_save_tensors_output_mark_dirty_False_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_function_returns_input_inner_requires_grad_True_save_for_vjp_save_tensors_output_mark_dirty_True_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_grad_fn_name_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_needs_input_grads_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_once_differentiable_autograd_vjp_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_once_differentiable_grad_vjp_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionCPU::test_set_materialize_grads_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_has_vmap_staticmethod_and_has_generate_vmap_rule_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_in_dims_multiple_inputs_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_in_dims_single_input_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_incompatible_out_dims_error_msg_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_info_object_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_kwarg_only_tensors_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_no_vmap_staticmethod_and_no_generate_vmap_rule_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_none_returns_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_should_have_two_returns_cpu, test/functorch/test_eager_transforms.py::TestAutogradFunctionVmapAPICPU::test_skips_empty_layer_cpu, test/functorch/test_eager_transforms.py::TestHelpersCPU::test_CtxWithSavedTensors_error_if_name_collision_cpu, test/functorch/test_eager_transforms.py::TestHelpersCPU::test_CtxWithSavedTensors_nesting_cpu, test/functorch/test_eager_transforms.py::TestHelpersCPU::test_CtxWithSavedTensors_overrides_saved_tensors_cpu, test/functorch/test_eager_transforms.py::TestHelpersCPU::test_CtxWithSavedTensors_passthrough_cpu, test/functorch/test_eager_transforms.py::TestHelpersCPU::test_debug_unwrap_cpu, test/functorch/test_eager_transforms.py::TestHelpersCPU::test_reductify_leaf_cpu, test/functorch/test_eager_transforms.py::TestCompileTransformsCPU::test_compile_vmap_hessian_cpu, test/functorch/test_eager_transforms.py::TestCompileTransformsCPU::test_grad_deprecated_api_cpu 2025-08-26T20:32:46.9516763Z 2025-08-26T20:32:50.1063794Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:32:50.1067137Z import pkg_resources 2025-08-26T20:32:50.2285558Z Running inductor/test_pattern_matcher 1/1 ... [2025-08-26 20:32:50.228236] 2025-08-26T20:32:50.2286050Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:32:50.2288191Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_pattern_matcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:32:50.228569] 2025-08-26T20:32:57.2720421Z 2025-08-26T20:32:57.2722017Z inductor/test_pattern_matcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_pattern_matcher_1.1_4eeb7f04c257da6b_.log 2025-08-26T20:32:57.2723544Z 2025-08-26T20:33:00.6405817Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:33:00.6407392Z import pkg_resources 2025-08-26T20:33:00.7617114Z Running inductor/test_inductor_utils 1/1 ... [2025-08-26 20:33:00.761371] 2025-08-26T20:33:00.7617630Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:33:00.7619893Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inductor_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:33:00.761741] 2025-08-26T20:33:03.9740344Z 2025-08-26T20:33:03.9741512Z inductor/test_inductor_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inductor_utils_1.1_6ed74e05b459072b_.log 2025-08-26T20:33:03.9742301Z 2025-08-26T20:33:07.4658085Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:33:07.4660689Z import pkg_resources 2025-08-26T20:33:07.5899590Z Running inductor/test_torchinductor_strided_blocks 1/1 ... [2025-08-26 20:33:07.589591] 2025-08-26T20:33:07.5900425Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:33:07.5902263Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_torchinductor_strided_blocks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:33:07.589930] 2025-08-26T20:33:14.9992001Z 2025-08-26T20:33:14.9993846Z inductor/test_torchinductor_strided_blocks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_torchinductor_strided_blocks_1.1_5d30fc80f400d7f1_.log 2025-08-26T20:33:14.9995612Z 2025-08-26T20:33:18.2795609Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:33:18.2798501Z import pkg_resources 2025-08-26T20:33:18.4015410Z Running inductor/test_subgraph_choice 1/1 ... [2025-08-26 20:33:18.401152] 2025-08-26T20:33:18.4016217Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:33:18.4018374Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_subgraph_choice.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:33:18.401506] 2025-08-26T20:33:25.9407042Z 2025-08-26T20:33:25.9408716Z inductor/test_subgraph_choice 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_subgraph_choice_1.1_c7ccc1b2fec51df3_.log 2025-08-26T20:33:25.9410437Z 2025-08-26T20:33:29.0332139Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:33:29.0333708Z import pkg_resources 2025-08-26T20:33:29.1530248Z Running inductor/test_aot_inductor_package 1/1 ... [2025-08-26 20:33:29.152635] 2025-08-26T20:33:29.1531216Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:33:29.1534183Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_aot_inductor_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:33:29.153012] 2025-08-26T20:33:35.9958570Z 2025-08-26T20:33:35.9959559Z inductor/test_aot_inductor_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_aot_inductor_package_1.1_3bd378ab4e4eeaaf_.log 2025-08-26T20:33:35.9960389Z 2025-08-26T20:33:39.1707372Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:33:39.1710455Z import pkg_resources 2025-08-26T20:33:39.3297893Z Running inductor/test_triton_heuristics 1/1 ... [2025-08-26 20:33:39.329385] 2025-08-26T20:33:39.3298868Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:33:39.3302033Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_triton_heuristics.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:33:39.329827] 2025-08-26T20:33:46.2658936Z 2025-08-26T20:33:46.2659977Z inductor/test_triton_heuristics 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_triton_heuristics_1.1_329bc94f28be7ec0_.log 2025-08-26T20:33:46.2660773Z 2025-08-26T20:33:50.0173779Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:33:50.0176975Z import pkg_resources 2025-08-26T20:33:50.1922280Z Running inductor/test_inplacing_pass 1/1 ... [2025-08-26 20:33:50.191902] 2025-08-26T20:33:50.1922780Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:33:50.1924814Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_inplacing_pass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:33:50.192226] 2025-08-26T20:33:57.2139606Z 2025-08-26T20:33:57.2140918Z inductor/test_inplacing_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_inplacing_pass_1.1_70ceca27ba424187_.log 2025-08-26T20:33:57.2141710Z 2025-08-26T20:34:00.3737237Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:34:00.3739238Z import pkg_resources 2025-08-26T20:34:00.4970486Z Running inductor/test_online_softmax 1/1 ... [2025-08-26 20:34:00.496734] 2025-08-26T20:34:00.4971002Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:34:00.4973750Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_online_softmax.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:34:00.497080] 2025-08-26T20:34:07.7022590Z 2025-08-26T20:34:07.7024158Z inductor/test_online_softmax 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_online_softmax_1.1_02723381bb5314f9_.log 2025-08-26T20:34:10.9431950Z 2025-08-26T20:34:10.9433836Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:34:10.9435430Z import pkg_resources 2025-08-26T20:34:11.0665123Z Running inductor/test_cpu_select_algorithm 4/16 ... [2025-08-26 20:34:11.066169] 2025-08-26T20:34:11.0665701Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:34:11.0667538Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'not serial', '--shard-id=4', '--num-shards=16', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:34:11.066529] 2025-08-26T20:39:11.7361020Z 2025-08-26T20:39:11.7362009Z functorch/test_aotdispatch 3/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aotdispatch_3.6_f178b0e1c3b80dad_.log 2025-08-26T20:39:11.7567589Z Running 385 items in this shard: test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_False_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_True_dynamic_shapes_False, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_alias_of_intermediate_detach_backend_inductor_view_replay_for_aliased_outputs_False_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_backward_mutation_forward_inputs, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_backward_mutation_forward_inputs_create_graph, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_batch_norm_amp, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_batchnorm_inference, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_buffer_batch_norm, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_complex_linear, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_grad_context, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_inference_mode, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_inner_grad, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_aliased_with_mutation_output_alias, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_metadata2, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_requires_grad_no_grad_detach_mixed, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_input_mutation_set__nop, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_mark_activations_dynamic, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_mem_leak_from_save_for_bw, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_multi_output_list, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_nested_subclasses_complicated_inps_mixed, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_input_multi_output_view_should_raise_autograd_error, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_inplace_view, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_inplace_view_with_detach, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_aliases_intermediate_single, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_output_all_alias_types, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_some_outputs_dont_require_grad_view, test/functorch/test_aotdispatch.py::TestAOTAutograd::test_subclass_metadata_mutation_req_grad_True, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_module_joint, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_multiple_outputs_require_grad_banned, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_buffer_mutation_metadata, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_composite_implicit_linear, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_contiguous, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_map_2, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_predispatch_with_cond, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_simplified_basic, test/functorch/test_aotdispatch.py::TestAOTExport::test_aot_export_synthetic_bases_banned, test/functorch/test_aotdispatch.py::TestPartitioning::test_default_partitioner_output_tensor_shape_tensor, test/functorch/test_aotdispatch.py::TestPartitioning::test_min_cut_partitioner, test/functorch/test_aotdispatch.py::TestAOTDispatch::test_aot_dispatch_inference, test/functorch/test_aotdispatch.py::TestAOTDispatch::test_aot_dispatch_input_mutation, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_aot_module_simplified_preserves_stack_trace_from_mutation, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_noncontig_nonmemformat_tangents_dynamic_shapes_False_test_subclasses_False_device_cuda, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_noncontig_nonmemformat_tangents_dynamic_shapes_False_test_subclasses_True_device_cuda, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_saved_tensors_hooks_base_saved_tensors_hooks_filtering_mode_donated, test/functorch/test_aotdispatch.py::TestAOTModuleSimplified::test_saved_tensors_hooks_donated_buffers, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_make_fx_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_make_fx_no_decompose_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_nnc_jit_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_resnet18_backward_trace_cpu, test/functorch/test_aotdispatch.py::TestPythonKeyCPU::test_scalar_device_cpu, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive__batch_norm_with_update_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_add_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_addcdiv_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_all_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_any_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_argsort_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_as_strided_scatter_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_auto_functionalize_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_broadcast_tensors_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cauchy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cdouble_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cholesky_inverse_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_clone_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cond_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_corrcoef_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cosh_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_cumulative_trapezoid_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_diff_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_digamma_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_div_floor_rounding_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_div_no_rounding_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_dstack_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_exp_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_hfft_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_hfftn_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_rfft2_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_fft_rfft_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_frexp_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_ge_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_gradient_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_half_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_heaviside_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_i0_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_igammac_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_index_fill_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_invoke_quant_packed_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_invoke_subgraph_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_isin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_cholesky_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_eig_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_eigvals_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_householder_product_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_lstsq_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_multi_dot_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_pinv_hermitian_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_solve_ex_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_linalg_solve_triangular_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_log10_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_log_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_log_softmax_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_logaddexp2_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_logaddexp_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_logit_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_long_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_lu_solve_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_mH_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_map_simple_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_amax_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_amin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_argmax_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_argmin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_fill_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_norm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_normalize_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_scatter_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_select_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_softmin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_masked_var_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_max_reduction_no_dim_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_max_reduction_with_dim_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_minimum_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nanmean_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nanquantile_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_narrow_copy_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_native_layer_norm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_avg_pool1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_conv2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_gelu_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_interpolate_bicubic_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_kl_div_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_local_response_norm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_nll_loss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_pad_circular_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_rms_norm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_silu_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_softplus_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_norm_fro_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_normal_in_place_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionOpInfoCPU::test_aot_autograd_exhaustive_pinverse_cpu_float32, 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test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_BCEWithLogitsLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ConstantPad3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Embedding_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_FractionalMaxPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_GELU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_GRU_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_InstanceNorm2d_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_InstanceNorm3d_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LPPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LazyConv3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Linear_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_LocalResponseNorm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_MultiMarginLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_MultiheadAttention_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_RNN_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReLU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReflectionPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReflectionPad2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_ReplicationPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Sigmoid_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Softmin_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_Softplus_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_module_exhaustive_nn_TransformerEncoder_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AdaptiveAvgPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AdaptiveMaxPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AvgPool2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_AvgPool3d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ConstantPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_GELU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_GRU_train_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_GroupNorm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_HuberLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_LayerNorm_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_LazyConvTranspose2d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Mish_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_MultiLabelSoftMarginLoss_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_RNNCell_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ReLU_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_ReplicationPad1d_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Tanh_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Threshold_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_TransformerEncoderLayer_eval_mode_cpu_float32, test/functorch/test_aotdispatch.py::TestEagerFusionModuleInfoCPU::test_aot_autograd_symbolic_module_exhaustive_nn_Transformer_cpu_float32, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_alias_of_intermediate_detach_backend_inductor_view_replay_for_aliased_outputs_True_dynamic_shapes_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_backward_mutation_on_grad_out, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_batchnorm, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_batchnorm_inference, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_inference_mode, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_metadata_mutation_aliases, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_false_aliasing, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_requires_grad_detach, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_mutation_requires_grad_no_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_input_output_view_mutate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_mutation_of_input_in_fw_and_bw, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_nested_subclasses, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_nested_subclasses_complicated_inps, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_nested_subclasses_complicated_inps_mixed, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_new_inp_requires_grad_now, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_multi_output_view, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_intermediate_view_meta_replay, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_output_aliases_output_view_meta_replay, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_set__and_data_mutation_good, test/functorch/test_aotdispatch.py::TestAOTAutogradWithDynamo::test_subclass_metadata_mutation_req_grad_True, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_alias_of_intermediate_detach_backend_aot_eager_view_replay_for_aliased_outputs_False_dynamic_shapes_False, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_backward_pass_autocast_custom, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_backward_pass_autocast_on, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_batch_norm_amp, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_compilation_context, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_embedding_bag_view_dynamic, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_aliases_and_none_require_gradients, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_aliases_and_output_alias, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_is_output, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_metadata2, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_mutation_noncontiguous, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_input_output_view_metadata_mutate_multiple, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_invalid_dupe_fake, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_invalid_requires_grad, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_mark_outputs_dynamic_use_autograd_False, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_module, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_multi_output_list, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_no_grad_input_output, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_and_returned, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_output_aliases_intermediate_single, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_real_weights_in_symbolic_mode_with_inplace_ops, test/functorch/test_aotdispatch.py::TestAOTAutogradWithCache::test_saved_tensors_hooks_mutations_raise 2025-08-26T20:39:11.7768613Z 2025-08-26T20:39:14.8527950Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:39:14.8529575Z import pkg_resources 2025-08-26T20:39:14.9728392Z Running inductor/test_cpu_select_algorithm 8/16 ... [2025-08-26 20:39:14.972486] 2025-08-26T20:39:14.9729058Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:39:14.9730870Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'not serial', '--shard-id=8', '--num-shards=16', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:39:14.972810] 2025-08-26T20:41:15.0843269Z 2025-08-26T20:41:15.0844417Z export/test_export_training_ir_to_run_decomp 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_training_ir_to_run_decomp_1.1_3fd39ceeb15712ba_.log 2025-08-26T20:41:15.1459038Z Running 822 items in this shard: test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_export_assume_static_by_default_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_export_constraints_error_not_in_range_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_export_constraints_error_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_export_inline_constraints_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_export_slice_maxsize_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_export_slice_unbacked_dim1_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_export_strict_narrow_unbacked_expr_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_no_grad_param_inplace_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestDynamismExpression::test_reshape_view_backed_size_oblivious_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_export_assume_static_by_default_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_export_constraints_error_not_in_range_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_export_constraints_error_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_export_inline_constraints_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_export_slice_maxsize_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_export_slice_unbacked_dim1_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_export_strict_narrow_unbacked_expr_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_no_grad_param_inplace_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestDynamismExpression::test_reshape_view_backed_size_oblivious_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test__scaled_dot_product_flash_attention_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_additional_inputs_constants_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_allow_explicit_guards_as_runtime_asserts_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_args_type_checked_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_aten_lift_fresh_copy_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_attention_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_attr_assignment_extra_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_automatic_constrain_size_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_automatic_dynamic_shapes_constant_relation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_automatic_dynamic_shapes_linear_relation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_automatic_dynamic_shapes_simple_equality_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_baddbmm_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_basic_non_strict_fake_tensor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_basic_non_strict_real_tensor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_basic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_bincount_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_buffer_util_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_capture_subclass_constructor_torch_ir_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_capture_subclass_constructor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_capture_subclass_wrong_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_ccode_python_mod_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_check_specialized_int_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_checks_to_constrain_range_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cleanup_dynamic_markers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_colin_unbacked_backed_vr_sub_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_colon_parameter_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_compiling_state_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_access_identical_symint_closure_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_branches_return_constant_int_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_branches_return_same_int_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_buffers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_contains_unbacked_no_escape_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_int_closure_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_unflatten_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_with_module_stack_export_with_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cond_with_module_stack_export_with_unflatten_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_aliasing_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_input_naming_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_no_user_inp_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_output_dup_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_output_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_requires_grad_const_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_return_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_tensor_mutation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_tensor_with_non_functional_nested_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constant_tensor_with_non_functional_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constrain_decomp_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constrain_size_in_eager_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constrain_size_with_constrain_value_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_constrain_size_with_various_cases_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_conv_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_crop_like_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_cse_for_symint_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_custom_op_auto_functionalize_pre_dispatch_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_custom_op_auto_functionalize_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_custom_op_auto_warn_pre_dispatch_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_custom_op_preserve_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_custom_pytree_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_custom_tag_metadata_re_export_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_decomp_batch_norm_functional_predispatch_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_decomp_item_in_prim_after_decomposition_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_decomp_item_in_prim_before_decomposition_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_default_decomposition_core_cia_ops_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_1_2_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_basic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_integer_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_nested_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_out_of_order_repeat_derived_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_out_of_order_simplified_repeat_non_derived_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_out_of_order_simplified_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_out_of_order_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_derived_dim_repeat_derived_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_detect_leak_strict_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_device_to_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_device_to_gpu_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_device_to_mutation_float_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_device_to_mutation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_device_to_static_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dim_1_2_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dim_auto_and_dim_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dim_dynamic_divisibility_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dim_dynamic_specialization_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dim_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dim_hint_range_violations_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dim_hint_ranges_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_disable_forced_specializations_errors_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_disable_forced_specializations_ok_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_distributed_all_gather_into_tensor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_distributed_all_gather_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_distributed_all_reduce_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_distributed_all_to_all_single_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_distributed_reduce_scatter_tensor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dont_duck_size_for_auto_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_double_lifted_constants_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_draft_export_checks_aliasing_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_draft_export_checks_mutation_list_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_draft_export_checks_mutation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_draft_export_checks_mutation_with_nan_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_draft_export_fake_kernel_inference_errors_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_draft_export_infers_fake_kernel_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_duplicate_modules_with_non_persistent_buffers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_lr_shift_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_bounds_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_builder_basic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_builder_kwargs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_builder_pytree_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_dataclass_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_inferred_basic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_serdes_generic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_serdes_user_errors_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_serdes_various_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_shapes_spec_with_pytree_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_dynamic_sym_round_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_ends_of_bounds_oblivious_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_error_does_not_reference_eager_fallback_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_error_when_passing_mutating_primitive_op_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_exception_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_api_with_dynamic_shapes_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_as_backend_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_associative_scan_lifted_buffers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_associative_scan_symbol_dim_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_associative_scan_symbol_scandim_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_aten_to_unflatten_subclass_pre_dispatch_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_aten_to_unflatten_subclass_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_aten_to_unflatten_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_cond_preserve_torch_fn_for_subgraphs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_cond_symbool_pred_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_cond_warns_constant_pred_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_custom_decomp_table_basic_pop_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_custom_decomp_table_container_methods_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_custom_op_lib_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_custom_triton_kernel_mutable_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_custom_triton_kernel_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_decomp_torture_case_1_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_decomp_torture_case_2_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_decomps_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_decomps_simple_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_dynamo_config_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_for_training_run_decomp_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_for_training_with_container_type_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_for_training_with_dynamic_shapes_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_for_training_with_mutation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_for_training_with_state_dict_hooks_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_func_with_default_kwargs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_func_with_keyword_only_args_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_func_with_kwargs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_func_with_pytree_kwargs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_func_with_var_keyword_args_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_func_with_var_keyword_pytree_args_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_func_with_var_postional_args_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_function_schema_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_graph_with_no_inputs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_input_mutation_bug_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_input_mutation_dynamic_shape_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_input_mutation_static_shape_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_linear_preserve_dynamic_shape_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_max_nonstrict_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_max_onnx_reported_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_method_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_mod_constraints_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_module_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_preserve_linear_at_aot_level_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_preserve_linear_but_not_custom_op_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_scan_pytree_output_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_script_module_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_statically_known_true_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_then_compile_tensor_ctor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_with_autocast_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_with_fake_tensor_inputs_on_cuda_devices_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_with_fake_tensor_inputs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_with_inline_constraints_complex_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_with_inline_constraints_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_with_set_grad_enabled_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_export_with_wrong_inputs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_external_call_non_strict_real_tensor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_fake_inputs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_fake_weights_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_filter_traceback_frames_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_float_conversion_from_int_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_float_conversion_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_fqn_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_from_node_metadata_export_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_full_on_scalar_tensor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_hints_wrapper_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_hoo_inline_users_issue_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_if_functional_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_if_post_autograd_op_preserved_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_inline_script_class_method_recursive_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_inline_script_class_method_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_inline_script_function_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_inline_script_method_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_int_shape_specialization_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_intermediate_shape_comp_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_is_exporting_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_is_non_negative_check_function_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_is_nonzero_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_isnonzero_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_issue_113041_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_issue_157289_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_istft_op_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_keep_composite_ops_invalid_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_keep_composite_ops_linear_convd_for_training_ir_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_keep_composite_ops_linear_convd_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_kwarg_dynamic_shapes_diff_order_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_kwargs_reorder_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_layer_norm_unbacked_normalized_shape_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_layer_sharing_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_lazy_module_kwargs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_lifted_constants_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_linear_conv_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_malformed_fqn_from_source_name_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_map_buffers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_map_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_mask_nonzero_static_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_masked_select_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_math_pow_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_mismatched_dynamic_shapes_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_mixed_input_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_module_dict_key_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_module_input_subclasses_parameterization_nested_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_module_input_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_module_list_slice_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_module_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_module_with_dict_container_inp_out_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_modules_access_for_deleted_submodule_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_more_multidimensional_slicing_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_multidimensional_slicing_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_multinomial_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_multiple_definitions_same_name_dim_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nested_dynamic_shapes_spec_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nested_module_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nested_module_with_constant_buffer_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nested_module_with_init_buffer_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nested_module_with_parameter_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nn_module_stack_shared_submodule_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nn_module_stack_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_no_check_is_size_error_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_no_suggested_fixes_for_data_dependent_errors_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_no_tensor_computation_2_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_no_tensor_computation_3_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_no_tensor_computation_4_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_no_tensor_computation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_non_arg_name_dynamic_shapes_api_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_non_arg_name_dynamic_shapes_api_with_container_type_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_non_arg_name_dynamic_shapes_api_with_kwarg_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_non_persistent_buffer_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_non_strict_dynamic_shapes_suggested_fixes_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_non_strict_dynamic_shapes_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_none_buffers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nonstrict_retrace_preserves_metadata_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nonzero_2_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_nonzero_dynamic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_not_registered_parameter_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_operator_aten_tensor_mode_variant_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_output_node_name_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_pad_sequence_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_param_util_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_partial_patched_forward_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_placeholder_naming_collisions_hoo_subgraphs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_placeholder_naming_collisions_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_placeholder_naming_order_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_placeholder_naming_order_variadic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_placeholder_update_preserving_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_predispatch_cond_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_predispatch_grad_wrappers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_preserve_module_call_signature_unflatten_specialization_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_preserve_requires_grad_placeholders_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_preserve_shape_dynamism_for_unused_inputs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_profiling_code_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_python_asserts_with_sym_int_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_pytree_register_data_class_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_pytree_register_nested_data_class_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_raise_user_error_when_guard_on_data_dependent_operation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_range_constraints_with_replacement_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_real_tensor_alias_dtype_mismatch_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_real_tensor_bool_cast_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_real_tensor_errors_on_aliasing_custom_op_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_real_tensor_for_max_op_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_real_tensor_size_mismatch_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_redundant_assert_max_upper_bound_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_redundant_asserts_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_refine_dynamic_shapes_from_suggested_fixes_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_register_constant_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_repeat_interleave_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_replace_unbacked_with_very_large_upperbound_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_replaced_unbacked_bindings_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_reshape_view_helper_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_retracable_ep_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_retrace_pre_autograd_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_run_decomposition_supports_user_input_mutation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_run_decompositions_keep_metadata_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_run_decompositions_keep_tensor_constant_metadata_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_runtime_assert_for_prim_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_runtime_assert_for_prm_str_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_runtime_assert_with_size_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_sdpa_gqa_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_sequential_slicing_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_set_example_inputs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_set_grad_as_side_effect_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_set_grad_empty_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_set_grad_unflatten_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_setgrad_lifted_tensor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_shared_submodule_nn_module_stack_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_simple_export_for_training_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_simple_unbacked_view_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_size_input_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_slice_nn_module_stack_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_solver_unsupported_sympy_function_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_specialize_derived_dim_roots_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_split_const_gm_with_lifted_constants_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_stack_trace_make_fx_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_stack_trace_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_state_primitives_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_state_shape_attribute_assignment_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_state_tensors_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_static_dim_constraints_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_subclass_nested_attr_access_complicated_metadata_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_subclass_nested_attr_access_const_metadata_not_top_level_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_subclass_nested_attr_access_const_metadata_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_subclass_nested_attr_access_submodule_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_subclass_nested_attr_access_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_subclasses_parameterization_nested_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_subclasses_parameterization_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_suggest_torch_checks_with_non_negative_check_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_suggest_torch_checks_with_regular_check_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_suggested_fixes_for_data_dependent_errors_basic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_suggested_fixes_for_data_dependent_errors_puzzlers_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_suggested_fixes_new_roots_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_sym_float_operators_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_sym_or_sym_and_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_sym_sqrt_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symbool_item_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symfloat_item_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_input_additional_inputs_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_input_basic_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_input_ranges_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_input_shapes_collection_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_input_specialization_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_item_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_output_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_symint_tensor_return_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_tensor_attribute_zero_args_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_tensor_constant_aten_to_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_tensor_constant_with_wrapped_method_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_to_module_with_mutated_buffer_multiple_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_to_module_with_mutated_buffer_multiple_update_sub_later_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_to_module_with_mutated_buffer_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_tolist_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_torch_check_eq_commutativity_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_torch_fn_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_trace_under_fake_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_train_eval_on_exported_preautograd_module_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_3d_matmul_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_bincount_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_bindings_for_divisible_u_symint_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_deferred_runtime_retrace_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_expand_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_infer_size_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_kth_value_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_linear_layer_norm_input_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_noncontig_lin_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_pad_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_scalar_constructor_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_slice_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_to_cond_passthrough_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_to_cond_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unbacked_unsqueeze_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_asserts_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_buffer_update_child2parent_swap_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_closure_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_isinstance_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_multiple_graphs_dispatch_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_multiple_graphs_preserve_signature_no_error_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_multiple_graphs_shared_submodule_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_multiple_graphs_state_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_no_unroll_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_placeholder_update_child2parent_swap_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_placeholder_update_grandchild2cousin_swap_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_5_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_6_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_buf_8_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_const_preserving_3_1_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_const_preserving_3_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_4_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_6_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_9_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_preserving_10_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_1_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_preserving_5_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_mutating_buf_preserving_7_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unflatten_random_dag_preserving_4_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unused_aliases_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_unused_constant_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_use_embedding_twice_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_user_input_and_buffer_mutation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_vmap_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_while_loop_assert_separation_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_while_loop_index_assertions_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_while_loop_simple_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_while_loop_tensor_constant_idx_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportTestExport::test_wrapper_module_training_ir_to_decomp_strict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test__scaled_dot_product_flash_attention_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_additional_inputs_constants_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_allow_explicit_guards_as_runtime_asserts_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_args_type_checked_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_aten_lift_fresh_copy_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_attention_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_attr_assignment_extra_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_automatic_constrain_size_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_automatic_dynamic_shapes_constant_relation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_automatic_dynamic_shapes_linear_relation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_automatic_dynamic_shapes_simple_equality_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_baddbmm_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_basic_non_strict_fake_tensor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_basic_non_strict_real_tensor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_basic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_bincount_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_buffer_util_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_capture_subclass_constructor_torch_ir_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_capture_subclass_constructor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_capture_subclass_wrong_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_ccode_python_mod_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_check_specialized_int_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_checks_to_constrain_range_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cleanup_dynamic_markers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_colin_unbacked_backed_vr_sub_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_colon_parameter_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_compiling_state_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_access_identical_symint_closure_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_branches_return_constant_int_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_branches_return_same_int_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_buffers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_contains_unbacked_no_escape_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_int_closure_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_unflatten_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_with_module_stack_export_with_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cond_with_module_stack_export_with_unflatten_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_aliasing_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_input_naming_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_no_user_inp_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_output_dup_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_output_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_requires_grad_const_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_return_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_tensor_mutation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_tensor_with_non_functional_nested_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constant_tensor_with_non_functional_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constrain_decomp_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constrain_size_in_eager_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constrain_size_with_constrain_value_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_constrain_size_with_various_cases_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_conv_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_crop_like_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_cse_for_symint_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_custom_op_auto_functionalize_pre_dispatch_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_custom_op_auto_functionalize_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_custom_op_auto_warn_pre_dispatch_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_custom_op_preserve_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_custom_pytree_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_custom_tag_metadata_re_export_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_decomp_batch_norm_functional_predispatch_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_decomp_item_in_prim_after_decomposition_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_decomp_item_in_prim_before_decomposition_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_default_decomposition_core_cia_ops_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_1_2_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_basic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_integer_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_nested_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_out_of_order_repeat_derived_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_out_of_order_simplified_repeat_non_derived_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_out_of_order_simplified_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_out_of_order_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_derived_dim_repeat_derived_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_detect_leak_strict_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_device_to_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_device_to_gpu_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_device_to_mutation_float_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_device_to_mutation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_device_to_static_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dim_1_2_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dim_auto_and_dim_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dim_dynamic_divisibility_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dim_dynamic_specialization_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dim_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dim_hint_range_violations_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dim_hint_ranges_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_disable_forced_specializations_errors_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_disable_forced_specializations_ok_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_distributed_all_gather_into_tensor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_distributed_all_gather_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_distributed_all_reduce_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_distributed_all_to_all_single_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_distributed_reduce_scatter_tensor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dont_duck_size_for_auto_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_double_lifted_constants_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_draft_export_checks_aliasing_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_draft_export_checks_mutation_list_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_draft_export_checks_mutation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_draft_export_checks_mutation_with_nan_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_draft_export_fake_kernel_inference_errors_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_draft_export_infers_fake_kernel_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_duplicate_modules_with_non_persistent_buffers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_lr_shift_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_bounds_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_builder_basic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_builder_kwargs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_builder_pytree_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_dataclass_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_inferred_basic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_serdes_generic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_serdes_user_errors_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_serdes_various_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_shapes_spec_with_pytree_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_dynamic_sym_round_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_ends_of_bounds_oblivious_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_error_does_not_reference_eager_fallback_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_error_when_passing_mutating_primitive_op_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_exception_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_api_with_dynamic_shapes_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_as_backend_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_associative_scan_lifted_buffers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_associative_scan_symbol_dim_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_associative_scan_symbol_scandim_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_aten_to_unflatten_subclass_pre_dispatch_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_aten_to_unflatten_subclass_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_aten_to_unflatten_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_cond_preserve_torch_fn_for_subgraphs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_cond_symbool_pred_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_cond_warns_constant_pred_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_custom_decomp_table_basic_pop_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_custom_decomp_table_container_methods_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_custom_op_lib_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_custom_triton_kernel_mutable_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_custom_triton_kernel_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_decomp_torture_case_1_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_decomp_torture_case_2_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_decomps_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_decomps_simple_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_dynamo_config_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_for_training_run_decomp_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_for_training_with_container_type_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_for_training_with_dynamic_shapes_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_for_training_with_mutation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_for_training_with_state_dict_hooks_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_func_with_default_kwargs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_func_with_keyword_only_args_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_func_with_kwargs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_func_with_pytree_kwargs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_func_with_var_keyword_args_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_func_with_var_keyword_pytree_args_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_func_with_var_postional_args_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_function_schema_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_graph_with_no_inputs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_input_mutation_bug_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_input_mutation_dynamic_shape_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_input_mutation_static_shape_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_linear_preserve_dynamic_shape_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_max_nonstrict_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_max_onnx_reported_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_method_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_mod_constraints_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_module_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_preserve_linear_at_aot_level_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_preserve_linear_but_not_custom_op_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_scan_pytree_output_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_script_module_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_statically_known_true_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_then_compile_tensor_ctor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_with_autocast_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_with_fake_tensor_inputs_on_cuda_devices_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_with_fake_tensor_inputs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_with_inline_constraints_complex_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_with_inline_constraints_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_with_set_grad_enabled_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_export_with_wrong_inputs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_external_call_non_strict_real_tensor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_fake_inputs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_fake_weights_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_filter_traceback_frames_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_float_conversion_from_int_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_float_conversion_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_fqn_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_from_node_metadata_export_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_full_on_scalar_tensor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_hints_wrapper_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_hoo_inline_users_issue_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_if_functional_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_if_post_autograd_op_preserved_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_inline_script_class_method_recursive_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_inline_script_class_method_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_inline_script_function_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_inline_script_method_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_int_shape_specialization_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_intermediate_shape_comp_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_is_exporting_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_is_non_negative_check_function_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_is_nonzero_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_isnonzero_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_issue_113041_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_issue_157289_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_istft_op_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_keep_composite_ops_invalid_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_keep_composite_ops_linear_convd_for_training_ir_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_keep_composite_ops_linear_convd_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_kwarg_dynamic_shapes_diff_order_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_kwargs_reorder_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_layer_norm_unbacked_normalized_shape_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_layer_sharing_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_lazy_module_kwargs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_lifted_constants_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_linear_conv_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_malformed_fqn_from_source_name_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_map_buffers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_map_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_mask_nonzero_static_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_masked_select_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_math_pow_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_mismatched_dynamic_shapes_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_mixed_input_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_module_dict_key_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_module_input_subclasses_parameterization_nested_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_module_input_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_module_list_slice_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_module_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_module_with_dict_container_inp_out_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_modules_access_for_deleted_submodule_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_more_multidimensional_slicing_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_multidimensional_slicing_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_multinomial_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_multiple_definitions_same_name_dim_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nested_dynamic_shapes_spec_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nested_module_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nested_module_with_constant_buffer_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nested_module_with_init_buffer_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nested_module_with_parameter_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nn_module_stack_shared_submodule_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nn_module_stack_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_no_check_is_size_error_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_no_suggested_fixes_for_data_dependent_errors_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_no_tensor_computation_2_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_no_tensor_computation_3_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_no_tensor_computation_4_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_no_tensor_computation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_non_arg_name_dynamic_shapes_api_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_non_arg_name_dynamic_shapes_api_with_container_type_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_non_arg_name_dynamic_shapes_api_with_kwarg_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_non_persistent_buffer_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_non_strict_dynamic_shapes_suggested_fixes_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_non_strict_dynamic_shapes_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_none_buffers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nonstrict_retrace_preserves_metadata_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nonzero_2_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_nonzero_dynamic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_not_registered_parameter_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_operator_aten_tensor_mode_variant_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_output_node_name_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_pad_sequence_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_param_util_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_partial_patched_forward_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_placeholder_naming_collisions_hoo_subgraphs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_placeholder_naming_collisions_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_placeholder_naming_order_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_placeholder_naming_order_variadic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_placeholder_update_preserving_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_predispatch_cond_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_predispatch_grad_wrappers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_preserve_module_call_signature_unflatten_specialization_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_preserve_requires_grad_placeholders_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_preserve_shape_dynamism_for_unused_inputs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_profiling_code_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_python_asserts_with_sym_int_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_pytree_register_data_class_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_pytree_register_nested_data_class_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_raise_user_error_when_guard_on_data_dependent_operation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_range_constraints_with_replacement_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_real_tensor_alias_dtype_mismatch_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_real_tensor_bool_cast_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_real_tensor_errors_on_aliasing_custom_op_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_real_tensor_for_max_op_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_real_tensor_size_mismatch_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_redundant_assert_max_upper_bound_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_redundant_asserts_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_refine_dynamic_shapes_from_suggested_fixes_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_register_constant_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_repeat_interleave_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_replace_unbacked_with_very_large_upperbound_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_replaced_unbacked_bindings_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_reshape_view_helper_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_retracable_ep_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_retrace_pre_autograd_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_run_decomposition_supports_user_input_mutation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_run_decompositions_keep_metadata_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_run_decompositions_keep_tensor_constant_metadata_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_runtime_assert_for_prim_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_runtime_assert_for_prm_str_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_runtime_assert_with_size_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_sdpa_gqa_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_sequential_slicing_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_set_example_inputs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_set_grad_as_side_effect_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_set_grad_empty_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_set_grad_unflatten_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_setgrad_lifted_tensor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_shared_submodule_nn_module_stack_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_simple_export_for_training_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_simple_unbacked_view_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_size_input_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_slice_nn_module_stack_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_solver_unsupported_sympy_function_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_specialize_derived_dim_roots_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_split_const_gm_with_lifted_constants_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_stack_trace_make_fx_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_stack_trace_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_state_primitives_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_state_shape_attribute_assignment_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_state_tensors_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_static_dim_constraints_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_subclass_nested_attr_access_complicated_metadata_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_subclass_nested_attr_access_const_metadata_not_top_level_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_subclass_nested_attr_access_const_metadata_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_subclass_nested_attr_access_submodule_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_subclass_nested_attr_access_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_subclasses_parameterization_nested_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_subclasses_parameterization_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_suggest_torch_checks_with_non_negative_check_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_suggest_torch_checks_with_regular_check_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_suggested_fixes_for_data_dependent_errors_basic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_suggested_fixes_for_data_dependent_errors_puzzlers_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_suggested_fixes_new_roots_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_sym_float_operators_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_sym_or_sym_and_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_sym_sqrt_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symbool_item_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symfloat_item_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_input_additional_inputs_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_input_basic_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_input_ranges_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_input_shapes_collection_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_input_specialization_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_item_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_output_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_symint_tensor_return_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_tensor_attribute_zero_args_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_tensor_constant_aten_to_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_tensor_constant_with_wrapped_method_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_to_module_with_mutated_buffer_multiple_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_to_module_with_mutated_buffer_multiple_update_sub_later_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_to_module_with_mutated_buffer_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_tolist_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_torch_check_eq_commutativity_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_torch_fn_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_trace_under_fake_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_train_eval_on_exported_preautograd_module_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_3d_matmul_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_bincount_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_bindings_for_divisible_u_symint_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_deferred_runtime_retrace_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_expand_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_infer_size_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_kth_value_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_linear_layer_norm_input_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_noncontig_lin_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_pad_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_scalar_constructor_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_slice_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_to_cond_passthrough_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_to_cond_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unbacked_unsqueeze_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_asserts_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_buffer_update_child2parent_swap_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_closure_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_isinstance_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_multiple_graphs_dispatch_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_multiple_graphs_preserve_signature_no_error_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_multiple_graphs_shared_submodule_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_multiple_graphs_state_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_no_unroll_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_placeholder_update_child2parent_swap_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_placeholder_update_grandchild2cousin_swap_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_5_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_6_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_buf_8_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_const_preserving_3_1_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_const_preserving_3_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_4_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_6_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_9_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_preserving_10_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_1_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_preserving_5_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_mutating_buf_preserving_7_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unflatten_random_dag_preserving_4_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unused_aliases_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_unused_constant_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_use_embedding_twice_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_user_input_and_buffer_mutation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_vmap_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_while_loop_assert_separation_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_while_loop_index_assertions_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_while_loop_simple_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_while_loop_tensor_constant_idx_training_ir_to_decomp_nonstrict, test/export/test_export_training_ir_to_run_decomp.py::TrainingIRToRunDecompExportNonStrictTestExport::test_wrapper_module_training_ir_to_decomp_nonstrict 2025-08-26T20:41:15.2055579Z 2025-08-26T20:41:18.4475347Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:41:18.4476952Z import pkg_resources 2025-08-26T20:41:18.5729872Z Running inductor/test_cpu_select_algorithm 12/16 ... [2025-08-26 20:41:18.572648] 2025-08-26T20:41:18.5730761Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:41:18.5733604Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_cpu_select_algorithm.py', '-m', 'not serial', '--shard-id=12', '--num-shards=16', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:41:18.573011] 2025-08-26T20:45:57.4688702Z 2025-08-26T20:45:57.4690567Z inductor/test_cpu_select_algorithm 4/16 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_4.16_26c023cae47eaaaf_.log 2025-08-26T20:45:57.4901440Z Running 122 items in this shard: test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_aoti_linear_multi_view_operations_batch_size_16_in_features_128_out_features_64_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_amx_bs_2_Mdim_16_Kdim_32_Ndim_16_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_amx_bs_2_Mdim_32_Kdim_32_Ndim_32_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_bs_50_Mdim_192_Kdim_196_Ndim_84_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_freezing_bs_1_Mdim_192_Kdim_196_Ndim_64_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_pointwise_bs_5_Mdim_384_Kdim_96_Ndim_64_epilogue_mul_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_bfloat16_per_channel_quant_False_reshape_a_True_expand_a_scale_True_dynamic_False_M_1_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_bfloat16_per_channel_quant_True_reshape_a_False_expand_a_scale_True_dynamic_False_M_32_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_float32_per_channel_quant_False_reshape_a_False_expand_a_scale_True_dynamic_False_M_32_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_float32_per_channel_quant_True_reshape_a_False_expand_a_scale_False_dynamic_True_M_32_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_True_float32_per_channel_quant_True_reshape_a_False_expand_a_scale_True_dynamic_False_M_1_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_True_float32_per_channel_quant_True_reshape_a_True_expand_a_scale_True_dynamic_False_M_32_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_False_bias1_epilogue2_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_False_bias3_epilogue2_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_True_bias0_epilogue4_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_True_bias3_epilogue1_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int4_concat_woq_mm_batch_size_4_in_features_256_out_features1_group_size_128_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int4_woq_mm_amx_batch_size_1_in_features_1024_out_features_1024_group_size_128_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int4_woq_mm_amx_batch_size_1_in_features_128_out_features_1024_group_size_128_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int4_woq_mm_avx512_batch_size_1_in_features_256_out_features_128_group_size_64_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_17_mid_dim_1_in_features_1024_out_features_65_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_17_mid_dim_8_in_features_1024_out_features_65_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_1_mid_dim_8_in_features_1024_out_features_64_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_1_mid_dim_8_in_features_144_out_features_1024_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_32_mid_dim_1_in_features_144_out_features_65_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_32_mid_dim_8_in_features_144_out_features_1024_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_concat_batch_size_1_mid_dim_1_in_features_128_out_features_64_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_concat_batch_size_32_mid_dim_1_in_features_128_out_features_64_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_k_slicing_batch_size_2_in_features_1000_out_features_2_bias_False_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1000_in_features_1000_out_features_1024_bias_False_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1000_in_features_1_out_features_1_bias_False_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1000_in_features_1_out_features_1_bias_True_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1024_bias_False_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1024_bias_False_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1024_bias_True_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1_bias_False_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1_out_features_1024_bias_False_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1_out_features_1_bias_False_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1000_out_features_1_bias_True_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1000_out_features_1_bias_True_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_indirect_indexing_batch_size_2_in_features_16_seq_lens_128_out_features_32_bias_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_gelu_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_hardtanh_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_mul_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_add_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_div_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_hardtanh_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_add_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_hardsigmoid_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_div_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_hardswish_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_relu_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_silu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_128_bias_False_epilogue_sub_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_False_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_384_bias_False_unary_relu_binary_mul_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_mul_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_sub_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_385_bias_True_unary_relu_binary_div_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_385_bias_True_unary_relu_binary_div_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_local_and_global_accumulator_out_features1_16_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_local_and_global_accumulator_out_features1_48_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_3_in_features_128_out_features_64_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_49_in_features_4_out_features_64_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_False_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_epilogue_gelu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_False_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_False_int8_mixed_bf16_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_int8_mixed_bf16_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_False_int8_mixed_bf16_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_True_int8_mixed_bf16_True_epilogue_none_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_True_int8_mixed_bf16_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_False_int8_mixed_bf16_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_bmm_with_pointwise_dynamic_shapes_bs_5_Mdim_384_Kdim_96_Ndim_64_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_bmm_with_pointwise_with_reshape_dynamic_shapes_bs_5_Mdim_384_Kdim_96_Ndim_65_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_False_bias2_epilogue0_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_True_bias0_epilogue4_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_True_bias2_epilogue0_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_True_bias3_epilogue0_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_amx_dynamic_shapes_batch_size_1024_in_features_1024_out_features_1024_bias_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_cache_blocking_dynamic_shapes_batch_size_512_in_features_1024_out_features_1024_bias_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1_out_features_1024_bias_False_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1_out_features_1_bias_False_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1000_out_features_1024_bias_True_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1_bias_False_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_2_in_features_1000_out_features_1_bias_True_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_thread_factors_dynamic_shapes_batch_size_1024_in_features_1024_out_features_1024_bias_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_gelu_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_sigmoid_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_tanh_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_hardsigmoid_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_hardswish_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_leaky_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_div_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_sub_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_transpose_dynamic_shapes_batch_size_384_in_features_196_out_features_128_bias_False_epilogue_sub_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_transpose_dynamic_shapes_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_add_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_unary_relu_binary_mul_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_div_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_div_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_amx_dynamic_shapes_batch_size_16_in_features_68_out_features_64_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_amx_dynamic_shapes_batch_size_32_in_features_68_out_features_64_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_amx_dynamic_shapes_batch_size_49_in_features_128_out_features_64_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_binary_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_False_int8_mixed_bf16_False_epilogue_none_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_binary_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_True_int8_mixed_bf16_False_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_binary_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_True_int8_mixed_bf16_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_False_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_False_epilogue_gelu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_False_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_False_epilogue_gelu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_True_epilogue_none_cpu_float32 2025-08-26T20:45:57.5106479Z 2025-08-26T20:46:00.7411288Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:46:00.7414124Z import pkg_resources 2025-08-26T20:46:00.8875718Z Running inductor/test_scatter_optimization 1/1 ... [2025-08-26 20:46:00.887162] 2025-08-26T20:46:00.8876752Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:46:00.8879974Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_scatter_optimization.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:46:00.887563] 2025-08-26T20:46:07.8921607Z 2025-08-26T20:46:07.8923386Z inductor/test_scatter_optimization 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_scatter_optimization_1.1_b19ddf983997e840_.log 2025-08-26T20:46:07.8925072Z 2025-08-26T20:46:11.1771432Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:46:11.1774539Z import pkg_resources 2025-08-26T20:46:11.3010812Z Running dynamo/test_list 1/1 ... [2025-08-26 20:46:11.300664] 2025-08-26T20:46:11.3011717Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:46:11.3014251Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_list.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:46:11.301017] 2025-08-26T20:46:17.4750149Z 2025-08-26T20:46:17.4751535Z dynamo/test_list 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_list_1.1_43cef3e7f9a77987_.log 2025-08-26T20:46:17.4771454Z Running 39 items in this shard: test/dynamo/test_list.py::TupleTests::test___contains__, test/dynamo/test_list.py::TupleTests::test___getitem__, test/dynamo/test_list.py::TupleTests::test_binop_add, test/dynamo/test_list.py::TupleTests::test_binop_imul, test/dynamo/test_list.py::TupleTests::test_cmp_eq, test/dynamo/test_list.py::TupleTests::test_cmp_greater_than, test/dynamo/test_list.py::TupleTests::test_cmp_greater_than_or_equal, test/dynamo/test_list.py::TupleTests::test_cmp_less_than, test/dynamo/test_list.py::TupleTests::test_cmp_less_than_or_equal, test/dynamo/test_list.py::TupleTests::test_cmp_ne, test/dynamo/test_list.py::TupleTests::test_count, test/dynamo/test_list.py::TupleTests::test_index, test/dynamo/test_list.py::ListTests::test___contains__, test/dynamo/test_list.py::ListTests::test___delitem__, test/dynamo/test_list.py::ListTests::test___getitem__, test/dynamo/test_list.py::ListTests::test___setitem__, test/dynamo/test_list.py::ListTests::test_append, test/dynamo/test_list.py::ListTests::test_binop_add, test/dynamo/test_list.py::ListTests::test_binop_delitem_global_list, test/dynamo/test_list.py::ListTests::test_binop_iadd, test/dynamo/test_list.py::ListTests::test_binop_iadd_global_list, test/dynamo/test_list.py::ListTests::test_binop_imul, test/dynamo/test_list.py::ListTests::test_binop_imul_global_list, test/dynamo/test_list.py::ListTests::test_clear, test/dynamo/test_list.py::ListTests::test_cmp_eq, test/dynamo/test_list.py::ListTests::test_cmp_greater_than, test/dynamo/test_list.py::ListTests::test_cmp_greater_than_or_equal, test/dynamo/test_list.py::ListTests::test_cmp_less_than, test/dynamo/test_list.py::ListTests::test_cmp_less_than_or_equal, test/dynamo/test_list.py::ListTests::test_cmp_ne, test/dynamo/test_list.py::ListTests::test_copy, test/dynamo/test_list.py::ListTests::test_count, test/dynamo/test_list.py::ListTests::test_extend, test/dynamo/test_list.py::ListTests::test_index, test/dynamo/test_list.py::ListTests::test_insert, test/dynamo/test_list.py::ListTests::test_pop, test/dynamo/test_list.py::ListTests::test_remove, test/dynamo/test_list.py::ListTests::test_reverse, test/dynamo/test_list.py::ListTests::test_sort 2025-08-26T20:46:17.4790137Z 2025-08-26T20:46:21.0157574Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:46:21.0159530Z import pkg_resources 2025-08-26T20:46:21.1404613Z Running dynamo/test_sources 1/1 ... [2025-08-26 20:46:21.140178] 2025-08-26T20:46:21.1405065Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:46:21.1407542Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sources.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:46:21.140517] 2025-08-26T20:46:24.9103700Z 2025-08-26T20:46:24.9104729Z dynamo/test_sources 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sources_1.1_5d333f0984a1e25f_.log 2025-08-26T20:46:24.9106632Z Running 3 items in this shard: test/dynamo/test_sources.py::SourceTests::test_is_local, test/dynamo/test_sources.py::SourceTests::test_property_closure, test/dynamo/test_sources.py::SourceTests::test_supported_nodes 2025-08-26T20:46:24.9107613Z 2025-08-26T20:46:28.2341524Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:46:28.2344864Z import pkg_resources 2025-08-26T20:46:28.3580456Z Running dynamo/test_model_output 1/1 ... [2025-08-26 20:46:28.357659] 2025-08-26T20:46:28.3581249Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:46:28.3582953Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_model_output.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:46:28.358019] 2025-08-26T20:46:32.0276044Z 2025-08-26T20:46:32.0277308Z dynamo/test_model_output 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_model_output_1.1_d6c2fb7e27f58d54_.log 2025-08-26T20:46:32.0283689Z Running 18 items in this shard: test/dynamo/test_model_output.py::TestHFPretrained::test_pretrained, test/dynamo/test_model_output.py::TestHFPretrained::test_pretrained_non_const_attr, test/dynamo/test_model_output.py::TestModelOutput::test_mo_assign, test/dynamo/test_model_output.py::TestModelOutput::test_mo_create, test/dynamo/test_model_output.py::TestModelOutput::test_mo_from_outside, test/dynamo/test_model_output.py::TestModelOutput::test_mo_getattr, test/dynamo/test_model_output.py::TestModelOutput::test_mo_getattr_missing, test/dynamo/test_model_output.py::TestModelOutput::test_mo_getitem, test/dynamo/test_model_output.py::TestModelOutput::test_mo_index, test/dynamo/test_model_output.py::TestModelOutput::test_mo_init, test/dynamo/test_model_output.py::TestModelOutput::test_mo_init2, test/dynamo/test_model_output.py::TestModelOutput::test_mo_init_with_disable, test/dynamo/test_model_output.py::TestModelOutput::test_mo_newkey, test/dynamo/test_model_output.py::TestModelOutput::test_mo_reconstruct_bytecode, test/dynamo/test_model_output.py::TestModelOutput::test_mo_tuple, test/dynamo/test_model_output.py::TestModelOutput::test_none, test/dynamo/test_model_output.py::TestModelOutput::test_reconstruction, test/dynamo/test_model_output.py::TestModelOutputBertCPU::test_HF_bert_model_output_cpu 2025-08-26T20:46:32.0289619Z 2025-08-26T20:46:35.1668366Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:46:35.1669972Z import pkg_resources 2025-08-26T20:46:35.2907618Z Running dynamo/test_profiler 1/1 ... [2025-08-26 20:46:35.290446] 2025-08-26T20:46:35.2908094Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:46:35.2910680Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_profiler.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:46:35.290820] 2025-08-26T20:46:50.6787791Z 2025-08-26T20:46:50.6789229Z dynamo/test_profiler 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_profiler_1.1_bda3d15bf2d21084_.log 2025-08-26T20:46:50.6799030Z Running 11 items in this shard: test/dynamo/test_profiler.py::DynamoProfilerTests::test_dynamo_timed_profiling_backend_compile, test/dynamo/test_profiler.py::DynamoProfilerTests::test_dynamo_timed_profiling_isolated, test/dynamo/test_profiler.py::DynamoProfilerTests::test_execution_trace_dynamic_shapes, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profile_dynamic_shapes_compilation, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profile_dynamic_shapes_list_compilation, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profile_dynamic_shapes_runtime, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_cache_lookup, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_cache_lookup_profiler_step, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_dynamo_compiled_region, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_enabled, test/dynamo/test_profiler.py::DynamoProfilerTests::test_profiler_record_function_ignore 2025-08-26T20:46:50.6807153Z 2025-08-26T20:46:54.0986325Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:46:54.0988147Z import pkg_resources 2025-08-26T20:46:54.2228073Z Running export/test_export_opinfo 1/1 ... [2025-08-26 20:46:54.222478] 2025-08-26T20:46:54.2228582Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:46:54.2230840Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export_opinfo.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:46:54.222838] 2025-08-26T20:48:24.9770072Z 2025-08-26T20:48:24.9771990Z export/test_export_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_opinfo_1.1_8a335e9dcb605d8c_.log 2025-08-26T20:48:25.0071608Z Running 672 items in this shard: test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_H_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_T_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___getitem___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___radd___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___rdiv___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___rmatmul___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___rmod___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___rmul___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___rpow___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export___rsub___cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__batch_norm_with_update_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__chunk_cat_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__native_batch_norm_legit_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__segment_reduce_lengths_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__segment_reduce_offsets_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__softmax_backward_data_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__unsafe_masked_index_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__unsafe_masked_index_put_accumulate_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export__upsample_bilinear2d_aa_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_abs_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_acos_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_acosh_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_add_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_addbmm_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_addcdiv_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_addcmul_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_addmm_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_addmm_decomposed_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_addmv_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_addr_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_alias_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_all_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_allclose_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_amax_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_amin_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_aminmax_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_angle_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_any_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_arange_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_argmax_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_argmin_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_argsort_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_argwhere_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_as_strided_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_as_strided_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_as_strided_partial_views_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_as_strided_scatter_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_asin_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_asinh_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_atan2_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_atan_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_atanh_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_atleast_1d_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_atleast_2d_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_atleast_3d_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_baddbmm_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_bernoulli_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_bfloat16_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_block_diag_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_bmm_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_bool_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_broadcast_shapes_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_broadcast_tensors_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_broadcast_to_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_bucketize_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_byte_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cartesian_prod_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cat_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cauchy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cdist_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cdouble_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_ceil_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cfloat_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_chalf_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_char_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cholesky_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cholesky_inverse_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_cholesky_solve_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_chunk_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_clamp_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_clamp_max_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_clamp_min_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_clone_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_column_stack_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_combinations_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_complex_cpu_float32, 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test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_softshrink_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_softsign_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_tanhshrink_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_threshold_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_triplet_margin_loss_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_unfold_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_upsample_bilinear_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nn_functional_upsample_nearest_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nonzero_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_nonzero_static_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_norm_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_norm_fro_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_norm_inf_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_norm_nuc_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_normal_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_normal_in_place_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_normal_number_mean_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_ones_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_ones_like_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_ormqr_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_outer_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_pca_lowrank_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_permute_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_permute_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_pinverse_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_polar_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_polygamma_polygamma_n_0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_polygamma_polygamma_n_1_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_polygamma_polygamma_n_2_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_polygamma_polygamma_n_3_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_polygamma_polygamma_n_4_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_positive_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_pow_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_prod_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_put_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_qr_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_quantile_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_rad2deg_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_rand_like_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_randint_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_randint_like_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_randn_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_randn_like_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_ravel_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_real_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_reciprocal_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_remainder_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_renorm_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_repeat_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_repeat_interleave_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_reshape_as_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_reshape_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_resize__cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_resize_as__cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_resolve_conj_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_resolve_neg_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_roll_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_rot90_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_round_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_round_decimals_0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_round_decimals_3_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_round_decimals_neg_3_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_rsqrt_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_rsub_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scalar_tensor_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scatter_add_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scatter_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scatter_reduce_amax_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scatter_reduce_amin_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scatter_reduce_mean_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scatter_reduce_prod_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_scatter_reduce_sum_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_searchsorted_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_select_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_select_scatter_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sgn_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_short_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sigmoid_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sign_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_bartlett_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_blackman_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_cosine_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_exponential_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_gaussian_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_general_cosine_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_general_hamming_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_hamming_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_hann_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_kaiser_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signal_windows_nuttall_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_signbit_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sin_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sinc_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sinh_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_slice_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_slice_scatter_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_softmax_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_softmax_with_dtype_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sort_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sparse_mm_reduce_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sparse_sampled_addmm_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_airy_ai_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_bessel_j0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_bessel_j1_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_bessel_y0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_bessel_y1_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_chebyshev_polynomial_t_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_chebyshev_polynomial_u_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_chebyshev_polynomial_v_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_chebyshev_polynomial_w_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_entr_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_erfcx_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_hermite_polynomial_h_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_hermite_polynomial_he_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_i0e_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_i1_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_i1e_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_laguerre_polynomial_l_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_legendre_polynomial_p_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_log_ndtr_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_modified_bessel_i0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_modified_bessel_i1_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_modified_bessel_k0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_modified_bessel_k1_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_ndtr_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_ndtri_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_polygamma_special_polygamma_n_0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_scaled_modified_bessel_k0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_scaled_modified_bessel_k1_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_shifted_chebyshev_polynomial_t_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_shifted_chebyshev_polynomial_u_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_shifted_chebyshev_polynomial_v_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_shifted_chebyshev_polynomial_w_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_spherical_bessel_j0_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_xlog1py_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_special_zeta_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_split_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_split_list_args_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_split_with_sizes_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_split_with_sizes_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sqrt_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_square_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_squeeze_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_squeeze_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_squeeze_multiple_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_stack_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_std_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_std_mean_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_std_mean_unbiased_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_std_unbiased_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_stft_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sub_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sum_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_sum_to_size_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_svd_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_svd_lowrank_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_t_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_t_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_take_along_dim_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_take_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_tan_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_tanh_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_tensor_split_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_tensordot_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_tile_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_to_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_to_sparse_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_topk_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_torch_ops_aten__safe_softmax_default_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_trace_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_transpose_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_transpose_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_trapezoid_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_trapz_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_triangular_solve_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_tril_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_triu_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_true_divide_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_trunc_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unbind_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unbind_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unflatten_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unfold_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unfold_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_uniform_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unique_consecutive_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unique_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unsafe_chunk_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unsafe_split_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unsqueeze_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_unsqueeze_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_var_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_var_mean_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_var_mean_unbiased_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_var_unbiased_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_vdot_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_view_as_complex_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_view_as_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_view_copy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_view_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_vsplit_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_vstack_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_where_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_xlogy_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_zero__cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_zeros_cpu_float32, test/export/test_export_opinfo.py::TestExportOpInfoCPU::test_fake_export_zeros_like_cpu_float32 2025-08-26T20:48:25.0364140Z 2025-08-26T20:48:28.2360313Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:48:28.2361914Z import pkg_resources 2025-08-26T20:48:28.3600826Z Running nn/test_multihead_attention 1/1 ... [2025-08-26 20:48:28.359732] 2025-08-26T20:48:28.3602506Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:48:28.3604721Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_multihead_attention.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:48:28.360094] 2025-08-26T20:48:37.7381650Z 2025-08-26T20:48:37.7383479Z nn/test_multihead_attention 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_multihead_attention_1.1_126f0eccfc91628f_.log 2025-08-26T20:48:37.7394705Z Running 19 items in this shard: test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attention_average_attn_weights_False, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attention_average_attn_weights_True, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_3d_attn_mask, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_fast_path_invalid_shape, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_invalid_shape, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_nested_tensor_outside_fast_path, test/nn/test_multihead_attention.py::TestMultiheadAttentionNN::test_multihead_attn_no_bias, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float16, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float32, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_batch_first_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float16, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float32, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attention_dtype_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_fast_path_query_and_bias_have_different_dtypes_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_fast_path_small_test_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_in_proj_bias_none_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_attn_in_proj_weight_none_cpu_float64, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_self_attn_two_masks_fast_path_cpu, test/nn/test_multihead_attention.py::TestMultiheadAttentionNNDeviceTypeCPU::test_multihead_self_attn_two_masks_fast_path_mock_cpu 2025-08-26T20:48:37.7405467Z 2025-08-26T20:48:41.0581661Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:48:41.0584816Z import pkg_resources 2025-08-26T20:48:41.1806747Z Running inductor/test_auto_functionalize 1/1 ... [2025-08-26 20:48:41.180323] 2025-08-26T20:48:41.1808246Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:48:41.1809564Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_auto_functionalize.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:48:41.180675] 2025-08-26T20:49:16.7543462Z 2025-08-26T20:49:16.7545061Z inductor/test_cpu_select_algorithm 8/16 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_8.16_2b926f44f3c8741c_.log 2025-08-26T20:49:16.7635438Z Running 111 items in this shard: test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_aoti_linear_batch_size_16_in_features_128_out_features_64_bias_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_2d_permute_Ndim_64_order4_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_amx_bs_2_Mdim_16_Kdim_32_Ndim_128_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_bs_50_Mdim_192_Kdim_196_Ndim_84_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_pointwise_bs_5_Mdim_384_Kdim_96_Ndim_64_epilogue_add_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_pointwise_bs_5_Mdim_384_Kdim_96_Ndim_64_epilogue_div_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_pointwise_bs_5_Mdim_384_Kdim_96_Ndim_65_epilogue_mul_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_pointwise_bs_5_Mdim_384_Kdim_96_Ndim_65_epilogue_sub_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_y_storage_offset_bs_1_Mdim_192_Kdim_196_Ndim_84_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_cpp_weight_prune_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_bfloat16_per_channel_quant_False_reshape_a_False_expand_a_scale_False_dynamic_True_M_1_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_bfloat16_per_channel_quant_False_reshape_a_False_expand_a_scale_True_dynamic_False_M_1_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_bfloat16_per_channel_quant_True_reshape_a_True_expand_a_scale_True_dynamic_True_M_32_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_float32_per_channel_quant_False_reshape_a_True_expand_a_scale_True_dynamic_False_M_1_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_float32_per_channel_quant_True_reshape_a_False_expand_a_scale_True_dynamic_True_M_1_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_True_float32_per_channel_quant_True_reshape_a_False_expand_a_scale_False_dynamic_True_M_32_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_True_float32_per_channel_quant_True_reshape_a_False_expand_a_scale_True_dynamic_True_M_1_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_True_float32_per_channel_quant_True_reshape_a_True_expand_a_scale_False_dynamic_False_M_1_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_batch_size_16_in_features_52_out_features_32_input_3d_False_gemm_num_2_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_False_bias0_epilogue0_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_False_bias3_epilogue3_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_True_bias0_epilogue2_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_True_bias3_epilogue2_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_1_mid_dim_1_in_features_128_out_features_65_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_1_mid_dim_8_in_features_128_out_features_64_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_1_mid_dim_8_in_features_128_out_features_65_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_k_slicing_batch_size_2_in_features_1000_out_features_2_bias_False_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1024_bias_False_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1_bias_False_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1_bias_True_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1_out_features_1_bias_False_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1_out_features_1_bias_True_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1000_out_features_1024_bias_False_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1_out_features_1024_bias_False_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1_out_features_1024_bias_False_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1_out_features_1_bias_False_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_add_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_hardswish_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_hardtanh_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_sigmoid_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_gelu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_leaky_relu_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_leaky_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_silu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_tanh_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_128_bias_False_epilogue_mul_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_128_bias_True_epilogue_add_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_128_bias_True_epilogue_none_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_128_bias_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_False_epilogue_mul_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_False_epilogue_sub_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_mul_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_none_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_sub_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_sub_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_sub_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_385_bias_False_unary_relu_binary_add_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_385_bias_False_unary_relu_binary_div_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_16_in_features_128_out_features_65_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_16_in_features_4_out_features_65_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_16_in_features_4_out_features_65_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_49_in_features_68_out_features_65_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_False_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_False_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_False_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_True_epilogue_none_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_False_int8_mixed_bf16_False_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_False_int8_mixed_bf16_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_False_int8_mixed_bf16_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_False_int8_mixed_bf16_True_epilogue_none_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_False_bias0_epilogue1_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_False_bias1_epilogue2_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1000_out_features_1024_bias_True_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1000_out_features_1_bias_True_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1000_out_features_1_bias_True_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1_out_features_1024_bias_True_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1_out_features_1024_bias_True_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1000_out_features_1024_bias_False_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1024_bias_False_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1024_bias_True_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_2_in_features_1000_out_features_1024_bias_False_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_2_in_features_1000_out_features_1024_bias_True_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_2_in_features_1000_out_features_1_bias_True_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_k_slicing_dynamic_shapes_batch_size_2_in_features_1000_out_features_2_bias_False_epilogue_none_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_div_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_hardsigmoid_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_div_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_hardtanh_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_silu_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_hardsigmoid_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_hardswish_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_hardtanh_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_mul_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_transpose_dynamic_shapes_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_none_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_transpose_dynamic_shapes_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_sub_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_unary_relu_binary_sub_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_div_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_mul_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_sub_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_unary_relu_binary_add_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_unary_relu_binary_add_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_unary_relu_binary_mul_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_amx_dynamic_shapes_batch_size_16_in_features_68_out_features_64_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_amx_dynamic_shapes_batch_size_32_in_features_4_out_features_65_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_amx_dynamic_shapes_batch_size_3_in_features_4_out_features_65_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_amx_dynamic_shapes_batch_size_49_in_features_68_out_features_65_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_binary_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_int8_mixed_bf16_False_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_binary_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_True_int8_mixed_bf16_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_False_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_False_epilogue_relu_cpu_float32 2025-08-26T20:49:16.7724182Z 2025-08-26T20:49:18.7556615Z 2025-08-26T20:49:18.7557694Z inductor/test_auto_functionalize 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_auto_functionalize_1.1_3a87b631fd9e08b6_.log 2025-08-26T20:49:18.7575374Z Running 39 items in this shard: test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias2_dynamic, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias_id_input_to_custom_op, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_alias_id_output, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_can_with_default, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_can_with_none_return, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra1, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra3, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra4, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_extra5, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_old, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_on_view, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_optional_old, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_optional_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_self_as_mutate_arg, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_tensorlist, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_with_returns_old, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_auto_functionalize_with_returns_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_can_auto_functionalize, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_dynamic2_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_dynamic3_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_dynamic_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_graph_input_is_view, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode1_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode2_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode3_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode4_v2, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_inference_mode_view, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_recompile, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_scheduling_with_multiple_mutates, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_slice, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_slice_dynamic, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_split, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_split_dynamic, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_try_use_slice, test/inductor/test_auto_functionalize.py::AutoFunctionalizeTests::test_unbacked_auto_functionalize_op 2025-08-26T20:49:18.7592279Z 2025-08-26T20:49:19.9406725Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:49:19.9408356Z import pkg_resources 2025-08-26T20:49:20.0637840Z Running dynamo/test_base_hop 1/1 ... [2025-08-26 20:49:20.063458] 2025-08-26T20:49:20.0638513Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:49:20.0640885Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_base_hop.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:49:20.063833] 2025-08-26T20:49:21.9369835Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:49:21.9371593Z import pkg_resources 2025-08-26T20:49:22.0599839Z Running export/test_upgrader 1/1 ... [2025-08-26 20:49:22.059684] 2025-08-26T20:49:22.0600310Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:49:22.0602868Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_upgrader.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:49:22.060016] 2025-08-26T20:49:25.4790619Z 2025-08-26T20:49:25.4791631Z export/test_upgrader 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_upgrader_1.1_d8ce2ceaa26e08b0_.log 2025-08-26T20:49:25.4794710Z Running 6 items in this shard: test/export/test_upgrader.py::TestUpgrader::test_field_renaming_chain_from_v0_complete, test/export/test_upgrader.py::TestUpgrader::test_field_renaming_chain_from_v0_missing_field, test/export/test_upgrader.py::TestUpgrader::test_field_renaming_from_v1_partial_chain, test/export/test_upgrader.py::TestUpgrader::test_nn_module_stack_error_handling_invalid_type, test/export/test_upgrader.py::TestUpgrader::test_nn_module_stack_transformation_from_v0, test/export/test_upgrader.py::TestUpgrader::test_nodes_without_metadata_handled_gracefully 2025-08-26T20:49:25.4797170Z 2025-08-26T20:49:25.6435553Z 2025-08-26T20:49:25.6436466Z dynamo/test_base_hop 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_base_hop_1.1_254bd9e29658cb38_.log 2025-08-26T20:49:25.6440556Z Running 11 items in this shard: test/dynamo/test_base_hop.py::BaseHOPTest::test_aliasing_mutation_error, test/dynamo/test_base_hop.py::BaseHOPTest::test_aot_eager, test/dynamo/test_base_hop.py::BaseHOPTest::test_auto_functionalize, test/dynamo/test_base_hop.py::BaseHOPTest::test_dynamo, test/dynamo/test_base_hop.py::BaseHOPTest::test_eager_call, test/dynamo/test_base_hop.py::BaseHOPTest::test_int_input, test/dynamo/test_base_hop.py::BaseHOPTest::test_none_input, test/dynamo/test_base_hop.py::BaseHOPTest::test_schema_gen_pytree_in_out, test/dynamo/test_base_hop.py::BaseHOPTest::test_schema_gen_pytree_in_out_with_mutation, test/dynamo/test_base_hop.py::BaseHOPTest::test_schema_gen_single_return, test/dynamo/test_base_hop.py::BaseHOPTest::test_schema_gen_single_return_with_mutation 2025-08-26T20:49:25.6444129Z 2025-08-26T20:49:28.9509662Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:49:28.9511260Z import pkg_resources 2025-08-26T20:49:28.9789500Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:49:28.9791039Z import pkg_resources 2025-08-26T20:49:29.0746045Z Running export/test_export 1/1 ... [2025-08-26 20:49:29.074352] 2025-08-26T20:49:29.0746718Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:49:29.0749380Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_export.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:49:29.074695] 2025-08-26T20:49:29.1014565Z Running inductor/test_binary_folding 1/1 ... [2025-08-26 20:49:29.101188] 2025-08-26T20:49:29.1015064Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:49:29.1017849Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_binary_folding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:49:29.101533] 2025-08-26T20:50:39.9796124Z 2025-08-26T20:50:39.9798826Z inductor/test_binary_folding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_binary_folding_1.1_ec3d76b6e67ede55_.log 2025-08-26T20:50:39.9800737Z Running 3 items in this shard: test/inductor/test_binary_folding.py::FreezingCpuTests::test_conv_binary_folding_cpu, test/inductor/test_binary_folding.py::FreezingCpuTests::test_conv_bn_folding_cpu, test/inductor/test_binary_folding.py::FreezingCpuTests::test_linear_binary_folding_cpu 2025-08-26T20:50:39.9802271Z 2025-08-26T20:50:43.4272103Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:50:43.4273924Z import pkg_resources 2025-08-26T20:50:43.5493868Z Running dynamo/test_backward_higher_order_ops 1/1 ... [2025-08-26 20:50:43.549051] 2025-08-26T20:50:43.5494427Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:50:43.5496711Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_backward_higher_order_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:50:43.549413] 2025-08-26T20:50:46.8051725Z 2025-08-26T20:50:46.8053143Z export/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_export_1.1_6d7575cb1b8e73b6_.log 2025-08-26T20:50:46.8254702Z Running 438 items in this shard: test/export/test_export.py::TestDynamismExpression::test_export_assume_static_by_default, test/export/test_export.py::TestDynamismExpression::test_export_constraints_error, test/export/test_export.py::TestDynamismExpression::test_export_constraints_error_not_in_range, test/export/test_export.py::TestDynamismExpression::test_export_inline_constraints, test/export/test_export.py::TestDynamismExpression::test_export_slice_maxsize, test/export/test_export.py::TestDynamismExpression::test_export_slice_unbacked_dim1, test/export/test_export.py::TestDynamismExpression::test_export_strict_narrow_unbacked_expr, test/export/test_export.py::TestDynamismExpression::test_no_grad_param_inplace, test/export/test_export.py::TestDynamismExpression::test_reshape_view_backed_size_oblivious, test/export/test_export.py::TestExport::test__scaled_dot_product_flash_attention, test/export/test_export.py::TestExport::test_additional_inputs_constants, test/export/test_export.py::TestExport::test_allow_explicit_guards_as_runtime_asserts, test/export/test_export.py::TestExport::test_args_type_checked, test/export/test_export.py::TestExport::test_aten_lift_fresh_copy, test/export/test_export.py::TestExport::test_attention, test/export/test_export.py::TestExport::test_attr_assignment_extra, test/export/test_export.py::TestExport::test_automatic_constrain_size, test/export/test_export.py::TestExport::test_automatic_dynamic_shapes_constant_relation, test/export/test_export.py::TestExport::test_automatic_dynamic_shapes_linear_relation, test/export/test_export.py::TestExport::test_automatic_dynamic_shapes_simple_equality, test/export/test_export.py::TestExport::test_baddbmm, test/export/test_export.py::TestExport::test_basic, test/export/test_export.py::TestExport::test_basic_non_strict_fake_tensor, test/export/test_export.py::TestExport::test_basic_non_strict_real_tensor, test/export/test_export.py::TestExport::test_bincount, test/export/test_export.py::TestExport::test_buffer_util, test/export/test_export.py::TestExport::test_capture_subclass_constructor, test/export/test_export.py::TestExport::test_capture_subclass_constructor_torch_ir, test/export/test_export.py::TestExport::test_capture_subclass_wrong, test/export/test_export.py::TestExport::test_ccode_python_mod, test/export/test_export.py::TestExport::test_check_specialized_int, test/export/test_export.py::TestExport::test_checks_to_constrain_range, test/export/test_export.py::TestExport::test_cleanup_dynamic_markers, test/export/test_export.py::TestExport::test_colin_unbacked_backed_vr_sub, test/export/test_export.py::TestExport::test_colon_parameter, test/export/test_export.py::TestExport::test_compiling_state, test/export/test_export.py::TestExport::test_cond_access_identical_symint_closure, test/export/test_export.py::TestExport::test_cond_branches_return_constant_int, test/export/test_export.py::TestExport::test_cond_branches_return_same_int, test/export/test_export.py::TestExport::test_cond_buffers, test/export/test_export.py::TestExport::test_cond_contains_unbacked_no_escape, test/export/test_export.py::TestExport::test_cond_int_closure, test/export/test_export.py::TestExport::test_cond_unflatten, test/export/test_export.py::TestExport::test_cond_with_module_stack_export_with, test/export/test_export.py::TestExport::test_cond_with_module_stack_export_with_unflatten, test/export/test_export.py::TestExport::test_constant_aliasing, test/export/test_export.py::TestExport::test_constant_input_naming, test/export/test_export.py::TestExport::test_constant_no_user_inp, test/export/test_export.py::TestExport::test_constant_output, test/export/test_export.py::TestExport::test_constant_output_dup, test/export/test_export.py::TestExport::test_constant_requires_grad_const, test/export/test_export.py::TestExport::test_constant_return, test/export/test_export.py::TestExport::test_constant_tensor_mutation, test/export/test_export.py::TestExport::test_constant_tensor_with_non_functional, test/export/test_export.py::TestExport::test_constant_tensor_with_non_functional_nested, test/export/test_export.py::TestExport::test_constrain_decomp, test/export/test_export.py::TestExport::test_constrain_size_in_eager, test/export/test_export.py::TestExport::test_constrain_size_with_constrain_value, test/export/test_export.py::TestExport::test_constrain_size_with_various_cases, test/export/test_export.py::TestExport::test_conv_dynamic, test/export/test_export.py::TestExport::test_crop_like, test/export/test_export.py::TestExport::test_cse_for_symint, test/export/test_export.py::TestExport::test_custom_op_auto_functionalize, test/export/test_export.py::TestExport::test_custom_op_auto_functionalize_pre_dispatch, test/export/test_export.py::TestExport::test_custom_op_auto_warn_pre_dispatch, test/export/test_export.py::TestExport::test_custom_op_preserve, test/export/test_export.py::TestExport::test_custom_pytree, test/export/test_export.py::TestExport::test_custom_tag_metadata_re_export, test/export/test_export.py::TestExport::test_decomp_batch_norm_functional_predispatch, test/export/test_export.py::TestExport::test_decomp_item_in_prim_after_decomposition, test/export/test_export.py::TestExport::test_decomp_item_in_prim_before_decomposition, test/export/test_export.py::TestExport::test_default_decomposition_core_cia_ops, test/export/test_export.py::TestExport::test_derived_dim_1_2, test/export/test_export.py::TestExport::test_derived_dim_basic, test/export/test_export.py::TestExport::test_derived_dim_integer, test/export/test_export.py::TestExport::test_derived_dim_nested, test/export/test_export.py::TestExport::test_derived_dim_out_of_order, test/export/test_export.py::TestExport::test_derived_dim_out_of_order_repeat_derived, test/export/test_export.py::TestExport::test_derived_dim_out_of_order_simplified, test/export/test_export.py::TestExport::test_derived_dim_out_of_order_simplified_repeat_non_derived, test/export/test_export.py::TestExport::test_derived_dim_repeat_derived, test/export/test_export.py::TestExport::test_detect_leak_strict, test/export/test_export.py::TestExport::test_device_to_dynamic, test/export/test_export.py::TestExport::test_device_to_gpu, test/export/test_export.py::TestExport::test_device_to_mutation, test/export/test_export.py::TestExport::test_device_to_mutation_float, test/export/test_export.py::TestExport::test_device_to_static, test/export/test_export.py::TestExport::test_dim_1_2, test/export/test_export.py::TestExport::test_dim_auto_and_dim, test/export/test_export.py::TestExport::test_dim_dynamic, test/export/test_export.py::TestExport::test_dim_dynamic_divisibility, test/export/test_export.py::TestExport::test_dim_dynamic_specialization, test/export/test_export.py::TestExport::test_dim_hint_range_violations, test/export/test_export.py::TestExport::test_dim_hint_ranges, test/export/test_export.py::TestExport::test_disable_forced_specializations_errors, test/export/test_export.py::TestExport::test_disable_forced_specializations_ok, test/export/test_export.py::TestExport::test_distributed_all_gather, test/export/test_export.py::TestExport::test_distributed_all_gather_into_tensor, test/export/test_export.py::TestExport::test_distributed_all_reduce, test/export/test_export.py::TestExport::test_distributed_all_to_all_single, test/export/test_export.py::TestExport::test_distributed_reduce_scatter_tensor, test/export/test_export.py::TestExport::test_dont_duck_size_for_auto_dynamic, test/export/test_export.py::TestExport::test_double_lifted_constants, test/export/test_export.py::TestExport::test_draft_export_checks_aliasing, test/export/test_export.py::TestExport::test_draft_export_checks_mutation, test/export/test_export.py::TestExport::test_draft_export_checks_mutation_list, test/export/test_export.py::TestExport::test_draft_export_checks_mutation_with_nan, test/export/test_export.py::TestExport::test_draft_export_fake_kernel_inference_errors, test/export/test_export.py::TestExport::test_draft_export_infers_fake_kernel, test/export/test_export.py::TestExport::test_duplicate_modules_with_non_persistent_buffers, test/export/test_export.py::TestExport::test_dynamic_lr_shift, test/export/test_export.py::TestExport::test_dynamic_shapes_bounds, test/export/test_export.py::TestExport::test_dynamic_shapes_builder_basic, test/export/test_export.py::TestExport::test_dynamic_shapes_builder_kwargs, test/export/test_export.py::TestExport::test_dynamic_shapes_builder_pytree, test/export/test_export.py::TestExport::test_dynamic_shapes_dataclass, test/export/test_export.py::TestExport::test_dynamic_shapes_inferred_basic, test/export/test_export.py::TestExport::test_dynamic_shapes_serdes_generic, test/export/test_export.py::TestExport::test_dynamic_shapes_serdes_user_errors, test/export/test_export.py::TestExport::test_dynamic_shapes_serdes_various, test/export/test_export.py::TestExport::test_dynamic_shapes_spec_with_pytree, test/export/test_export.py::TestExport::test_dynamic_sym_round, test/export/test_export.py::TestExport::test_ends_of_bounds_oblivious, test/export/test_export.py::TestExport::test_error_does_not_reference_eager_fallback, test/export/test_export.py::TestExport::test_error_when_passing_mutating_primitive_op, test/export/test_export.py::TestExport::test_exception, test/export/test_export.py::TestExport::test_export_api_with_dynamic_shapes, test/export/test_export.py::TestExport::test_export_as_backend, test/export/test_export.py::TestExport::test_export_associative_scan_lifted_buffers, test/export/test_export.py::TestExport::test_export_associative_scan_symbol_dim, test/export/test_export.py::TestExport::test_export_associative_scan_symbol_scandim, test/export/test_export.py::TestExport::test_export_aten_to_unflatten, test/export/test_export.py::TestExport::test_export_aten_to_unflatten_subclass, test/export/test_export.py::TestExport::test_export_aten_to_unflatten_subclass_pre_dispatch, test/export/test_export.py::TestExport::test_export_cond_preserve_torch_fn_for_subgraphs, test/export/test_export.py::TestExport::test_export_cond_symbool_pred, test/export/test_export.py::TestExport::test_export_cond_warns_constant_pred, test/export/test_export.py::TestExport::test_export_custom_decomp_table_basic_pop, test/export/test_export.py::TestExport::test_export_custom_decomp_table_container_methods, test/export/test_export.py::TestExport::test_export_custom_op_lib, test/export/test_export.py::TestExport::test_export_custom_triton_kernel, test/export/test_export.py::TestExport::test_export_custom_triton_kernel_mutable, test/export/test_export.py::TestExport::test_export_decomp_torture_case_1, test/export/test_export.py::TestExport::test_export_decomp_torture_case_2, test/export/test_export.py::TestExport::test_export_decomps_dynamic, test/export/test_export.py::TestExport::test_export_decomps_simple, test/export/test_export.py::TestExport::test_export_dynamo_config, test/export/test_export.py::TestExport::test_export_for_training_run_decomp, test/export/test_export.py::TestExport::test_export_for_training_with_container_type, test/export/test_export.py::TestExport::test_export_for_training_with_dynamic_shapes, test/export/test_export.py::TestExport::test_export_for_training_with_mutation, test/export/test_export.py::TestExport::test_export_for_training_with_state_dict_hooks, test/export/test_export.py::TestExport::test_export_func_with_default_kwargs, test/export/test_export.py::TestExport::test_export_func_with_keyword_only_args, test/export/test_export.py::TestExport::test_export_func_with_kwargs, test/export/test_export.py::TestExport::test_export_func_with_pytree_kwargs, test/export/test_export.py::TestExport::test_export_func_with_var_keyword_args, test/export/test_export.py::TestExport::test_export_func_with_var_keyword_pytree_args, test/export/test_export.py::TestExport::test_export_func_with_var_postional_args, test/export/test_export.py::TestExport::test_export_function_schema, test/export/test_export.py::TestExport::test_export_graph_with_no_inputs, test/export/test_export.py::TestExport::test_export_input_mutation_bug, test/export/test_export.py::TestExport::test_export_input_mutation_dynamic_shape, test/export/test_export.py::TestExport::test_export_input_mutation_static_shape, test/export/test_export.py::TestExport::test_export_linear_preserve_dynamic_shape, test/export/test_export.py::TestExport::test_export_max_nonstrict, test/export/test_export.py::TestExport::test_export_max_onnx_reported, test/export/test_export.py::TestExport::test_export_method, test/export/test_export.py::TestExport::test_export_mod_constraints, test/export/test_export.py::TestExport::test_export_module, test/export/test_export.py::TestExport::test_export_preserve_linear_at_aot_level, test/export/test_export.py::TestExport::test_export_preserve_linear_but_not_custom_op, test/export/test_export.py::TestExport::test_export_scan_pytree_output, test/export/test_export.py::TestExport::test_export_script_module, test/export/test_export.py::TestExport::test_export_statically_known_true, test/export/test_export.py::TestExport::test_export_then_compile_tensor_ctor, test/export/test_export.py::TestExport::test_export_with_autocast, test/export/test_export.py::TestExport::test_export_with_fake_tensor_inputs, test/export/test_export.py::TestExport::test_export_with_fake_tensor_inputs_on_cuda_devices, test/export/test_export.py::TestExport::test_export_with_inline_constraints, test/export/test_export.py::TestExport::test_export_with_inline_constraints_complex, test/export/test_export.py::TestExport::test_export_with_set_grad_enabled, test/export/test_export.py::TestExport::test_export_with_wrong_inputs, test/export/test_export.py::TestExport::test_external_call_non_strict_real_tensor, test/export/test_export.py::TestExport::test_fake_inputs, test/export/test_export.py::TestExport::test_fake_weights, test/export/test_export.py::TestExport::test_filter_traceback_frames, test/export/test_export.py::TestExport::test_float_conversion, test/export/test_export.py::TestExport::test_float_conversion_from_int, test/export/test_export.py::TestExport::test_fqn, test/export/test_export.py::TestExport::test_from_node_metadata_export, test/export/test_export.py::TestExport::test_full_on_scalar_tensor, test/export/test_export.py::TestExport::test_hints_wrapper, test/export/test_export.py::TestExport::test_hoo_inline_users_issue, test/export/test_export.py::TestExport::test_if_functional, test/export/test_export.py::TestExport::test_if_post_autograd_op_preserved, test/export/test_export.py::TestExport::test_inline_script_class_method, test/export/test_export.py::TestExport::test_inline_script_class_method_recursive, test/export/test_export.py::TestExport::test_inline_script_function, test/export/test_export.py::TestExport::test_inline_script_method, test/export/test_export.py::TestExport::test_int_shape_specialization, test/export/test_export.py::TestExport::test_intermediate_shape_comp, test/export/test_export.py::TestExport::test_is_exporting, test/export/test_export.py::TestExport::test_is_non_negative_check_function, test/export/test_export.py::TestExport::test_is_nonzero, test/export/test_export.py::TestExport::test_isnonzero, test/export/test_export.py::TestExport::test_issue_113041, test/export/test_export.py::TestExport::test_issue_157289, test/export/test_export.py::TestExport::test_istft_op, test/export/test_export.py::TestExport::test_keep_composite_ops_invalid, test/export/test_export.py::TestExport::test_keep_composite_ops_linear_convd, test/export/test_export.py::TestExport::test_keep_composite_ops_linear_convd_for_training_ir, test/export/test_export.py::TestExport::test_kwarg_dynamic_shapes_diff_order, test/export/test_export.py::TestExport::test_kwargs_reorder, test/export/test_export.py::TestExport::test_layer_norm_unbacked_normalized_shape, test/export/test_export.py::TestExport::test_layer_sharing, test/export/test_export.py::TestExport::test_lazy_module_kwargs, test/export/test_export.py::TestExport::test_lifted_constants, test/export/test_export.py::TestExport::test_linear_conv, test/export/test_export.py::TestExport::test_malformed_fqn_from_source_name, test/export/test_export.py::TestExport::test_map, test/export/test_export.py::TestExport::test_map_buffers, test/export/test_export.py::TestExport::test_mask_nonzero_static, test/export/test_export.py::TestExport::test_masked_select_dynamic, test/export/test_export.py::TestExport::test_math_pow, test/export/test_export.py::TestExport::test_mismatched_dynamic_shapes, test/export/test_export.py::TestExport::test_mixed_input, test/export/test_export.py::TestExport::test_module, test/export/test_export.py::TestExport::test_module_dict_key, test/export/test_export.py::TestExport::test_module_input, test/export/test_export.py::TestExport::test_module_input_subclasses_parameterization_nested, test/export/test_export.py::TestExport::test_module_list_slice, test/export/test_export.py::TestExport::test_module_with_dict_container_inp_out, test/export/test_export.py::TestExport::test_modules_access_for_deleted_submodule, test/export/test_export.py::TestExport::test_more_multidimensional_slicing, test/export/test_export.py::TestExport::test_multidimensional_slicing, test/export/test_export.py::TestExport::test_multinomial_dynamic, test/export/test_export.py::TestExport::test_multiple_definitions_same_name_dim, test/export/test_export.py::TestExport::test_nested_dynamic_shapes_spec, test/export/test_export.py::TestExport::test_nested_module, test/export/test_export.py::TestExport::test_nested_module_with_constant_buffer, test/export/test_export.py::TestExport::test_nested_module_with_init_buffer, test/export/test_export.py::TestExport::test_nested_module_with_parameter, test/export/test_export.py::TestExport::test_nn_module_stack, test/export/test_export.py::TestExport::test_nn_module_stack_shared_submodule, test/export/test_export.py::TestExport::test_no_check_is_size_error, test/export/test_export.py::TestExport::test_no_suggested_fixes_for_data_dependent_errors, test/export/test_export.py::TestExport::test_no_tensor_computation, test/export/test_export.py::TestExport::test_no_tensor_computation_2, test/export/test_export.py::TestExport::test_no_tensor_computation_3, test/export/test_export.py::TestExport::test_no_tensor_computation_4, test/export/test_export.py::TestExport::test_non_arg_name_dynamic_shapes_api, test/export/test_export.py::TestExport::test_non_arg_name_dynamic_shapes_api_with_container_type, test/export/test_export.py::TestExport::test_non_arg_name_dynamic_shapes_api_with_kwarg, test/export/test_export.py::TestExport::test_non_persistent_buffer, test/export/test_export.py::TestExport::test_non_strict_dynamic_shapes, test/export/test_export.py::TestExport::test_non_strict_dynamic_shapes_suggested_fixes, test/export/test_export.py::TestExport::test_none_buffers, test/export/test_export.py::TestExport::test_nonstrict_retrace_preserves_metadata, test/export/test_export.py::TestExport::test_nonzero_2, test/export/test_export.py::TestExport::test_nonzero_dynamic, test/export/test_export.py::TestExport::test_not_registered_parameter, test/export/test_export.py::TestExport::test_operator_aten_tensor_mode_variant, test/export/test_export.py::TestExport::test_output_node_name, test/export/test_export.py::TestExport::test_pad_sequence, test/export/test_export.py::TestExport::test_param_util, test/export/test_export.py::TestExport::test_partial_patched_forward, test/export/test_export.py::TestExport::test_placeholder_naming_collisions, test/export/test_export.py::TestExport::test_placeholder_naming_collisions_hoo_subgraphs, test/export/test_export.py::TestExport::test_placeholder_naming_order, test/export/test_export.py::TestExport::test_placeholder_naming_order_variadic, test/export/test_export.py::TestExport::test_placeholder_update_preserving, test/export/test_export.py::TestExport::test_predispatch_cond, test/export/test_export.py::TestExport::test_predispatch_grad_wrappers, test/export/test_export.py::TestExport::test_preserve_module_call_signature_unflatten_specialization, test/export/test_export.py::TestExport::test_preserve_requires_grad_placeholders, test/export/test_export.py::TestExport::test_preserve_shape_dynamism_for_unused_inputs, test/export/test_export.py::TestExport::test_profiling_code, test/export/test_export.py::TestExport::test_python_asserts_with_sym_int, test/export/test_export.py::TestExport::test_pytree_register_data_class, test/export/test_export.py::TestExport::test_pytree_register_nested_data_class, test/export/test_export.py::TestExport::test_raise_user_error_when_guard_on_data_dependent_operation, test/export/test_export.py::TestExport::test_range_constraints_with_replacement, test/export/test_export.py::TestExport::test_real_tensor_alias_dtype_mismatch, test/export/test_export.py::TestExport::test_real_tensor_bool_cast, test/export/test_export.py::TestExport::test_real_tensor_errors_on_aliasing_custom_op, test/export/test_export.py::TestExport::test_real_tensor_for_max_op, test/export/test_export.py::TestExport::test_real_tensor_size_mismatch, test/export/test_export.py::TestExport::test_redundant_assert_max_upper_bound, test/export/test_export.py::TestExport::test_redundant_asserts, test/export/test_export.py::TestExport::test_refine_dynamic_shapes_from_suggested_fixes, test/export/test_export.py::TestExport::test_register_constant, test/export/test_export.py::TestExport::test_repeat_interleave, test/export/test_export.py::TestExport::test_replace_unbacked_with_very_large_upperbound, test/export/test_export.py::TestExport::test_replaced_unbacked_bindings, test/export/test_export.py::TestExport::test_reshape_view_helper, test/export/test_export.py::TestExport::test_retracable_ep, test/export/test_export.py::TestExport::test_retrace_pre_autograd, test/export/test_export.py::TestExport::test_run_decomposition_supports_user_input_mutation, test/export/test_export.py::TestExport::test_run_decompositions_keep_metadata, test/export/test_export.py::TestExport::test_run_decompositions_keep_tensor_constant_metadata, test/export/test_export.py::TestExport::test_runtime_assert_for_prim, test/export/test_export.py::TestExport::test_runtime_assert_for_prm_str, test/export/test_export.py::TestExport::test_runtime_assert_with_size, test/export/test_export.py::TestExport::test_sdpa_gqa, test/export/test_export.py::TestExport::test_sequential_slicing, test/export/test_export.py::TestExport::test_set_example_inputs, test/export/test_export.py::TestExport::test_set_grad_as_side_effect, test/export/test_export.py::TestExport::test_set_grad_empty, test/export/test_export.py::TestExport::test_set_grad_unflatten, test/export/test_export.py::TestExport::test_setgrad_lifted_tensor, test/export/test_export.py::TestExport::test_shared_submodule_nn_module_stack, test/export/test_export.py::TestExport::test_simple_export_for_training, test/export/test_export.py::TestExport::test_simple_unbacked_view, test/export/test_export.py::TestExport::test_size_input, test/export/test_export.py::TestExport::test_slice_nn_module_stack, test/export/test_export.py::TestExport::test_solver_unsupported_sympy_function, test/export/test_export.py::TestExport::test_specialize_derived_dim_roots, test/export/test_export.py::TestExport::test_split_const_gm_with_lifted_constants, test/export/test_export.py::TestExport::test_stack_trace, test/export/test_export.py::TestExport::test_stack_trace_make_fx, test/export/test_export.py::TestExport::test_state_primitives, test/export/test_export.py::TestExport::test_state_shape_attribute_assignment, test/export/test_export.py::TestExport::test_state_tensors, test/export/test_export.py::TestExport::test_static_dim_constraints, test/export/test_export.py::TestExport::test_subclass_nested_attr_access, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_complicated_metadata, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_const_metadata, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_const_metadata_not_top_level, test/export/test_export.py::TestExport::test_subclass_nested_attr_access_submodule, test/export/test_export.py::TestExport::test_subclasses_parameterization, test/export/test_export.py::TestExport::test_subclasses_parameterization_nested, test/export/test_export.py::TestExport::test_suggest_torch_checks_with_non_negative_check, test/export/test_export.py::TestExport::test_suggest_torch_checks_with_regular_check, test/export/test_export.py::TestExport::test_suggested_fixes_for_data_dependent_errors_basic, test/export/test_export.py::TestExport::test_suggested_fixes_for_data_dependent_errors_puzzlers, test/export/test_export.py::TestExport::test_suggested_fixes_new_roots, test/export/test_export.py::TestExport::test_sym_float_operators, test/export/test_export.py::TestExport::test_sym_or_sym_and, test/export/test_export.py::TestExport::test_sym_sqrt, test/export/test_export.py::TestExport::test_symbool_item, test/export/test_export.py::TestExport::test_symfloat_item, test/export/test_export.py::TestExport::test_symint_input_additional_inputs, test/export/test_export.py::TestExport::test_symint_input_basic, test/export/test_export.py::TestExport::test_symint_input_ranges, test/export/test_export.py::TestExport::test_symint_input_shapes_collection, test/export/test_export.py::TestExport::test_symint_input_specialization, test/export/test_export.py::TestExport::test_symint_item, test/export/test_export.py::TestExport::test_symint_output, test/export/test_export.py::TestExport::test_symint_tensor_return, test/export/test_export.py::TestExport::test_tensor_attribute_zero_args, test/export/test_export.py::TestExport::test_tensor_constant_aten_to, test/export/test_export.py::TestExport::test_tensor_constant_with_wrapped_method, test/export/test_export.py::TestExport::test_to_module_with_mutated_buffer, test/export/test_export.py::TestExport::test_to_module_with_mutated_buffer_multiple, test/export/test_export.py::TestExport::test_to_module_with_mutated_buffer_multiple_update_sub_later, test/export/test_export.py::TestExport::test_tolist, test/export/test_export.py::TestExport::test_torch_check_eq_commutativity, test/export/test_export.py::TestExport::test_torch_fn, test/export/test_export.py::TestExport::test_trace_under_fake, test/export/test_export.py::TestExport::test_train_eval_on_exported_preautograd_module, test/export/test_export.py::TestExport::test_unbacked_3d_matmul, test/export/test_export.py::TestExport::test_unbacked_bincount, test/export/test_export.py::TestExport::test_unbacked_bindings_for_divisible_u_symint, test/export/test_export.py::TestExport::test_unbacked_deferred_runtime_retrace, test/export/test_export.py::TestExport::test_unbacked_expand, test/export/test_export.py::TestExport::test_unbacked_infer_size, test/export/test_export.py::TestExport::test_unbacked_kth_value, test/export/test_export.py::TestExport::test_unbacked_linear_layer_norm_input, test/export/test_export.py::TestExport::test_unbacked_noncontig_lin, test/export/test_export.py::TestExport::test_unbacked_pad, test/export/test_export.py::TestExport::test_unbacked_scalar_constructor, test/export/test_export.py::TestExport::test_unbacked_slice, test/export/test_export.py::TestExport::test_unbacked_to_cond, test/export/test_export.py::TestExport::test_unbacked_to_cond_passthrough, test/export/test_export.py::TestExport::test_unbacked_unsqueeze, test/export/test_export.py::TestExport::test_unflatten_asserts, test/export/test_export.py::TestExport::test_unflatten_buffer_update_child2parent_swap, test/export/test_export.py::TestExport::test_unflatten_closure, test/export/test_export.py::TestExport::test_unflatten_isinstance, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_dispatch, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_preserve_signature_no_error, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_shared_submodule, test/export/test_export.py::TestExport::test_unflatten_multiple_graphs_state, test/export/test_export.py::TestExport::test_unflatten_no_unroll, test/export/test_export.py::TestExport::test_unflatten_placeholder_update_child2parent_swap, test/export/test_export.py::TestExport::test_unflatten_placeholder_update_grandchild2cousin_swap, test/export/test_export.py::TestExport::test_unflatten_random_dag_5, test/export/test_export.py::TestExport::test_unflatten_random_dag_6, test/export/test_export.py::TestExport::test_unflatten_random_dag_buf_8, test/export/test_export.py::TestExport::test_unflatten_random_dag_const_preserving_3, test/export/test_export.py::TestExport::test_unflatten_random_dag_const_preserving_3_1, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_4, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_6, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_9, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_10, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_4, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_4_1, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_5, test/export/test_export.py::TestExport::test_unflatten_random_dag_mutating_buf_preserving_7, test/export/test_export.py::TestExport::test_unflatten_random_dag_preserving_4, test/export/test_export.py::TestExport::test_unused_aliases, test/export/test_export.py::TestExport::test_unused_constant, test/export/test_export.py::TestExport::test_use_embedding_twice, test/export/test_export.py::TestExport::test_user_input_and_buffer_mutation, test/export/test_export.py::TestExport::test_vmap, test/export/test_export.py::TestExport::test_while_loop_assert_separation, test/export/test_export.py::TestExport::test_while_loop_index_assertions, test/export/test_export.py::TestExport::test_while_loop_simple, test/export/test_export.py::TestExport::test_while_loop_tensor_constant_idx, test/export/test_export.py::TestExport::test_wrapper_module, test/export/test_export.py::TestOneOffModelExportResult::test_assert_tensor_metadata_device_index, test/export/test_export.py::TestOneOffModelExportResult::test_constant_fqn, test/export/test_export.py::TestOneOffModelExportResult::test_constant_name, test/export/test_export.py::TestOneOffModelExportResult::test_duplicated_getitem, test/export/test_export.py::TestOneOffModelExportResult::test_hf_logging_logger, test/export/test_export.py::TestOneOffModelExportResult::test_input_output_no_stacktrace, test/export/test_export.py::TestOneOffModelExportResult::test_int_list_output, test/export/test_export.py::TestOneOffModelExportResult::test_logging_logger, test/export/test_export.py::TestOneOffModelExportResult::test_nested_retrace, test/export/test_export.py::TestOneOffModelExportResult::test_none_input_output, test/export/test_export.py::TestOneOffModelExportResult::test_primitive_constant_output, test/export/test_export.py::TestOneOffModelExportResult::test_print, test/export/test_export.py::TestOneOffModelExportResult::test_print_graph_signature, test/export/test_export.py::TestOneOffModelExportResult::test_scaled_dot_product_attention_cpu, test/export/test_export.py::TestOneOffModelExportResult::test_scaled_dot_product_attention_cuda, test/export/test_export.py::TestOneOffModelExportResult::test_strict_export_with_shared_parameters, test/export/test_export.py::TestOneOffModelExportResult::test_torchrec_jagged_tensor, test/export/test_export.py::TestOneOffModelExportResult::test_unbacked_sdpa, test/export/test_export.py::TestOneOffModelExportResult::test_warning, test/export/test_export.py::TestExportCustomClass::test_export_script_module, test/export/test_export.py::TestExportCustomClass::test_export_unbacked_lt, test/export/test_export.py::TestExportCustomClass::test_int_lift_constant, test/export/test_export.py::TestExportCustomClass::test_lift_custom_obj, test/export/test_export.py::TestExportCustomClass::test_preserve_cia_op, test/export/test_export.py::TestExportCustomClass::test_preserve_non_cia_op, test/export/test_export.py::TestExportCustomClass::test_unbacked_contiguous, test/export/test_export.py::TestExportCustomClass::test_unbacked_select_index 2025-08-26T20:50:46.8454786Z 2025-08-26T20:50:49.9982377Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:50:49.9985292Z import pkg_resources 2025-08-26T20:50:50.1187756Z Running dynamo/test_deviceguard 1/1 ... [2025-08-26 20:50:50.118417] 2025-08-26T20:50:50.1188802Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:50:50.1190929Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_deviceguard.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:50:50.118765] 2025-08-26T20:50:53.5886383Z 2025-08-26T20:50:53.5888104Z dynamo/test_deviceguard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_deviceguard_1.1_8aef425a3e1beff3_.log 2025-08-26T20:50:53.5890357Z Running 4 items in this shard: test/dynamo/test_deviceguard.py::TestDeviceGuard::test_device_guard, test/dynamo/test_deviceguard.py::TestDeviceGuard::test_device_guard_no_index, test/dynamo/test_deviceguard.py::TestCUDADeviceGuard::test_device_guard, test/dynamo/test_deviceguard.py::TestCUDADeviceGuard::test_device_guard_no_index 2025-08-26T20:50:53.5891830Z 2025-08-26T20:50:56.7465844Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:50:56.7467505Z import pkg_resources 2025-08-26T20:50:56.8694980Z Running export/test_swap 1/1 ... [2025-08-26 20:50:56.869195] 2025-08-26T20:50:56.8695416Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:50:56.8697788Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_swap.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:50:56.869527] 2025-08-26T20:50:57.7846557Z 2025-08-26T20:50:57.7847930Z dynamo/test_backward_higher_order_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_backward_higher_order_ops_1.1_ea4cba785d2854e9_.log 2025-08-26T20:50:57.7852225Z Running 7 items in this shard: test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_eager, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2_compiled_autograd, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2_compiled_autograd_graph_breaks, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_in_pt2_compiled_autograd_side_effect, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_make_bw, test/dynamo/test_backward_higher_order_ops.py::BackwardHigherOrderOpTests::test_invoke_make_fx_forward_contrived 2025-08-26T20:50:57.7855838Z 2025-08-26T20:51:01.0555168Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:01.0557760Z import pkg_resources 2025-08-26T20:51:01.1787287Z Running dynamo/test_export 1/1 ... [2025-08-26 20:51:01.178366] 2025-08-26T20:51:01.1787998Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:01.1790049Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_export.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:01.178697] 2025-08-26T20:51:10.0790723Z 2025-08-26T20:51:10.0792366Z inductor/test_cpu_select_algorithm 12/16 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_cpu_select_algorithm_12.16_bdebc809c97de968_.log 2025-08-26T20:51:10.0924169Z Running 97 items in this shard: test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_2d_permute_Ndim_61_order0_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_2d_permute_Ndim_61_order3_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_2d_permute_Ndim_64_order0_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_2d_permute_Ndim_64_order1_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_y_storage_offset_bs_1_Mdim_192_Kdim_196_Ndim_385_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_y_storage_offset_bs_50_Mdim_192_Kdim_196_Ndim_385_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_bmm_with_y_storage_offset_bs_50_Mdim_192_Kdim_196_Ndim_84_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_False_bfloat16_per_channel_quant_False_reshape_a_False_expand_a_scale_False_dynamic_False_M_32_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_True_bfloat16_per_channel_quant_True_reshape_a_False_expand_a_scale_False_dynamic_True_M_32_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_da8w8_sym_act_sym_wgt_with_int_mm_has_bias_True_float32_per_channel_quant_False_reshape_a_False_expand_a_scale_False_dynamic_True_M_1_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_False_bias2_epilogue3_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_grouped_linear_epilogue_batch_size_16_in_features_52_out_features_32_input_3d_True_bias0_epilogue0_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int4_woq_mm_amx_batch_size_4_in_features_128_out_features_1024_group_size_64_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int4_woq_mm_avx512_batch_size_1_in_features_256_out_features_64_group_size_32_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_17_mid_dim_1_in_features_1024_out_features_1024_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_int8_woq_mm_batch_size_1_mid_dim_8_in_features_1024_out_features_1024_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_cache_blocking_batch_size_512_in_features_1024_out_features_1024_bias_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_k_slicing_batch_size_2_in_features_1000_out_features_2_bias_True_epilogue_none_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_local_and_global_buffer_dynamic_shapes_batch_size_256_in_features_3_out_features_1024_out_features2_2_bias_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1000_in_features_1000_out_features_1_bias_True_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1000_in_features_1_out_features_1024_bias_False_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1024_bias_False_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1000_out_features_1024_bias_True_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1_out_features_1024_bias_False_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1_out_features_1024_bias_True_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_1_in_features_1_out_features_1_bias_False_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1000_out_features_1024_bias_False_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_static_shapes_batch_size_2_in_features_1000_out_features_1_bias_True_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_embedding_batch_size_384_in_features_196_out_features_384_bias_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_hardsigmoid_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_div_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_sigmoid_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_pointwise_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_div_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_128_bias_False_epilogue_add_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_False_epilogue_mul_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_transpose_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_div_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_385_bias_False_unary_relu_binary_mul_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_385_bias_False_unary_relu_binary_sub_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_linear_with_unary_binary_batch_size_384_in_features_196_out_features_385_bias_False_unary_relu_binary_sub_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_local_and_global_accumulator_out_features1_32_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_local_and_global_accumulator_out_features1_8_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_32_in_features_128_out_features_65_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_32_in_features_68_out_features_64_bias_False_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_amx_batch_size_49_in_features_68_out_features_64_bias_True_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmCPU::test_quantized_linear_with_pointwise_binary_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_False_int8_mixed_bf16_True_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_bmm_with_pointwise_dynamic_shapes_bs_5_Mdim_384_Kdim_96_Ndim_64_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_False_bias2_epilogue2_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_False_bias3_epilogue4_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_True_bias1_epilogue0_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_grouped_linear_epilogue_dynamic_shapes_batch_size_16_in_features_52_out_features_32_input_3d_True_bias2_epilogue3_cpu, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1000_out_features_1024_bias_True_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1_out_features_1024_bias_True_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1000_in_features_1_out_features_1_bias_True_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1000_out_features_1024_bias_False_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1000_out_features_1_bias_False_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1000_out_features_1_bias_False_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1000_out_features_1_bias_True_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1024_bias_True_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1024_bias_True_input_3d_True_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1_bias_False_input_3d_False_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1_bias_False_input_3d_True_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_1_in_features_1_out_features_1_bias_True_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_2_in_features_1000_out_features_1024_bias_False_input_3d_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_2_in_features_1000_out_features_1_bias_True_input_3d_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_dynamic_shapes_batch_size_2_in_features_1_out_features_1024_bias_True_input_3d_False_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_k_slicing_dynamic_shapes_batch_size_2_in_features_1000_out_features_2_bias_False_epilogue_relu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_thread_factors_dynamic_shapes_batch_size_1024_in_features_1024_out_features_1024_bias_True_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_embedding_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_False_epilogue_tanh_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_div_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_leaky_relu_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_mul_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_epilogue_sigmoid_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_hardsigmoid_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_epilogue_tanh_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_gelu_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_relu_cpu_float16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_pointwise_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_True_epilogue_tanh_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_transpose_dynamic_shapes_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_none_cpu_float32, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_transpose_dynamic_shapes_batch_size_384_in_features_196_out_features_129_bias_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_384_bias_True_unary_relu_binary_mul_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_linear_with_unary_binary_dynamic_shapes_batch_size_384_in_features_196_out_features_385_bias_False_unary_relu_binary_add_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_binary_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_int8_mixed_bf16_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_binary_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_True_input_3d_False_int8_mixed_bf16_True_epilogue_none_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_False_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_epilogue_gelu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_False_input_3d_True_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_64_bias_True_input_3d_False_epilogue_relu_cpu_bfloat16, test/inductor/test_cpu_select_algorithm.py::TestSelectAlgorithmDynamicShapesCPU::test_quantized_linear_with_pointwise_dynamic_shapes_batch_size_32_in_features_128_out_features_65_bias_False_input_3d_False_epilogue_none_cpu_bfloat16 2025-08-26T20:51:10.1099283Z 2025-08-26T20:51:10.2041830Z 2025-08-26T20:51:10.2042804Z export/test_swap 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_swap_1.1_87059e91961312ac_.log 2025-08-26T20:51:10.2048949Z Running 18 items in this shard: test/export/test_swap.py::TestSwap_nonstrict::test_custom_input_args, test/export/test_swap.py::TestSwap_nonstrict::test_custom_input_kwargs, test/export/test_swap.py::TestSwap_nonstrict::test_custom_output, test/export/test_swap.py::TestSwap_nonstrict::test_dedup_sym_size, test/export/test_swap.py::TestSwap_nonstrict::test_nested_leaf, test/export/test_swap.py::TestSwap_nonstrict::test_remove_duplicate_pytree_different_order, test/export/test_swap.py::TestSwap_nonstrict::test_remove_duplicate_pytree_simple, test/export/test_swap.py::TestSwap_nonstrict::test_unflatten_preserve_signature, test/export/test_swap.py::TestSwap_nonstrict::test_unflatten_preserve_with_unused_input, test/export/test_swap.py::TestSwap_strict::test_custom_input_args, test/export/test_swap.py::TestSwap_strict::test_custom_input_kwargs, test/export/test_swap.py::TestSwap_strict::test_custom_output, test/export/test_swap.py::TestSwap_strict::test_dedup_sym_size, test/export/test_swap.py::TestSwap_strict::test_nested_leaf, test/export/test_swap.py::TestSwap_strict::test_remove_duplicate_pytree_different_order, test/export/test_swap.py::TestSwap_strict::test_remove_duplicate_pytree_simple, test/export/test_swap.py::TestSwap_strict::test_unflatten_preserve_signature, test/export/test_swap.py::TestSwap_strict::test_unflatten_preserve_with_unused_input 2025-08-26T20:51:10.2054997Z 2025-08-26T20:51:13.2524954Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:13.2526965Z import pkg_resources 2025-08-26T20:51:13.3760725Z Running dynamo/test_debug_utils 1/1 ... [2025-08-26 20:51:13.375741] 2025-08-26T20:51:13.3761225Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:13.3763984Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_debug_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:13.376133] 2025-08-26T20:51:13.4287533Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:13.4289324Z import pkg_resources 2025-08-26T20:51:13.5537788Z Running dynamo/test_flat_apply 1/1 ... [2025-08-26 20:51:13.553410] 2025-08-26T20:51:13.5538311Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:13.5540184Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_flat_apply.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:13.553732] 2025-08-26T20:51:17.1455709Z 2025-08-26T20:51:17.1456818Z dynamo/test_debug_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_debug_utils_1.1_dd4a113df3130c83_.log 2025-08-26T20:51:17.1458359Z Running 2 items in this shard: test/dynamo/test_debug_utils.py::TestDebugUtilsCPU::test_cast_model_to_fp64_dtype_args_cpu, test/dynamo/test_debug_utils.py::TestDebugUtilsCPU::test_generate_env_vars_string_cpu 2025-08-26T20:51:17.1459281Z 2025-08-26T20:51:17.5235834Z 2025-08-26T20:51:17.5237086Z dynamo/test_flat_apply 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_flat_apply_1.1_76d65b7fc63c4087_.log 2025-08-26T20:51:17.5239460Z Running 4 items in this shard: test/dynamo/test_flat_apply.py::FlatApplyTests::test_non_tensor_output, test/dynamo/test_flat_apply.py::FlatApplyTests::test_nonstrict_trace_captured_tensor_post_aot_graph, test/dynamo/test_flat_apply.py::FlatApplyTests::test_nonstrict_trace_dynamo_graph, test/dynamo/test_flat_apply.py::FlatApplyTests::test_simple 2025-08-26T20:51:17.5240994Z 2025-08-26T20:51:20.3628917Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:20.3630790Z import pkg_resources 2025-08-26T20:51:20.4868816Z Running dynamo/test_optimizers 1/1 ... [2025-08-26 20:51:20.486600] 2025-08-26T20:51:20.4869316Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:20.4871335Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_optimizers.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:20.486914] 2025-08-26T20:51:20.8349041Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:20.8350633Z import pkg_resources 2025-08-26T20:51:20.9834026Z Running dynamo/test_verify_correctness 1/1 ... [2025-08-26 20:51:20.983104] 2025-08-26T20:51:20.9834535Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:20.9836582Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_verify_correctness.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:20.983427] 2025-08-26T20:51:25.2537009Z 2025-08-26T20:51:25.2538329Z dynamo/test_verify_correctness 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_verify_correctness_1.1_1d000412454d1b4d_.log 2025-08-26T20:51:25.2541088Z Running 4 items in this shard: test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_example_inputs, test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_incorrect_verify_false, test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_incorrect_verify_true, test/dynamo/test_verify_correctness.py::TestVerifyCorrectness::test_torchscript 2025-08-26T20:51:25.2542839Z 2025-08-26T20:51:25.8095445Z 2025-08-26T20:51:25.8096958Z dynamo/test_optimizers 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_optimizers_1.1_8b773086c8211d1b_.log 2025-08-26T20:51:25.8100572Z Running 3 items in this shard: test/dynamo/test_optimizers.py::End2EndTests::test_init_group, test/dynamo/test_optimizers.py::End2EndTests::test_optimizing_over_tensor_with_requires_grad, test/dynamo/test_optimizers.py::End2EndTests::test_state_dict 2025-08-26T20:51:25.8102731Z 2025-08-26T20:51:28.4966115Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:28.4969286Z import pkg_resources 2025-08-26T20:51:28.6206014Z Running dynamo/test_sets 1/1 ... [2025-08-26 20:51:28.620243] 2025-08-26T20:51:28.6206855Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:28.6209842Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_sets.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:28.620647] 2025-08-26T20:51:28.9676145Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:28.9677920Z import pkg_resources 2025-08-26T20:51:29.1534042Z Running inductor/test_unbacked_symints 1/1 ... [2025-08-26 20:51:29.153042] 2025-08-26T20:51:29.1534574Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:29.1536167Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_unbacked_symints.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:29.153371] 2025-08-26T20:51:40.6041120Z 2025-08-26T20:51:40.6042038Z dynamo/test_sets 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_sets_1.1_649e49c5b7d083ed_.log 2025-08-26T20:51:40.6076302Z Running 124 items in this shard: test/dynamo/test_sets.py::CustomSetTests::test_custom_add, test/dynamo/test_sets.py::CustomSetTests::test_custom_contains, test/dynamo/test_sets.py::MiscTests::test_isdisjoint_with_generator, test/dynamo/test_sets.py::TestSetGuards::test_in_guard, test/dynamo/test_sets.py::TestSetGuards::test_set_guard_on_keys_change, test/dynamo/test_sets.py::TestSetGuards::test_set_multiple_types, test/dynamo/test_sets.py::TestSetGuards::test_set_recompile_on_key_change, test/dynamo/test_sets.py::TestSetGuards::test_set_recompile_on_key_pop, test/dynamo/test_sets.py::TestSetGuards::test_set_with_function, test/dynamo/test_sets.py::TestSetGuards::test_set_with_tensors, test/dynamo/test_sets.py::FrozensetTests::test_binop_and, test/dynamo/test_sets.py::FrozensetTests::test_binop_or, test/dynamo/test_sets.py::FrozensetTests::test_binop_sub, test/dynamo/test_sets.py::FrozensetTests::test_binop_xor, test/dynamo/test_sets.py::FrozensetTests::test_cmp_eq, test/dynamo/test_sets.py::FrozensetTests::test_cmp_greater_than, test/dynamo/test_sets.py::FrozensetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::FrozensetTests::test_cmp_less_than, test/dynamo/test_sets.py::FrozensetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::FrozensetTests::test_cmp_ne, test/dynamo/test_sets.py::FrozensetTests::test_constructor_iterable, test/dynamo/test_sets.py::FrozensetTests::test_contains, test/dynamo/test_sets.py::FrozensetTests::test_copy, test/dynamo/test_sets.py::FrozensetTests::test_difference, test/dynamo/test_sets.py::FrozensetTests::test_equality, test/dynamo/test_sets.py::FrozensetTests::test_in_frozenset, test/dynamo/test_sets.py::FrozensetTests::test_intersection, test/dynamo/test_sets.py::FrozensetTests::test_isdisjoint, test/dynamo/test_sets.py::FrozensetTests::test_issubset, test/dynamo/test_sets.py::FrozensetTests::test_issuperset, test/dynamo/test_sets.py::FrozensetTests::test_symmetric_difference, test/dynamo/test_sets.py::FrozensetTests::test_to_frozenset, test/dynamo/test_sets.py::FrozensetTests::test_to_set, test/dynamo/test_sets.py::FrozensetTests::test_union, test/dynamo/test_sets.py::SetTests::test_add, test/dynamo/test_sets.py::SetTests::test_binop_and, test/dynamo/test_sets.py::SetTests::test_binop_or, test/dynamo/test_sets.py::SetTests::test_binop_sub, test/dynamo/test_sets.py::SetTests::test_binop_xor, test/dynamo/test_sets.py::SetTests::test_clear, test/dynamo/test_sets.py::SetTests::test_cmp_eq, test/dynamo/test_sets.py::SetTests::test_cmp_greater_than, test/dynamo/test_sets.py::SetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::SetTests::test_cmp_less_than, test/dynamo/test_sets.py::SetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::SetTests::test_cmp_ne, test/dynamo/test_sets.py::SetTests::test_constructor_iterable, test/dynamo/test_sets.py::SetTests::test_contains, test/dynamo/test_sets.py::SetTests::test_copy, test/dynamo/test_sets.py::SetTests::test_difference, test/dynamo/test_sets.py::SetTests::test_difference_update, test/dynamo/test_sets.py::SetTests::test_discard, test/dynamo/test_sets.py::SetTests::test_equality, test/dynamo/test_sets.py::SetTests::test_in_frozenset, test/dynamo/test_sets.py::SetTests::test_intersection, test/dynamo/test_sets.py::SetTests::test_intersection_update, test/dynamo/test_sets.py::SetTests::test_isdisjoint, test/dynamo/test_sets.py::SetTests::test_issubset, test/dynamo/test_sets.py::SetTests::test_issuperset, test/dynamo/test_sets.py::SetTests::test_pop, test/dynamo/test_sets.py::SetTests::test_remove, test/dynamo/test_sets.py::SetTests::test_symmetric_difference, test/dynamo/test_sets.py::SetTests::test_symmetric_difference_update, test/dynamo/test_sets.py::SetTests::test_to_frozenset, test/dynamo/test_sets.py::SetTests::test_to_set, test/dynamo/test_sets.py::SetTests::test_union, test/dynamo/test_sets.py::SetTests::test_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_add, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_and, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_or, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_sub, test/dynamo/test_sets.py::UserDefinedSetTests::test_binop_xor, test/dynamo/test_sets.py::UserDefinedSetTests::test_clear, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_eq, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_greater_than, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_less_than, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::UserDefinedSetTests::test_cmp_ne, test/dynamo/test_sets.py::UserDefinedSetTests::test_constructor_iterable, test/dynamo/test_sets.py::UserDefinedSetTests::test_contains, test/dynamo/test_sets.py::UserDefinedSetTests::test_copy, test/dynamo/test_sets.py::UserDefinedSetTests::test_difference, test/dynamo/test_sets.py::UserDefinedSetTests::test_difference_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_discard, test/dynamo/test_sets.py::UserDefinedSetTests::test_equality, test/dynamo/test_sets.py::UserDefinedSetTests::test_in_frozenset, test/dynamo/test_sets.py::UserDefinedSetTests::test_intersection, test/dynamo/test_sets.py::UserDefinedSetTests::test_intersection_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_isdisjoint, test/dynamo/test_sets.py::UserDefinedSetTests::test_issubset, test/dynamo/test_sets.py::UserDefinedSetTests::test_issuperset, test/dynamo/test_sets.py::UserDefinedSetTests::test_pop, test/dynamo/test_sets.py::UserDefinedSetTests::test_remove, test/dynamo/test_sets.py::UserDefinedSetTests::test_symmetric_difference, test/dynamo/test_sets.py::UserDefinedSetTests::test_symmetric_difference_update, test/dynamo/test_sets.py::UserDefinedSetTests::test_to_frozenset, test/dynamo/test_sets.py::UserDefinedSetTests::test_to_set, test/dynamo/test_sets.py::UserDefinedSetTests::test_union, test/dynamo/test_sets.py::UserDefinedSetTests::test_update, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_and, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_or, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_sub, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_binop_xor, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_eq, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_greater_than, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_greater_than_or_equal, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_less_than, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_less_than_or_equal, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_cmp_ne, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_constructor_iterable, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_contains, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_copy, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_difference, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_equality, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_in_frozenset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_intersection, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_isdisjoint, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_issubset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_issuperset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_symmetric_difference, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_to_frozenset, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_to_set, test/dynamo/test_sets.py::UserDefinedFrozensetTests::test_union 2025-08-26T20:51:40.6109461Z 2025-08-26T20:51:43.8273569Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:43.8275166Z import pkg_resources 2025-08-26T20:51:43.9522068Z Running dynamo/test_python_dispatcher 1/1 ... [2025-08-26 20:51:43.951810] 2025-08-26T20:51:43.9523067Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:43.9525417Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_dispatcher.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:43.952153] 2025-08-26T20:51:48.5736716Z 2025-08-26T20:51:48.5738044Z dynamo/test_python_dispatcher 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_dispatcher_1.1_055b921a453437de_.log 2025-08-26T20:51:48.5741582Z Running 6 items in this shard: test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key1, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key2, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key3, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key4, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_dispatch_key_set_guard, test/dynamo/test_python_dispatcher.py::PythonDispatcherTests::test_functorch_interpreter 2025-08-26T20:51:48.5744036Z 2025-08-26T20:51:51.8658589Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:51.8660210Z import pkg_resources 2025-08-26T20:51:51.9903536Z Running dynamo/test_cudagraphs 1/1 ... [2025-08-26 20:51:51.990046] 2025-08-26T20:51:51.9904018Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:51.9907476Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_cudagraphs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:51.990451] 2025-08-26T20:51:55.4347501Z 2025-08-26T20:51:55.4348512Z dynamo/test_cudagraphs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_cudagraphs_1.1_0be297ab460d7760_.log 2025-08-26T20:51:55.4349230Z 2025-08-26T20:51:58.6712168Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:51:58.6713779Z import pkg_resources 2025-08-26T20:51:58.7953982Z Running export/test_unflatten 1/1 ... [2025-08-26 20:51:58.795044] 2025-08-26T20:51:58.7954495Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:51:58.7956329Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_unflatten.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:51:58.795379] 2025-08-26T20:52:04.5723042Z 2025-08-26T20:52:04.5724226Z inductor/test_unbacked_symints 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_unbacked_symints_1.1_3761931a670eb722_.log 2025-08-26T20:52:04.5736878Z Running 27 items in this shard: test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_autotuning_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_broadcast_tensors_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_einsum_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_equivalent_backed_unbacked_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_expand_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_expand_ok_with_runtime_assert_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_issue_143498_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_mm_and_friends_addmm_False_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_mm_and_friends_addmm_True_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_mm_and_friends_bmm_False_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_mm_and_friends_bmm_True_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_mm_and_friends_mm_False_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_mm_and_friends_mm_True_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_nonzero_in_inference_mode_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_sdpfa_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_split_with_sizes_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_to_int_with_unbacked_size_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_triton_kernel_grid_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_unbacked_linear_layer_norm_input_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_unbacked_masked_scatter_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_unbacked_range_tree_divisor_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_unbacked_repeat_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_unbacked_slice_on_subclass_dynamic2_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_unbacked_slice_on_subclass_dynamic_False_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_unbacked_slice_on_subclass_dynamic_True_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_vertical_pointwise_reduction_fusion_cpu, test/inductor/test_unbacked_symints.py::TestUnbackedSymintsCPU::test_view_of_slice_cpu 2025-08-26T20:52:07.7643871Z 2025-08-26T20:52:07.7646841Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:52:07.7650089Z import pkg_resources 2025-08-26T20:52:07.8880556Z Running inductor/test_efficient_conv_bn_eval 1/1 ... [2025-08-26 20:52:07.887600] 2025-08-26T20:52:07.8881609Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:52:07.8883909Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'inductor/test_efficient_conv_bn_eval.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:52:07.887943] 2025-08-26T20:52:15.3635859Z 2025-08-26T20:52:15.3637139Z inductor/test_efficient_conv_bn_eval 1/1 was successful, full logs can be found in artifacts with path test/test-reports/inductor.test_efficient_conv_bn_eval_1.1_e113d16af7ed8a8d_.log 2025-08-26T20:52:15.3638671Z Running 1 items in this shard: test/inductor/test_efficient_conv_bn_eval.py::EfficientConvBNEvalCpuTests::test_basic_cpu 2025-08-26T20:52:15.3639252Z 2025-08-26T20:52:15.7846871Z 2025-08-26T20:52:15.7848215Z export/test_unflatten 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_unflatten_1.1_3a38a030eb1f7c70_.log 2025-08-26T20:52:15.7858536Z Running 28 items in this shard: test/export/test_unflatten.py::TestUnflatten::test_assert_tensor_metadata_stack, test/export/test_unflatten.py::TestUnflatten::test_attr_as_submod_input, test/export/test_unflatten.py::TestUnflatten::test_dedup_sym_size, test/export/test_unflatten.py::TestUnflatten::test_double_nested_submodule, test/export/test_unflatten.py::TestUnflatten::test_duplicate_placeholder, test/export/test_unflatten.py::TestUnflatten::test_fx_trace, test/export/test_unflatten.py::TestUnflatten::test_nested_leaf_non_strict, test/export/test_unflatten.py::TestUnflatten::test_placeholder_and_get_attr_ordering_after_unflattened, test/export/test_unflatten.py::TestUnflatten::test_simple_alias, test/export/test_unflatten.py::TestUnflatten::test_unflatten_buffer_mutation, test/export/test_unflatten.py::TestUnflatten::test_unflatten_constant_obj, test/export/test_unflatten.py::TestUnflatten::test_unflatten_constant_tensor, test/export/test_unflatten.py::TestUnflatten::test_unflatten_container_type, test/export/test_unflatten.py::TestUnflatten::test_unflatten_eager, test/export/test_unflatten.py::TestUnflatten::test_unflatten_empty_branch, test/export/test_unflatten.py::TestUnflatten::test_unflatten_nested, test/export/test_unflatten.py::TestUnflatten::test_unflatten_nested_access, test/export/test_unflatten.py::TestUnflatten::test_unflatten_none, test/export/test_unflatten.py::TestUnflatten::test_unflatten_param_list_dict, test/export/test_unflatten.py::TestUnflatten::test_unflatten_preserve_signature, test/export/test_unflatten.py::TestUnflatten::test_unflatten_preserve_with_unused_input, test/export/test_unflatten.py::TestUnflatten::test_unflatten_requires_grad_param, test/export/test_unflatten.py::TestUnflatten::test_unflatten_shared_submodule, test/export/test_unflatten.py::TestUnflatten::test_unflatten_skipped_call_module, test/export/test_unflatten.py::TestUnflatten::test_unflatten_submodule_ordering, test/export/test_unflatten.py::TestUnflatten::test_unflatten_with_inplace_compile, test/export/test_unflatten.py::TestUnflatten::test_unflatten_wrong_input, test/export/test_unflatten.py::TestUnflatten::test_unflattened_module_nodes_has_meta_val 2025-08-26T20:52:15.7868341Z 2025-08-26T20:52:16.5956848Z Uploading artifacts took 1.23 seconds 2025-08-26T20:52:18.5945665Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:52:18.5947261Z import pkg_resources 2025-08-26T20:52:18.7199394Z Running export/test_nativert 1/1 ... [2025-08-26 20:52:18.719551] 2025-08-26T20:52:18.7199879Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:52:18.7202179Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_nativert.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:52:18.719937] 2025-08-26T20:52:19.0343792Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:52:19.0347139Z import pkg_resources 2025-08-26T20:52:19.1783277Z Running dynamo/test_activation_checkpointing 1/1 ... [2025-08-26 20:52:19.177967] 2025-08-26T20:52:19.1783842Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:52:19.1785587Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_activation_checkpointing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:52:19.178285] 2025-08-26T20:52:27.2557628Z 2025-08-26T20:52:27.2559181Z dynamo/test_activation_checkpointing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_activation_checkpointing_1.1_00b54b784c7dd18a_.log 2025-08-26T20:52:27.2560785Z Running 0 items in this shard: 2025-08-26T20:52:27.2561095Z 2025-08-26T20:52:30.4482276Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:52:30.4483892Z import pkg_resources 2025-08-26T20:52:30.5727823Z Running dynamo/test_hooks 1/1 ... [2025-08-26 20:52:30.572448] 2025-08-26T20:52:30.5728265Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:52:30.5731229Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_hooks.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:52:30.572854] 2025-08-26T20:52:53.9580007Z 2025-08-26T20:52:53.9581595Z dynamo/test_export 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_export_1.1_334be70ba3e1422e_.log 2025-08-26T20:52:53.9696496Z Running 184 items in this shard: test/dynamo/test_export.py::ExportTests::test_access_class_method_from_user_class_attr, test/dynamo/test_export.py::ExportTests::test_access_class_method_from_user_class_builtin, test/dynamo/test_export.py::ExportTests::test_byte_tensor_does_not_crash, test/dynamo/test_export.py::ExportTests::test_capture_symbolic_tracing_simple_within_fake_mode, test/dynamo/test_export.py::ExportTests::test_capture_symbolic_tracing_within_fake_mode, test/dynamo/test_export.py::ExportTests::test_cond_free_variables_overlapping, test/dynamo/test_export.py::ExportTests::test_cond_op_param_buffer_lifted, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_branch_args_mismatch, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_branch_return_multiple_tensors, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_branch_return_non_tensor, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_mismatch_return_length, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_mismatch_return_tensor_meta, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_missing_args, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_non_list_operands, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_non_tensor_operands, test/dynamo/test_export.py::ExportTests::test_cond_raise_user_error_on_unsupported_pred, test/dynamo/test_export.py::ExportTests::test_cond_supported_pred_types, test/dynamo/test_export.py::ExportTests::test_constraint_violation_error_messages, test/dynamo/test_export.py::ExportTests::test_dataclass_input_output, test/dynamo/test_export.py::ExportTests::test_dict_return, test/dynamo/test_export.py::ExportTests::test_dict_return_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_dupes, test/dynamo/test_export.py::ExportTests::test_dupes_2, test/dynamo/test_export.py::ExportTests::test_dupes_2_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass_reorder_with_non_tensor_arg, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass_reorder_with_non_tensor_arg_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass_with_non_tensor_arg, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass_with_non_tensor_arg_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass_with_non_tensor_output, test/dynamo/test_export.py::ExportTests::test_dupes_and_bypass_with_non_tensor_output_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_dupes_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_dynamic_slicing, test/dynamo/test_export.py::ExportTests::test_dynamic_slicing_invalid, test/dynamo/test_export.py::ExportTests::test_dynamic_slicing_simple, test/dynamo/test_export.py::ExportTests::test_dynamo_enum_in_tuple, test/dynamo/test_export.py::ExportTests::test_dynamo_list_index, test/dynamo/test_export.py::ExportTests::test_empty, test/dynamo/test_export.py::ExportTests::test_enforce_equalities, test/dynamo/test_export.py::ExportTests::test_export, test/dynamo/test_export.py::ExportTests::test_export_compare_optimize_with_make_fx, test/dynamo/test_export.py::ExportTests::test_export_cond_in_aten_symbolic, test/dynamo/test_export.py::ExportTests::test_export_control_flow_with_getattr, test/dynamo/test_export.py::ExportTests::test_export_decomp, test/dynamo/test_export.py::ExportTests::test_export_decomp_asserts_bad_args, test/dynamo/test_export.py::ExportTests::test_export_defaults_ok, test/dynamo/test_export.py::ExportTests::test_export_dynamic_control_flow_error, test/dynamo/test_export.py::ExportTests::test_export_dynamic_dim_cleanup, test/dynamo/test_export.py::ExportTests::test_export_dynamic_dim_not_1, test/dynamo/test_export.py::ExportTests::test_export_dynamic_dim_range_constraint, test/dynamo/test_export.py::ExportTests::test_export_graph_bypass, test/dynamo/test_export.py::ExportTests::test_export_graph_bypass_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_export_graph_with_complex_reorder, test/dynamo/test_export.py::ExportTests::test_export_graph_with_complex_reorder_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_export_graph_with_list, test/dynamo/test_export.py::ExportTests::test_export_graph_with_list_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_export_identity, test/dynamo/test_export.py::ExportTests::test_export_masking_with_no_grad, test/dynamo/test_export.py::ExportTests::test_export_meta, test/dynamo/test_export.py::ExportTests::test_export_meta_val, test/dynamo/test_export.py::ExportTests::test_export_mismatched_out, test/dynamo/test_export.py::ExportTests::test_export_mismatched_out_2, test/dynamo/test_export.py::ExportTests::test_export_mismatched_out_2_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_export_mismatched_out_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_export_module_specify_constraints_signature, test/dynamo/test_export.py::ExportTests::test_export_multi_dynamic_dim_constraint, test/dynamo/test_export.py::ExportTests::test_export_multi_dynamic_dim_unsafe_relationship, test/dynamo/test_export.py::ExportTests::test_export_nn_module_stack_patched_module, test/dynamo/test_export.py::ExportTests::test_export_no_raise, test/dynamo/test_export.py::ExportTests::test_export_no_tensor_computation_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_export_pass_arg_by_name, test/dynamo/test_export.py::ExportTests::test_export_pass_arg_by_name_star_args, test/dynamo/test_export.py::ExportTests::test_export_persist_assert, test/dynamo/test_export.py::ExportTests::test_export_preserve_constraints_as_metadata_tensor, test/dynamo/test_export.py::ExportTests::test_export_preserves_nn_module_stack_for_get_attr, test/dynamo/test_export.py::ExportTests::test_export_raise_guard_full_constraint, test/dynamo/test_export.py::ExportTests::test_export_raise_guard_partial_constraint, test/dynamo/test_export.py::ExportTests::test_export_raise_on_relationship, test/dynamo/test_export.py::ExportTests::test_export_shape_control_flow_1, test/dynamo/test_export.py::ExportTests::test_export_specialized_int, test/dynamo/test_export.py::ExportTests::test_export_symbolic_shape, test/dynamo/test_export.py::ExportTests::test_export_with_args_and_empty_kwargs, test/dynamo/test_export.py::ExportTests::test_export_with_args_with_default_None, test/dynamo/test_export.py::ExportTests::test_export_with_args_with_default_float, test/dynamo/test_export.py::ExportTests::test_export_with_args_with_default_tensor, test/dynamo/test_export.py::ExportTests::test_export_with_args_with_default_tuple, test/dynamo/test_export.py::ExportTests::test_export_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_export_with_builtin_op_on_assume_constant, test/dynamo/test_export.py::ExportTests::test_export_with_cond_branches_calling_methods, test/dynamo/test_export.py::ExportTests::test_export_with_cond_closure, test/dynamo/test_export.py::ExportTests::test_export_with_cond_dynamic_shape_pred, test/dynamo/test_export.py::ExportTests::test_export_with_cond_with_closed_function, test/dynamo/test_export.py::ExportTests::test_export_with_constant_dict_values, test/dynamo/test_export.py::ExportTests::test_export_with_constant_free_function, test/dynamo/test_export.py::ExportTests::test_export_with_constant_free_function_and_class_method, test/dynamo/test_export.py::ExportTests::test_export_with_constant_free_function_and_class_method_multiarg, test/dynamo/test_export.py::ExportTests::test_export_with_constant_free_function_and_class_method_multiarg_diff, test/dynamo/test_export.py::ExportTests::test_export_with_constant_global_function, test/dynamo/test_export.py::ExportTests::test_export_with_constant_in_unspecialized_nn_module, test/dynamo/test_export.py::ExportTests::test_export_with_constant_list_nonzero, test/dynamo/test_export.py::ExportTests::test_export_with_constant_list_nonzero_free_function, test/dynamo/test_export.py::ExportTests::test_export_with_constant_method_on_module, test/dynamo/test_export.py::ExportTests::test_export_with_constant_method_on_module_invoke_twice, test/dynamo/test_export.py::ExportTests::test_export_with_constant_none_control_flow, test/dynamo/test_export.py::ExportTests::test_export_with_constant_none_control_flow_free_func, test/dynamo/test_export.py::ExportTests::test_export_with_constant_not_none_control_flow, test/dynamo/test_export.py::ExportTests::test_export_with_constant_not_none_control_flow_free_func, test/dynamo/test_export.py::ExportTests::test_export_with_constant_not_none_control_flow_pos, test/dynamo/test_export.py::ExportTests::test_export_with_constant_not_return_const, test/dynamo/test_export.py::ExportTests::test_export_with_constant_tuple_nonzero, test/dynamo/test_export.py::ExportTests::test_export_with_functools_wrapped_fn, test/dynamo/test_export.py::ExportTests::test_export_with_functools_wrapped_method, test/dynamo/test_export.py::ExportTests::test_export_with_kwargs, test/dynamo/test_export.py::ExportTests::test_export_with_kwargs_and_empty_args, test/dynamo/test_export.py::ExportTests::test_export_with_kwargs_with_default_None, test/dynamo/test_export.py::ExportTests::test_export_with_kwargs_with_default_float, test/dynamo/test_export.py::ExportTests::test_export_with_kwargs_with_default_tensor, test/dynamo/test_export.py::ExportTests::test_export_with_kwargs_with_default_tuple, test/dynamo/test_export.py::ExportTests::test_export_with_map_cond, test/dynamo/test_export.py::ExportTests::test_export_with_map_zero_sized_tensor, test/dynamo/test_export.py::ExportTests::test_export_with_map_zero_sized_tensor_suppress_errors, test/dynamo/test_export.py::ExportTests::test_export_with_module_layer, test/dynamo/test_export.py::ExportTests::test_export_with_nonzero_static, test/dynamo/test_export.py::ExportTests::test_export_with_shallow_list_copy_with_side_effects, test/dynamo/test_export.py::ExportTests::test_export_with_shallow_list_copy_wo_side_effects, test/dynamo/test_export.py::ExportTests::test_export_with_stack_trace, test/dynamo/test_export.py::ExportTests::test_export_with_symbool_inputs, test/dynamo/test_export.py::ExportTests::test_export_with_wrapped_fn, test/dynamo/test_export.py::ExportTests::test_exported_graph_serialization, test/dynamo/test_export.py::ExportTests::test_func_return, test/dynamo/test_export.py::ExportTests::test_func_return_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_fx_pytree, test/dynamo/test_export.py::ExportTests::test_immutable_list_dict, test/dynamo/test_export.py::ExportTests::test_input_container_type, test/dynamo/test_export.py::ExportTests::test_invalid_input_global, test/dynamo/test_export.py::ExportTests::test_invalid_input_global_multiple_access, test/dynamo/test_export.py::ExportTests::test_invalid_input_nonlocal, test/dynamo/test_export.py::ExportTests::test_invalid_input_unused_nonlocal_ok, test/dynamo/test_export.py::ExportTests::test_list_contains, test/dynamo/test_export.py::ExportTests::test_list_not_contains, test/dynamo/test_export.py::ExportTests::test_list_unpack, test/dynamo/test_export.py::ExportTests::test_list_unpack_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_map_cond_param_buffer_lifted, test/dynamo/test_export.py::ExportTests::test_mixed_real_and_fake_inputs, test/dynamo/test_export.py::ExportTests::test_multiple_outputs_op_with_evaluator, test/dynamo/test_export.py::ExportTests::test_nested_cond_op_param_buffer_lifted, test/dynamo/test_export.py::ExportTests::test_no_tensor_computation, test/dynamo/test_export.py::ExportTests::test_no_tensor_computation_2, test/dynamo/test_export.py::ExportTests::test_no_tensor_computation_2_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_no_tensor_computation_fail, test/dynamo/test_export.py::ExportTests::test_not_functionalize, test/dynamo/test_export.py::ExportTests::test_param_buffer_safe_from_mutation_recurse, test/dynamo/test_export.py::ExportTests::test_param_buffer_safe_from_mutation_simple, test/dynamo/test_export.py::ExportTests::test_pre_dispatch_simple, test/dynamo/test_export.py::ExportTests::test_predispatch_with_for_out_dtype, test/dynamo/test_export.py::ExportTests::test_predispatch_with_for_out_dtype_nested, test/dynamo/test_export.py::ExportTests::test_predispatch_with_higher_order, test/dynamo/test_export.py::ExportTests::test_predispatch_with_higher_order_nested, test/dynamo/test_export.py::ExportTests::test_preserve_fx_node_metadata, test/dynamo/test_export.py::ExportTests::test_preserve_fx_node_metadata_graph_break, test/dynamo/test_export.py::ExportTests::test_preserve_fx_node_metadata_inline, test/dynamo/test_export.py::ExportTests::test_preserve_fx_node_metadata_recompile, test/dynamo/test_export.py::ExportTests::test_remove_redundant_dynamic_dim_in_error_message, test/dynamo/test_export.py::ExportTests::test_retracibility, test/dynamo/test_export.py::ExportTests::test_retracibility_dict_container_inp_out, test/dynamo/test_export.py::ExportTests::test_retracibility_nested_list_out, test/dynamo/test_export.py::ExportTests::test_round_dynamic_shapes, test/dynamo/test_export.py::ExportTests::test_strict_fake_tensor_prop_real_tensors, test/dynamo/test_export.py::ExportTests::test_subclass_parameters, test/dynamo/test_export.py::ExportTests::test_sum_param, test/dynamo/test_export.py::ExportTests::test_sym_contains, test/dynamo/test_export.py::ExportTests::test_symbolic_tracing_within_fake_mode_with_constraints, test/dynamo/test_export.py::ExportTests::test_symbolic_tracing_within_fake_mode_with_constraints_with_parameters, test/dynamo/test_export.py::ExportTests::test_symbool, test/dynamo/test_export.py::ExportTests::test_torch_inference_mode_ctx, test/dynamo/test_export.py::ExportTests::test_trivial_constraint, test/dynamo/test_export.py::ExportTests::test_uncaptured_higher_order_op_error_not_suppresed, test/dynamo/test_export.py::ExportTests::test_untracked_inputs_in_constraints, test/dynamo/test_export.py::ExportTests::test_zeroes_in_and_out_different_shape_on_test, test/dynamo/test_export.py::ExportTests::test_zeroes_in_and_out_different_shape_on_test_with_aten_graph, test/dynamo/test_export.py::ExportTests::test_zeroes_in_new_shape_scalar_out, test/dynamo/test_export.py::ExportTests::test_zeroes_in_new_shape_scalar_out_permute, test/dynamo/test_export.py::ExportTests::test_zeroes_in_new_shape_scalar_out_permute_dupe_and_bypass 2025-08-26T20:52:53.9809981Z 2025-08-26T20:52:56.6745182Z 2025-08-26T20:52:56.6746025Z dynamo/test_hooks 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_hooks_1.1_bcd27dc2de4fc5bd_.log 2025-08-26T20:52:56.6758242Z Running 34 items in this shard: test/dynamo/test_hooks.py::HooksTests::test_complex_state_mutation_in_intermediary_hooks_same_on_inductor, test/dynamo/test_hooks.py::HooksTests::test_complex_state_mutation_in_intermediary_hooks_same_on_inductor_with_graph_break, test/dynamo/test_hooks.py::HooksTests::test_functools_arg_vary, test/dynamo/test_hooks.py::HooksTests::test_global_module_forward_pre_hook, test/dynamo/test_hooks.py::HooksTests::test_hook_with_closure, test/dynamo/test_hooks.py::HooksTests::test_hook_with_nested_closure, test/dynamo/test_hooks.py::HooksTests::test_input_hooks_same, test/dynamo/test_hooks.py::HooksTests::test_intermediary_hooks, test/dynamo/test_hooks.py::HooksTests::test_intermediary_hooks_same_on_aot_eager, test/dynamo/test_hooks.py::HooksTests::test_intermediary_hooks_same_on_inductor, test/dynamo/test_hooks.py::HooksTests::test_intermediate_hook_with_closure_aot, test/dynamo/test_hooks.py::HooksTests::test_intermediate_hook_with_closure_eager, test/dynamo/test_hooks.py::HooksTests::test_nnmodule_hook_guards, test/dynamo/test_hooks.py::HooksTests::test_no_recompile_on_hook_identity_change, test/dynamo/test_hooks.py::HooksTests::test_no_recompile_on_same_hook, test/dynamo/test_hooks.py::HooksTests::test_post_acc_grad_hook, test/dynamo/test_hooks.py::HooksTests::test_recompile, test/dynamo/test_hooks.py::HooksTests::test_register_hook_partial_guarding, test/dynamo/test_hooks.py::HooksTests::test_removed_handle_return, test/dynamo/test_hooks.py::HooksTests::test_tensor_only_register_hook_in_graph_lambda, test/dynamo/test_hooks.py::HooksTests::test_tensor_only_register_hook_in_graph_local, test/dynamo/test_hooks.py::HooksTests::test_tensor_only_register_hook_in_graph_local_inner, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_global_hook, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_global_hooks_handles_in_list, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_hook_in_graph_break_handle_lambda, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_hook_in_graph_break_handle_local, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_hook_in_graph_lambda, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_hook_in_graph_local, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_hook_multi_handle_return, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_hook_repeated_handle_not_local, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_hook_repeated_handle_return, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_multiple_hooks, test/dynamo/test_hooks.py::HooksTests::test_tensor_register_multiple_hooks_handles_in_list, test/dynamo/test_hooks.py::HooksTests::test_wrap_top_frame_with_hooks 2025-08-26T20:52:56.6769979Z 2025-08-26T20:52:57.2843401Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:52:57.2845012Z import pkg_resources 2025-08-26T20:52:57.4112916Z Running dynamo/test_generator 1/1 ... [2025-08-26 20:52:57.411000] 2025-08-26T20:52:57.4113390Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:52:57.4115750Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_generator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:52:57.411343] 2025-08-26T20:52:59.9064039Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:52:59.9065655Z import pkg_resources 2025-08-26T20:53:00.0296897Z Running dynamo/test_reorder_logs 1/1 ... [2025-08-26 20:53:00.029397] 2025-08-26T20:53:00.0297410Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:00.0300227Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_reorder_logs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:00.029753] 2025-08-26T20:53:04.6370983Z 2025-08-26T20:53:04.6372272Z dynamo/test_generator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_generator_1.1_6d905016f5ec6e62_.log 2025-08-26T20:53:04.6401063Z Running 78 items in this shard: test/dynamo/test_generator.py::GeneratorTests::test_cleanup_throw, test/dynamo/test_generator.py::GeneratorTests::test_deque_extendleft, test/dynamo/test_generator.py::GeneratorTests::test_dict_tuple_list_generator_container0, test/dynamo/test_generator.py::GeneratorTests::test_dict_tuple_list_generator_container1, test/dynamo/test_generator.py::GeneratorTests::test_dict_tuple_list_generator_container2, test/dynamo/test_generator.py::GeneratorTests::test_dict_tuple_list_generator_container3, test/dynamo/test_generator.py::GeneratorTests::test_dynamo_disable_generator, test/dynamo/test_generator.py::GeneratorTests::test_dynamo_disable_sub_generator, test/dynamo/test_generator.py::GeneratorTests::test_generator___contains__, test/dynamo/test_generator.py::GeneratorTests::test_generator___contains___side_effects, test/dynamo/test_generator.py::GeneratorTests::test_generator_as_argument, test/dynamo/test_generator.py::GeneratorTests::test_generator_as_argument_2, test/dynamo/test_generator.py::GeneratorTests::test_generator_as_argument_3, test/dynamo/test_generator.py::GeneratorTests::test_generator_as_argument_4, test/dynamo/test_generator.py::GeneratorTests::test_generator_simple, test/dynamo/test_generator.py::GeneratorTests::test_generator_with_side_effects, test/dynamo/test_generator.py::GeneratorTests::test_generator_with_side_effects_graph_break, test/dynamo/test_generator.py::GeneratorTests::test_generator_with_side_effects_graph_break_2, test/dynamo/test_generator.py::GeneratorTests::test_graph_break_and_reconstruct_generator, test/dynamo/test_generator.py::GeneratorTests::test_graph_break_before_calling_generator, test/dynamo/test_generator.py::GeneratorTests::test_graph_break_in_generator, test/dynamo/test_generator.py::GeneratorTests::test_graph_break_in_generator_2, test/dynamo/test_generator.py::GeneratorTests::test_graph_break_in_generator_while_reconstructing, test/dynamo/test_generator.py::GeneratorTests::test_graph_break_outside_generator, test/dynamo/test_generator.py::GeneratorTests::test_infinite_generator, test/dynamo/test_generator.py::GeneratorTests::test_infinite_generator_2, test/dynamo/test_generator.py::GeneratorTests::test_infinite_generator_3, test/dynamo/test_generator.py::GeneratorTests::test_islice_chain, test/dynamo/test_generator.py::GeneratorTests::test_iter, test/dynamo/test_generator.py::GeneratorTests::test_list_extend, test/dynamo/test_generator.py::GeneratorTests::test_list_zip_generator, test/dynamo/test_generator.py::GeneratorTests::test_reconstruct_generator_tensor_mutation, test/dynamo/test_generator.py::GeneratorTests::test_reconstruct_generator_with_dict_mutation, test/dynamo/test_generator.py::GeneratorTests::test_reconstruct_generator_with_dict_mutation_before, test/dynamo/test_generator.py::GeneratorTests::test_reconstruct_generator_with_local_var_mutation, test/dynamo/test_generator.py::GeneratorTests::test_reconstruct_generator_with_object_mutation, test/dynamo/test_generator.py::GeneratorTests::test_reconstruct_generator_with_object_mutation_before, test/dynamo/test_generator.py::GeneratorTests::test_return_advanced_generator, test/dynamo/test_generator.py::GeneratorTests::test_return_exhaust_generator, test/dynamo/test_generator.py::GeneratorTests::test_return_generator, test/dynamo/test_generator.py::GeneratorTests::test_return_subgenerator, test/dynamo/test_generator.py::GeneratorTests::test_return_tuple_generator, test/dynamo/test_generator.py::GeneratorTests::test_subgenerator, test/dynamo/test_generator.py::GeneratorTests::test_subgenerator_with_side_effects, test/dynamo/test_generator.py::GeneratorTests::test_zip_generator, test/dynamo/test_generator.py::GeneratorTests::test_zip_generator_2, test/dynamo/test_generator.py::GeneratorTests::test_zip_infinite_generator, test/dynamo/test_generator.py::GeneratorTests::test_zip_subgenerator, test/dynamo/test_generator.py::TestGeneratorSend::test_send, test/dynamo/test_generator.py::TestGeneratorSend::test_send_stop_iteration_fullgraph_False, test/dynamo/test_generator.py::TestGeneratorSend::test_send_stop_iteration_fullgraph_True, test/dynamo/test_generator.py::TestGeneratorClose::test_close, test/dynamo/test_generator.py::TestGeneratorClose::test_close_after_close, test/dynamo/test_generator.py::TestGeneratorClose::test_close_after_exception, test/dynamo/test_generator.py::TestGeneratorClose::test_close_capture_GeneratorExit_fullgraph_False, test/dynamo/test_generator.py::TestGeneratorClose::test_close_capture_GeneratorExit_fullgraph_True, test/dynamo/test_generator.py::TestGeneratorClose::test_close_capture_GeneratorExit_return, test/dynamo/test_generator.py::TestGeneratorClose::test_close_capture_and_reraise_GeneratorExit, test/dynamo/test_generator.py::TestGeneratorClose::test_close_capture_and_reraise_exc_exc0, test/dynamo/test_generator.py::TestGeneratorClose::test_close_capture_and_reraise_exc_exc1, test/dynamo/test_generator.py::TestGeneratorClose::test_close_handling_finally, test/dynamo/test_generator.py::TestGeneratorClose::test_close_subgen, test/dynamo/test_generator.py::TestGeneratorClose::test_close_with_side_effects, test/dynamo/test_generator.py::TestGeneratorClose::test_close_with_subgen, test/dynamo/test_generator.py::TestGeneratorClose::test_next_after_close_fullgraph_False, test/dynamo/test_generator.py::TestGeneratorClose::test_next_after_close_fullgraph_True, test/dynamo/test_generator.py::TestGeneratorThrow::test_exception_context_with_yield, test/dynamo/test_generator.py::TestGeneratorThrow::test_return_None_in_except_and_finally, test/dynamo/test_generator.py::TestGeneratorThrow::test_return_const_value_in_except_and_finally, test/dynamo/test_generator.py::TestGeneratorThrow::test_return_value_in_except_and_finally, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw_no_yield_after_throw, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw_not_catch, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw_raise_difference_exc, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw_try_except_finally, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw_with_finally, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw_without_finally, test/dynamo/test_generator.py::TestGeneratorThrow::test_throw_yield_finally 2025-08-26T20:53:04.6429077Z 2025-08-26T20:53:05.1011832Z 2025-08-26T20:53:05.1012824Z dynamo/test_reorder_logs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_reorder_logs_1.1_3da3e3c7d302d6b1_.log 2025-08-26T20:53:05.1019497Z Running 14 items in this shard: test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method0_fn0_should_ignore_logger_False, test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method1_fn1_should_ignore_logger_False, test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method2_fn2_should_ignore_logger_False, test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method3_fn3_should_ignore_logger_False, test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method4_fn4_should_ignore_logger_True, test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method5_fn5_should_ignore_logger_True, test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method6_fn6_should_ignore_logger_True, test/dynamo/test_reorder_logs.py::IgnoreLogsTests::test_ignore_logger_ignore_method7_fn7_should_ignore_logger_True, test/dynamo/test_reorder_logs.py::ReorderLogsTests::test_constant_mutation, test/dynamo/test_reorder_logs.py::ReorderLogsTests::test_dont_reorder_print, test/dynamo/test_reorder_logs.py::ReorderLogsTests::test_reorder_custom_log_fn, test/dynamo/test_reorder_logs.py::ReorderLogsTests::test_reorder_print, test/dynamo/test_reorder_logs.py::ReorderLogsTests::test_reorder_print_graph_break, test/dynamo/test_reorder_logs.py::ReorderLogsTests::test_reorder_warnings 2025-08-26T20:53:05.1025954Z 2025-08-26T20:53:07.9201314Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:07.9203259Z import pkg_resources 2025-08-26T20:53:08.0442982Z Running export/test_verifier 1/1 ... [2025-08-26 20:53:08.044004] 2025-08-26T20:53:08.0443435Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:08.0445776Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_verifier.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:08.044321] 2025-08-26T20:53:08.2780915Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:08.2782512Z import pkg_resources 2025-08-26T20:53:08.4311712Z Running export/test_sparse 1/1 ... [2025-08-26 20:53:08.430749] 2025-08-26T20:53:08.4312553Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:08.4372786Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'export/test_sparse.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:08.436862] 2025-08-26T20:53:12.1144087Z 2025-08-26T20:53:12.1145067Z export/test_sparse 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_sparse_1.1_140a24a0a893c298_.log 2025-08-26T20:53:12.1218973Z Running 203 items in this shard: test/export/test_sparse.py::TestSparseProp::test_activation_coo, test/export/test_sparse.py::TestSparseProp::test_activation_csr, test/export/test_sparse.py::TestSparseProp::test_add, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_bfloat16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float32_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_float64_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_eltwisenet_int64_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_bfloat16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float32_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_float64_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_idnet_int64_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_bfloat16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float32_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_float64_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_sumnet_int64_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_bfloat16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float16_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float32_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_float64_int64_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int32_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int32_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int32_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int32_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int32_SparseCSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int64_SparseBSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int64_SparseBSR, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int64_SparseCOO, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int64_SparseCSC, test/export/test_sparse.py::TestSparseProp::test_todensenet_int64_int64_SparseCSR 2025-08-26T20:53:12.1291526Z 2025-08-26T20:53:15.3641851Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:15.3643454Z import pkg_resources 2025-08-26T20:53:15.4886026Z Running dynamo/test_comptime 1/1 ... [2025-08-26 20:53:15.488335] 2025-08-26T20:53:15.4886491Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:15.4889162Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_comptime.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:15.488664] 2025-08-26T20:53:18.7733688Z 2025-08-26T20:53:18.7734684Z export/test_verifier 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_verifier_1.1_8a575d8ce691e247_.log 2025-08-26T20:53:18.7738797Z Running 10 items in this shard: test/export/test_verifier.py::TestVerifier::test_ep_verifier_basic, test/export/test_verifier.py::TestVerifier::test_ep_verifier_buffer_mutate, test/export/test_verifier.py::TestVerifier::test_ep_verifier_invalid_buffer, test/export/test_verifier.py::TestVerifier::test_ep_verifier_invalid_output, test/export/test_verifier.py::TestVerifier::test_ep_verifier_invalid_param, test/export/test_verifier.py::TestVerifier::test_verifier_basic, test/export/test_verifier.py::TestVerifier::test_verifier_call_module, test/export/test_verifier.py::TestVerifier::test_verifier_higher_order, test/export/test_verifier.py::TestVerifier::test_verifier_nested_invalid_module, test/export/test_verifier.py::TestVerifier::test_verifier_no_functional 2025-08-26T20:53:18.7742128Z 2025-08-26T20:53:21.9968503Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:21.9970301Z import pkg_resources 2025-08-26T20:53:22.1219648Z Running dynamo/test_python_autograd 1/1 ... [2025-08-26 20:53:22.121668] 2025-08-26T20:53:22.1220170Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:22.1223020Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'dynamo/test_python_autograd.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:22.122026] 2025-08-26T20:53:26.3417372Z 2025-08-26T20:53:26.3418381Z dynamo/test_python_autograd 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_python_autograd_1.1_3ef33c202e7aacad_.log 2025-08-26T20:53:26.3421054Z Running 5 items in this shard: test/dynamo/test_python_autograd.py::TestPythonAutograd::test_backwards1, test/dynamo/test_python_autograd.py::TestPythonAutograd::test_backwards2, test/dynamo/test_python_autograd.py::TestPythonAutograd::test_forwards1, test/dynamo/test_python_autograd.py::TestPythonAutograd::test_forwards2, test/dynamo/test_python_autograd.py::TestPythonAutograd::test_split 2025-08-26T20:53:26.3422870Z 2025-08-26T20:53:28.1707237Z 2025-08-26T20:53:28.1708205Z dynamo/test_comptime 1/1 was successful, full logs can be found in artifacts with path test/test-reports/dynamo.test_comptime_1.1_d5b5c66a2562a10f_.log 2025-08-26T20:53:28.1712319Z Running 12 items in this shard: test/dynamo/test_comptime.py::ComptimeTests::test_get_local, test/dynamo/test_comptime.py::ComptimeTests::test_get_local_closure_variable, test/dynamo/test_comptime.py::ComptimeTests::test_graph_break, test/dynamo/test_comptime.py::ComptimeTests::test_print_bt, test/dynamo/test_comptime.py::ComptimeTests::test_print_direct, test/dynamo/test_comptime.py::ComptimeTests::test_print_disas, test/dynamo/test_comptime.py::ComptimeTests::test_print_graph, test/dynamo/test_comptime.py::ComptimeTests::test_print_guards, test/dynamo/test_comptime.py::ComptimeTests::test_print_locals, test/dynamo/test_comptime.py::ComptimeTests::test_print_single, test/dynamo/test_comptime.py::ComptimeTests::test_print_value_stack, test/dynamo/test_comptime.py::ComptimeTests::test_sleep 2025-08-26T20:53:28.1716603Z 2025-08-26T20:53:29.5637027Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:29.5638748Z import pkg_resources 2025-08-26T20:53:29.6869891Z Running test_ao_sparsity 1/1 ... [2025-08-26 20:53:29.686689] 2025-08-26T20:53:29.6870343Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:29.6873461Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ao_sparsity.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:29.687074] 2025-08-26T20:53:31.3584635Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:31.3586244Z import pkg_resources 2025-08-26T20:53:31.4813144Z Running test_package 1/1 ... [2025-08-26 20:53:31.481059] 2025-08-26T20:53:31.4813559Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:31.4816226Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_package.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:31.481396] 2025-08-26T20:53:37.0533118Z 2025-08-26T20:53:37.0534528Z test_package 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_package_1.1_5f27f6ddcdb41263_.log 2025-08-26T20:53:37.0601811Z Running 137 items in this shard: test/test_package.py::TestAnalyze::test_trace_dependencies, test/test_package.py::TestDependencyAPI::test_allow_empty_with_error, test/test_package.py::TestDependencyAPI::test_broken_dependency, test/test_package.py::TestDependencyAPI::test_deny, test/test_package.py::TestDependencyAPI::test_deny_glob, test/test_package.py::TestDependencyAPI::test_extern, test/test_package.py::TestDependencyAPI::test_extern_glob, test/test_package.py::TestDependencyAPI::test_extern_glob_allow_empty, test/test_package.py::TestDependencyAPI::test_externing_c_extension, test/test_package.py::TestDependencyAPI::test_implicit_intern, test/test_package.py::TestDependencyAPI::test_intern_error, test/test_package.py::TestDependencyAPI::test_invalid_import, test/test_package.py::TestDependencyAPI::test_mock, test/test_package.py::TestDependencyAPI::test_mock_glob, test/test_package.py::TestDependencyAPI::test_mock_glob_allow_empty, test/test_package.py::TestDependencyAPI::test_pickle_mocked, test/test_package.py::TestDependencyAPI::test_pickle_mocked_all, test/test_package.py::TestDependencyAPI::test_repackage_mocked_module, test/test_package.py::TestDependencyHooks::test_extern_and_mock_hook, test/test_package.py::TestDependencyHooks::test_multiple_extern_hooks, test/test_package.py::TestDependencyHooks::test_multiple_mock_hooks, test/test_package.py::TestDependencyHooks::test_remove_hooks, test/test_package.py::TestDependencyHooks::test_single_hook, test/test_package.py::TestDiGraph::test_all_paths, test/test_package.py::TestDiGraph::test_contains, test/test_package.py::TestDiGraph::test_contains_non_hashable, test/test_package.py::TestDiGraph::test_edges, test/test_package.py::TestDiGraph::test_forward_closure, test/test_package.py::TestDiGraph::test_iter, test/test_package.py::TestDiGraph::test_node_attr_update, test/test_package.py::TestDiGraph::test_node_attrs, test/test_package.py::TestDiGraph::test_predecessor_not_in_graph, test/test_package.py::TestDiGraph::test_predecessors, test/test_package.py::TestDiGraph::test_successor_not_in_graph, test/test_package.py::TestDiGraph::test_successors, test/test_package.py::DirectoryReaderTest::test_importer_access, test/test_package.py::DirectoryReaderTest::test_loading_has_record, test/test_package.py::DirectoryReaderTest::test_loading_module, test/test_package.py::DirectoryReaderTest::test_loading_pickle, test/test_package.py::DirectoryReaderTest::test_package_resource_access, test/test_package.py::DirectoryReaderTest::test_resource_access_by_path, test/test_package.py::DirectoryReaderTest::test_resource_reader, test/test_package.py::DirectoryReaderTest::test_scriptobject_failure_message, test/test_package.py::TestGlobGroup::test_exclude, test/test_package.py::TestGlobGroup::test_exclude_from_all, test/test_package.py::TestGlobGroup::test_invalid_raw, test/test_package.py::TestGlobGroup::test_list_include_exclude, test/test_package.py::TestGlobGroup::test_one_star, test/test_package.py::TestGlobGroup::test_one_star_middle, test/test_package.py::TestGlobGroup::test_one_star_multiple_in_component, test/test_package.py::TestGlobGroup::test_one_star_partial, test/test_package.py::TestGlobGroup::test_one_star_partial_extension, test/test_package.py::TestGlobGroup::test_raw_two_star, test/test_package.py::TestGlobGroup::test_two_star, test/test_package.py::TestGlobGroup::test_two_star_end, test/test_package.py::TestGlobGroup::test_two_star_middle, test/test_package.py::TestGlobGroup::test_two_star_multiple, test/test_package.py::TestImporter::test_ordered_importer_basic, test/test_package.py::TestImporter::test_ordered_importer_whichmodule, test/test_package.py::TestImporter::test_package_importer_whichmodule_no_dunder_module, test/test_package.py::TestImporter::test_single_ordered_importer, test/test_package.py::TestImporter::test_sys_importer, test/test_package.py::TestImporter::test_sys_importer_roundtrip, test/test_package.py::TestLoadBCPackages::test_load_bc_packages_fx_module, test/test_package.py::TestLoadBCPackages::test_load_bc_packages_nn_module, test/test_package.py::TestLoadBCPackages::test_load_bc_packages_torchscript_module, test/test_package.py::TestMangling::test_demangle_base, test/test_package.py::TestMangling::test_demangler_multiple_manglers, test/test_package.py::TestMangling::test_is_mangled, test/test_package.py::TestMangling::test_mangle_empty_errors, test/test_package.py::TestMangling::test_mangle_prefix, test/test_package.py::TestMangling::test_mangler_is_consistent, test/test_package.py::TestMangling::test_package_mangler, test/test_package.py::TestMangling::test_roundtrip_mangling, test/test_package.py::TestMangling::test_unique_manglers, test/test_package.py::TestMangling::test_unique_module_names, test/test_package.py::TestMisc::test_dunder_package_present, test/test_package.py::TestMisc::test_dunder_package_works_from_package, test/test_package.py::TestMisc::test_exporter_content_lists, test/test_package.py::TestMisc::test_file_structure, test/test_package.py::TestMisc::test_file_structure_has_file, test/test_package.py::TestMisc::test_inspect_class, test/test_package.py::TestMisc::test_is_from_package, test/test_package.py::TestMisc::test_load_python_version_from_package, test/test_package.py::TestMisc::test_loaders_that_remap_files_work_ok, test/test_package.py::TestMisc::test_python_version, test/test_package.py::TestMisc::test_std_lib_sys_hackery_checks, test/test_package.py::ModelTest::test_model_save, test/test_package.py::ModelTest::test_resnet, test/test_package.py::ModelTest::test_script_resnet, test/test_package.py::TestPackageFX::test_package_fx_custom_tracer, test/test_package.py::TestPackageFX::test_package_fx_package, test/test_package.py::TestPackageFX::test_package_fx_simple, test/test_package.py::TestPackageFX::test_package_fx_with_imports, test/test_package.py::TestPackageFX::test_package_fx_wrap, test/test_package.py::TestPackageFX::test_package_gm_preserve_stack_trace, test/test_package.py::TestPackageFX::test_package_then_fx, test/test_package.py::TestPackageScript::test_different_package_interface, test/test_package.py::TestPackageScript::test_different_package_script_class, test/test_package.py::TestPackageScript::test_load_shared_scriptmodules, test/test_package.py::TestPackageScript::test_load_shared_tensors, test/test_package.py::TestPackageScript::test_load_shared_tensors_repackaged, test/test_package.py::TestPackageScript::test_mixing_packaged_and_inline_modules, test/test_package.py::TestPackageScript::test_mixing_packaged_and_inline_modules_shared_code, test/test_package.py::TestPackageScript::test_package_interface, test/test_package.py::TestPackageScript::test_package_script_class, test/test_package.py::TestPackageScript::test_package_script_class_referencing_self, test/test_package.py::TestPackageScript::test_save_eager_mods_sharing_scriptmodule, test/test_package.py::TestPackageScript::test_save_independent_scriptmodules, test/test_package.py::TestPackageScript::test_save_repeat_scriptmodules, test/test_package.py::TestPackageScript::test_save_scriptmodule, test/test_package.py::TestPackageScript::test_save_scriptmodule_file, test/test_package.py::TestPackageScript::test_save_scriptmodule_only_necessary_code, test/test_package.py::TestPackageScript::test_save_scriptmodule_with_submods, test/test_package.py::TestPackageScript::test_save_scriptmodules_in_container, test/test_package.py::TestPackageScript::test_save_scriptmodules_submod_redefinition, test/test_package.py::TestPackageScript::test_save_shared_tensors, test/test_package.py::TestPackageScript::test_saving_and_scripting_packaged_mod, test/test_package.py::TestPackageScript::test_scriptmodules_repeat_save, test/test_package.py::TestPackageScript::test_tensor_sharing_pickle, test/test_package.py::TestRepackage::test_repackage_import_indirectly_via_parent_module, test/test_package.py::TestResources::test_importer_access, test/test_package.py::TestResources::test_package_resource_access, test/test_package.py::TestResources::test_resource_access_by_path, test/test_package.py::TestResources::test_resource_reader, test/test_package.py::TestSaveLoad::test_bad_dunder_imports, test/test_package.py::TestSaveLoad::test_dunder_imports, test/test_package.py::TestSaveLoad::test_exporting_mismatched_code, test/test_package.py::TestSaveLoad::test_pickle, test/test_package.py::TestSaveLoad::test_pickle_long_name_with_protocol_4, test/test_package.py::TestSaveLoad::test_save_imported_module, test/test_package.py::TestSaveLoad::test_save_imported_module_using_package_importer, test/test_package.py::TestSaveLoad::test_save_load_fp8, test/test_package.py::TestSaveLoad::test_save_module, test/test_package.py::TestSaveLoad::test_save_module_binary, test/test_package.py::TestSaveLoad::test_saving_source, test/test_package.py::TestSaveLoad::test_saving_string 2025-08-26T20:53:37.0667846Z 2025-08-26T20:53:39.7654874Z 2025-08-26T20:53:39.7656337Z test_ao_sparsity 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_ao_sparsity_1.1_91524bf9e0805e4f_.log 2025-08-26T20:53:39.7708505Z Running 88 items in this shard: test/test_ao_sparsity.py::TestQuantizedSparseKernels::test_sparse_qlinear, test/test_ao_sparsity.py::TestQuantizedSparseLayers::test_sparse_qlinear, test/test_ao_sparsity.py::TestQuantizedSparseLayers::test_sparse_qlinear_serdes, test/test_ao_sparsity.py::TestFakeSparsity::test_jit_trace, test/test_ao_sparsity.py::TestFakeSparsity::test_masking_logic, test/test_ao_sparsity.py::TestFakeSparsity::test_state_dict_preserved, test/test_ao_sparsity.py::TestFakeSparsity::test_weights_parametrized, test/test_ao_sparsity.py::TestCubicScheduler::test_constructor, test/test_ao_sparsity.py::TestCubicScheduler::test_step, test/test_ao_sparsity.py::TestScheduler::test_constructor, test/test_ao_sparsity.py::TestScheduler::test_lambda_scheduler, test/test_ao_sparsity.py::TestScheduler::test_order_of_steps, test/test_ao_sparsity.py::TestScheduler::test_step, test/test_ao_sparsity.py::TestBaseSparsifier::test_constructor, test/test_ao_sparsity.py::TestBaseSparsifier::test_convert, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash_with_params1, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash_with_params2, test/test_ao_sparsity.py::TestBaseSparsifier::test_mask_squash_with_params3, test/test_ao_sparsity.py::TestBaseSparsifier::test_prepare_config, test/test_ao_sparsity.py::TestBaseSparsifier::test_state_dict, test/test_ao_sparsity.py::TestBaseSparsifier::test_step, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_constructor, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_mask_squash, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_prepare, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_sparsity_levels, test/test_ao_sparsity.py::TestNearlyDiagonalSparsifier::test_step, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_constructor, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_mask_squash, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_prepare, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_sparsity_levels, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_step, test/test_ao_sparsity.py::TestWeightNormSparsifier::test_step_2_of_4, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_complex_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_constructor, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prepare_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prepare_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_activation_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_bias_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_padding_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_conv2d_pool_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_linear_activation_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_linear_bias_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_linear_linear, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_layernorm_linear_multiple_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_layernorm_linear_single_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_linear_multiple_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_prune_lstm_linear_single_layer, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_step_conv2d, test/test_ao_sparsity.py::TestBaseStructuredSparsifier::test_step_linear, test/test_ao_sparsity.py::TestFPGMPruner::test_compute_distance, test/test_ao_sparsity.py::TestFPGMPruner::test_update_mask, test/test_ao_sparsity.py::TestSaliencyPruner::test_lstm_saliency_pruner_update_mask, test/test_ao_sparsity.py::TestSaliencyPruner::test_saliency_pruner_update_mask, test/test_ao_sparsity.py::TestComposability::test_convert_without_squash_mask, test/test_ao_sparsity.py::TestComposability::test_fusion_before_s_prep, test/test_ao_sparsity.py::TestComposability::test_q_prep_before_s_prep, test/test_ao_sparsity.py::TestComposability::test_qat_prep_before_s_prep, test/test_ao_sparsity.py::TestComposability::test_s_prep_before_fusion, test/test_ao_sparsity.py::TestComposability::test_s_prep_before_q_prep, test/test_ao_sparsity.py::TestComposability::test_s_prep_before_qat_prep, test/test_ao_sparsity.py::TestFxComposability::test_q_prep_fx_before_s_prep, test/test_ao_sparsity.py::TestFxComposability::test_q_prep_fx_s_prep_ref_conv, test/test_ao_sparsity.py::TestFxComposability::test_s_prep_before_q_prep_fx, test/test_ao_sparsity.py::TestFxComposability::test_s_prep_before_qat_prep_fx, test/test_ao_sparsity.py::TestFxComposability::test_s_prep_q_prep_fx_ref, test/test_ao_sparsity.py::TestActivationSparsifier::test_activation_sparsifier, test/test_ao_sparsity.py::TestBaseDataScheduler::test_constructor, test/test_ao_sparsity.py::TestBaseDataScheduler::test_order_of_steps, test/test_ao_sparsity.py::TestBaseDataScheduler::test_state_dict, test/test_ao_sparsity.py::TestBaseDataScheduler::test_step, test/test_ao_sparsity.py::TestBaseDataSparsifier::test_nn_embeddings, test/test_ao_sparsity.py::TestBaseDataSparsifier::test_nn_parameters, test/test_ao_sparsity.py::TestBaseDataSparsifier::test_tensors, test/test_ao_sparsity.py::TestNormDataSparsifiers::test_nn_embeddings, test/test_ao_sparsity.py::TestNormDataSparsifiers::test_nn_parameters, test/test_ao_sparsity.py::TestNormDataSparsifiers::test_tensors, test/test_ao_sparsity.py::TestQuantizationUtils::test_ptq_quantize_first, test/test_ao_sparsity.py::TestQuantizationUtils::test_ptq_sparsify_first, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_fqn_to_module, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_fqn_to_module_fail, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_fqn_to_module_for_tensors, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_get_arg_info_from_tensor_fqn, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_get_arg_info_from_tensor_fqn_fail, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_module_to_fqn, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_module_to_fqn_fail, test/test_ao_sparsity.py::TestSparsityUtilFunctions::test_module_to_fqn_root 2025-08-26T20:53:39.7755268Z 2025-08-26T20:53:40.4949887Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:40.4951721Z import pkg_resources 2025-08-26T20:53:40.6180789Z Running profiler/test_kineto 1/1 ... [2025-08-26 20:53:40.617806] 2025-08-26T20:53:40.6181232Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:40.6183900Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_kineto.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:40.618133] 2025-08-26T20:53:42.9262721Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:42.9265751Z import pkg_resources 2025-08-26T20:53:43.0502375Z Running higher_order_ops/test_invoke_subgraph 1/1 ... [2025-08-26 20:53:43.049765] 2025-08-26T20:53:43.0503442Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:43.0505704Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'higher_order_ops/test_invoke_subgraph.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:43.050140] 2025-08-26T20:53:43.9868996Z 2025-08-26T20:53:43.9870052Z profiler/test_kineto 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_kineto_1.1_67664a3bfbde7617_.log 2025-08-26T20:53:43.9871335Z Running 1 items in this shard: test/profiler/test_kineto.py::SimpleKinetoInitializationTest::test_kineto_profiler_with_environment_variable 2025-08-26T20:53:43.9872033Z 2025-08-26T20:53:47.1533843Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:47.1535399Z import pkg_resources 2025-08-26T20:53:47.2769174Z Running test_comparison_utils 1/1 ... [2025-08-26 20:53:47.276588] 2025-08-26T20:53:47.2769825Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:47.2771620Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_comparison_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:47.276925] 2025-08-26T20:53:50.8478509Z 2025-08-26T20:53:50.8480248Z test_comparison_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_comparison_utils_1.1_1137bd0bda20ffed_.log 2025-08-26T20:53:50.8485492Z Running 7 items in this shard: test/test_comparison_utils.py::TestComparisonUtils::test_all_equal_no_assert, test/test_comparison_utils.py::TestComparisonUtils::test_all_equal_no_assert_nones, test/test_comparison_utils.py::TestComparisonUtils::test_assert_device, test/test_comparison_utils.py::TestComparisonUtils::test_assert_dtype, test/test_comparison_utils.py::TestComparisonUtils::test_assert_layout, test/test_comparison_utils.py::TestComparisonUtils::test_assert_sizes, test/test_comparison_utils.py::TestComparisonUtils::test_assert_strides 2025-08-26T20:53:50.8490081Z 2025-08-26T20:53:54.3867303Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:53:54.3870581Z import pkg_resources 2025-08-26T20:53:54.5114694Z Running functorch/test_ac_logging 1/1 ... [2025-08-26 20:53:54.511056] 2025-08-26T20:53:54.5115620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:53:54.5117989Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ac_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:53:54.511390] 2025-08-26T20:53:57.9803756Z 2025-08-26T20:53:57.9805141Z functorch/test_ac_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ac_logging_1.1_b7b03853bd67f268_.log 2025-08-26T20:53:57.9809640Z Running 4 items in this shard: test/functorch/test_ac_logging.py::TestAcLogging::test_create_activation_checkpointing_logging_structure_payload, test/functorch/test_ac_logging.py::TestAcLogging::test_create_joint_graph_edges, test/functorch/test_ac_logging.py::TestAcLogging::test_create_joint_graph_node_information, test/functorch/test_ac_logging.py::TestAcLogging::test_create_structured_trace_for_min_cut_info 2025-08-26T20:53:57.9812779Z 2025-08-26T20:54:01.2601553Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:54:01.2603157Z import pkg_resources 2025-08-26T20:54:01.3852927Z Running test_mkl_verbose 1/1 ... [2025-08-26 20:54:01.384842] 2025-08-26T20:54:01.3853396Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:54:01.3854774Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkl_verbose.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:54:01.385210] 2025-08-26T20:54:08.0597101Z 2025-08-26T20:54:08.0598190Z test_mkl_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkl_verbose_1.1_96fb8e87d3388319_.log 2025-08-26T20:54:08.0599411Z Running 2 items in this shard: test/test_mkl_verbose.py::TestMKLVerbose::test_verbose_off, test/test_mkl_verbose.py::TestMKLVerbose::test_verbose_on 2025-08-26T20:54:08.0600240Z 2025-08-26T20:54:11.1996390Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:54:11.1999534Z import pkg_resources 2025-08-26T20:54:11.3242119Z Running test_decomp 1/11 ... [2025-08-26 20:54:11.323814] 2025-08-26T20:54:11.3242922Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:54:11.3245705Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_decomp.py', '-m', 'not serial', '--shard-id=1', '--num-shards=11', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:54:11.324220] 2025-08-26T20:54:41.6968561Z 2025-08-26T20:54:41.6969983Z higher_order_ops/test_invoke_subgraph 1/1 was successful, full logs can be found in artifacts with path test/test-reports/higher_order_ops.test_invoke_subgraph_1.1_4bdcde2667c313cd_.log 2025-08-26T20:54:41.7000506Z Running 67 items in this shard: test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraph::test_aot_function, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraph::test_multiple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraph::test_simple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_ac, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_ac_rng, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_ac_rng_cudagraphs, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_auto_functionalize, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_autograd_function, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_buffer_mutation_errors_under_training, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_buffer_mutation_works_under_no_grad, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_bwd_partitioning, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_complex, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_const_tensor, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dce, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dedupe, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_different_strides_in_backward, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_different_symint, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_differing_strides_for_grad_outs, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_div, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dropout_checks_joint_graph, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dropout_checks_joint_graph_inference, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_dynamic, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_fail_with_direct_invoke_subgraph, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_fake_tensor_checking, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_gen_schema, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_gen_schema_with_buffer_mutation, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_input_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation_inference_mode, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation_mutiple_times, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_mutation_mutiple_times_fake_tensor_cahche_hit, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_input_output_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_kwargs_only, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_list, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_mod_attr_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_module_forward, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_module_method, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_nonlocal_update, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_normalize_gm, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_output_output_aliasing, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_pending_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_preserves_output_strides, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_preserves_strides, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_redundant_compile_region, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_return_none, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_return_none_from_fwd, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_sdpa, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_simple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_simple_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_symint_from_fwd_to_bwd, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_triton_kernel_native, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_tuple_of_tuple, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_unbacked_symbol, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphCompile::test_view_to_reshape, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_multiple_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_pending_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_simple_func, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_simple_method, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportNonstrict::test_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_multiple_module, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_pending_unbacked, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_simple_func, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_simple_method, test/higher_order_ops/test_invoke_subgraph.py::TestInvokeSubgraphExportStrict::test_unbacked, test/higher_order_ops/test_invoke_subgraph.py::NegativeTesting::test_graph_break 2025-08-26T20:54:41.7030518Z 2025-08-26T20:54:44.7585106Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:54:44.7586913Z import pkg_resources 2025-08-26T20:54:44.8812242Z Running test_transformers 1/2 ... [2025-08-26 20:54:44.880904] 2025-08-26T20:54:44.8812702Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:54:44.8814821Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:54:44.881224] 2025-08-26T20:55:06.3346022Z 2025-08-26T20:55:06.3347510Z export/test_nativert 1/1 was successful, full logs can be found in artifacts with path test/test-reports/export.test_nativert_1.1_b260410c86649291_.log 2025-08-26T20:55:06.3765842Z Running 402 items in this shard: test/export/test_nativert.py::NativeRTTestExport::test__scaled_dot_product_flash_attention_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_additional_inputs_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_allow_explicit_guards_as_runtime_asserts_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_args_type_checked_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_aten_lift_fresh_copy_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_attention_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_attr_assignment_extra_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_constrain_size_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_dynamic_shapes_constant_relation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_dynamic_shapes_linear_relation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_automatic_dynamic_shapes_simple_equality_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_baddbmm_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_basic_non_strict_fake_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_basic_non_strict_real_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_bincount_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_buffer_util_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_capture_subclass_constructor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_capture_subclass_constructor_torch_ir_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_capture_subclass_wrong_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_ccode_python_mod_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_check_specialized_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_checks_to_constrain_range_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cleanup_dynamic_markers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_colin_unbacked_backed_vr_sub_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_colon_parameter_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_compiling_state_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_access_identical_symint_closure_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_branches_return_constant_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_branches_return_same_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_contains_unbacked_no_escape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_int_closure_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_with_module_stack_export_with_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cond_with_module_stack_export_with_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_aliasing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_input_naming_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_no_user_inp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_output_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_output_dup_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_requires_grad_const_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_return_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_tensor_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_tensor_with_non_functional_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constant_tensor_with_non_functional_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_decomp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_size_in_eager_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_size_with_constrain_value_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_constrain_size_with_various_cases_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_conv_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_crop_like_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_cse_for_symint_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_auto_functionalize_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_auto_functionalize_pre_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_auto_warn_pre_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_op_preserve_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_pytree_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_custom_tag_metadata_re_export_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_decomp_batch_norm_functional_predispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_decomp_item_in_prim_after_decomposition_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_decomp_item_in_prim_before_decomposition_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_default_decomposition_core_cia_ops_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_1_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_integer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_repeat_derived_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_simplified_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_out_of_order_simplified_repeat_non_derived_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_derived_dim_repeat_derived_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_detect_leak_strict_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_gpu_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_mutation_float_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_device_to_static_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_1_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_auto_and_dim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_dynamic_divisibility_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_dynamic_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_hint_range_violations_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dim_hint_ranges_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_disable_forced_specializations_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_disable_forced_specializations_ok_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_gather_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_gather_into_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_reduce_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_all_to_all_single_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_distributed_reduce_scatter_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dont_duck_size_for_auto_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_double_lifted_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_aliasing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_mutation_list_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_checks_mutation_with_nan_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_fake_kernel_inference_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_draft_export_infers_fake_kernel_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_duplicate_modules_with_non_persistent_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_lr_shift_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_bounds_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_builder_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_builder_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_builder_pytree_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_dataclass_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_inferred_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_serdes_generic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_serdes_user_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_serdes_various_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_shapes_spec_with_pytree_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_dynamic_sym_round_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_ends_of_bounds_oblivious_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_error_does_not_reference_eager_fallback_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_error_when_passing_mutating_primitive_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_exception_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_api_with_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_as_backend_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_associative_scan_lifted_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_associative_scan_symbol_dim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_associative_scan_symbol_scandim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_aten_to_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_aten_to_unflatten_subclass_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_aten_to_unflatten_subclass_pre_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_cond_preserve_torch_fn_for_subgraphs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_cond_symbool_pred_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_cond_warns_constant_pred_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_decomp_table_basic_pop_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_decomp_table_container_methods_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_op_lib_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_triton_kernel_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_custom_triton_kernel_mutable_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomp_torture_case_1_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomp_torture_case_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomps_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_decomps_simple_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_dynamo_config_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_run_decomp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_container_type_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_for_training_with_state_dict_hooks_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_default_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_keyword_only_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_pytree_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_var_keyword_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_var_keyword_pytree_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_func_with_var_postional_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_function_schema_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_graph_with_no_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_input_mutation_bug_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_input_mutation_dynamic_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_input_mutation_static_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_linear_preserve_dynamic_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_max_nonstrict_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_max_onnx_reported_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_mod_constraints_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_preserve_linear_at_aot_level_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_preserve_linear_but_not_custom_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_scan_pytree_output_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_script_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_statically_known_true_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_then_compile_tensor_ctor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_autocast_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_fake_tensor_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_fake_tensor_inputs_on_cuda_devices_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_inline_constraints_complex_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_inline_constraints_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_set_grad_enabled_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_export_with_wrong_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_external_call_non_strict_real_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_fake_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_fake_weights_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_filter_traceback_frames_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_float_conversion_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_float_conversion_from_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_fqn_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_from_node_metadata_export_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_full_on_scalar_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_hints_wrapper_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_hoo_inline_users_issue_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_if_functional_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_if_post_autograd_op_preserved_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_class_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_class_method_recursive_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_function_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_inline_script_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_int_shape_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_intermediate_shape_comp_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_is_exporting_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_is_non_negative_check_function_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_is_nonzero_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_isnonzero_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_issue_113041_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_issue_157289_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_istft_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_keep_composite_ops_invalid_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_keep_composite_ops_linear_convd_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_keep_composite_ops_linear_convd_for_training_ir_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_kwarg_dynamic_shapes_diff_order_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_kwargs_reorder_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_layer_norm_unbacked_normalized_shape_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_layer_sharing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_lazy_module_kwargs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_lifted_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_linear_conv_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_malformed_fqn_from_source_name_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_map_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_map_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_mask_nonzero_static_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_masked_select_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_math_pow_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_mismatched_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_mixed_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_dict_key_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_input_subclasses_parameterization_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_list_slice_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_module_with_dict_container_inp_out_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_modules_access_for_deleted_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_more_multidimensional_slicing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_multidimensional_slicing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_multinomial_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_multiple_definitions_same_name_dim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_dynamic_shapes_spec_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_with_constant_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_with_init_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nested_module_with_parameter_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nn_module_stack_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nn_module_stack_shared_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_check_is_size_error_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_suggested_fixes_for_data_dependent_errors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_3_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_no_tensor_computation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_arg_name_dynamic_shapes_api_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_arg_name_dynamic_shapes_api_with_container_type_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_arg_name_dynamic_shapes_api_with_kwarg_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_persistent_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_strict_dynamic_shapes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_non_strict_dynamic_shapes_suggested_fixes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_none_buffers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nonstrict_retrace_preserves_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nonzero_2_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_nonzero_dynamic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_not_registered_parameter_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_operator_aten_tensor_mode_variant_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_output_node_name_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_pad_sequence_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_param_util_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_partial_patched_forward_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_collisions_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_collisions_hoo_subgraphs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_order_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_naming_order_variadic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_placeholder_update_preserving_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_predispatch_cond_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_predispatch_grad_wrappers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_preserve_module_call_signature_unflatten_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_preserve_requires_grad_placeholders_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_preserve_shape_dynamism_for_unused_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_profiling_code_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_python_asserts_with_sym_int_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_pytree_register_data_class_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_pytree_register_nested_data_class_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_raise_user_error_when_guard_on_data_dependent_operation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_range_constraints_with_replacement_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_alias_dtype_mismatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_bool_cast_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_errors_on_aliasing_custom_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_for_max_op_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_real_tensor_size_mismatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_redundant_assert_max_upper_bound_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_redundant_asserts_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_refine_dynamic_shapes_from_suggested_fixes_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_register_constant_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_repeat_interleave_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_replace_unbacked_with_very_large_upperbound_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_replaced_unbacked_bindings_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_reshape_view_helper_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_retracable_ep_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_retrace_pre_autograd_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_run_decomposition_supports_user_input_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_run_decompositions_keep_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_run_decompositions_keep_tensor_constant_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_runtime_assert_for_prim_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_runtime_assert_for_prm_str_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_runtime_assert_with_size_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sdpa_gqa_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sequential_slicing_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_example_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_grad_as_side_effect_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_grad_empty_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_set_grad_unflatten_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_setgrad_lifted_tensor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_shared_submodule_nn_module_stack_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_simple_export_for_training_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_simple_unbacked_view_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_size_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_slice_nn_module_stack_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_solver_unsupported_sympy_function_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_specialize_derived_dim_roots_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_split_const_gm_with_lifted_constants_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_stack_trace_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_stack_trace_make_fx_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_state_primitives_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_state_shape_attribute_assignment_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_state_tensors_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_static_dim_constraints_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_complicated_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_const_metadata_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_const_metadata_not_top_level_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclass_nested_attr_access_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclasses_parameterization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_subclasses_parameterization_nested_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggest_torch_checks_with_non_negative_check_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggest_torch_checks_with_regular_check_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggested_fixes_for_data_dependent_errors_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggested_fixes_for_data_dependent_errors_puzzlers_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_suggested_fixes_new_roots_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sym_float_operators_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sym_or_sym_and_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_sym_sqrt_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symbool_item_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symfloat_item_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_additional_inputs_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_basic_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_ranges_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_shapes_collection_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_input_specialization_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_item_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_output_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_symint_tensor_return_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tensor_attribute_zero_args_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tensor_constant_aten_to_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tensor_constant_with_wrapped_method_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_to_module_with_mutated_buffer_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_to_module_with_mutated_buffer_multiple_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_to_module_with_mutated_buffer_multiple_update_sub_later_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_tolist_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_torch_check_eq_commutativity_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_torch_fn_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_trace_under_fake_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_train_eval_on_exported_preautograd_module_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_3d_matmul_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_bincount_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_bindings_for_divisible_u_symint_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_deferred_runtime_retrace_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_expand_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_infer_size_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_kth_value_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_linear_layer_norm_input_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_noncontig_lin_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_pad_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_scalar_constructor_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_slice_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_to_cond_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_to_cond_passthrough_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unbacked_unsqueeze_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_asserts_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_buffer_update_child2parent_swap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_closure_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_isinstance_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_dispatch_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_preserve_signature_no_error_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_shared_submodule_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_multiple_graphs_state_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_no_unroll_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_placeholder_update_child2parent_swap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_placeholder_update_grandchild2cousin_swap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_5_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_6_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_buf_8_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_const_preserving_3_1_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_const_preserving_3_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_6_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_9_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_10_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_1_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_5_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_mutating_buf_preserving_7_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unflatten_random_dag_preserving_4_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unused_aliases_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_unused_constant_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_use_embedding_twice_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_user_input_and_buffer_mutation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_vmap_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_assert_separation_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_index_assertions_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_simple_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_while_loop_tensor_constant_idx_cpp_runtime_nonstrict, test/export/test_nativert.py::NativeRTTestExport::test_wrapper_module_cpp_runtime_nonstrict 2025-08-26T20:55:06.4180575Z 2025-08-26T20:55:10.5351597Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T20:55:10.5355303Z import pkg_resources 2025-08-26T20:55:10.6692153Z Running test_transformers 2/2 ... [2025-08-26 20:55:10.668781] 2025-08-26T20:55:10.6693270Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T20:55:10.6696393Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_transformers.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 20:55:10.669256] 2025-08-26T21:03:40.5045491Z 2025-08-26T21:03:40.5047099Z test_transformers 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_1.2_e0b1379a24fb20b6_.log 2025-08-26T21:03:40.8954073Z Running 1703 items in this shard: test/test_transformers.py::TestTransformersCPU::test_bias_is_none_cpu, test/test_transformers.py::TestTransformersCPU::test_decoder_only_layer_cpu, test/test_transformers.py::TestTransformersCPU::test_encoder_padding_and_src_mask_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_is_causal_gpu_cpu, test/test_transformers.py::TestTransformersCPU::test_kpm_mask_trailing_column_with_nested_tensor_cpu, test/test_transformers.py::TestTransformersCPU::test_mask_check_fastpath_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_1_bias_False_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_8_bias_True_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_mask_dim1_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_mask_dim_2_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_2_key_padding_mask_dim_2_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_2_key_padding_mask_dim_2_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_3_key_padding_mask_dim1_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_3_key_padding_mask_dim1_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_3_key_padding_mask_dim_2_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_causal_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_causal_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_causal_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_no_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_no_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_causal_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_no_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_script_mha_in_proj_weight_none_cpu, test/test_transformers.py::TestTransformersCPU::test_self_attn_TxT_attn_mask_cpu, test/test_transformers.py::TestTransformersCPU::test_train_with_pad_and_catch_error_cpu, test/test_transformers.py::TestTransformersCPU::test_transformer_bias_is_none_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_False_training_False_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_False_training_False_enable_nested_tensor_True_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_False_training_True_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_False_training_True_enable_nested_tensor_True_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_True_training_True_enable_nested_tensor_True_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_False_use_autocast_False_d_model_12_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_False_use_autocast_False_d_model_256_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_False_use_autocast_True_d_model_12_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_False_use_autocast_True_d_model_256_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_True_use_autocast_False_d_model_256_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_square_input_with_no_grad_False_training_True_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_src_mask_nhead_4_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_subclass_model_cpu, test/test_transformers.py::TestTransformersCPU::test_with_nested_tensor_input_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_atteention_large_bf16_nan_values_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_attention_fail_with_non_square_causal_attention_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_backward_failure_sm86plus_head_dim_193_dropout_p_0_0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_backward_failure_sm86plus_head_dim_256_dropout_p_0_2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_fail_fp32_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_fused_kernels_nested_broadcasting_error_cases_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_fused_kernels_nested_broadcasting_requires_grad_failure_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_fused_kernels_seq_len_0_inputs_fused_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_attn_mask_present_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_broadcast_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_dim_3_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_invalid_dtype_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_1_dimensional_inputs_kernel1_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_1_dimensional_inputs_kernel2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_datatypes_kernel1_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_datatypes_kernel2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_devices_kernel1_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_devices_kernel2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_last_dim_stride_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_sequence_lengths_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_mem_eff_attention_fail_with_batch_size_geq_65536_error_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_mem_efficient_fail_bfloat16_less_than_sm80_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_nested_fails_on_padding_head_dim_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_unaligned_tensors_cpu, test/test_transformers.py::TestSDPACpuOnlyCPU::test_cpu_flash_attn_nan_propagation_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_128_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_32_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_32_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_64_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_64_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_64_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_128_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_float64_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_7_float64_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_0_bfloat16_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_7_bfloat16_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_7_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_7_float64_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_non_masked_rows_nan_props_float32_fill_val_inf_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_attention_math_with_negative_scale_kernel0_cpu, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads0_train_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads1_train_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads0_train_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads0_train_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads1_train_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads1_train_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads2_train_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads0_train_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads2_train_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads2_train_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads3_train_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads1_train_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_1_shape0_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_1_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_1_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_2_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_2_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_2_shape3_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_1_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_2_shape0_cpu, test/test_transformers.py::TestAttnBiasCPU::test_is_causal_and_mask_fails_cpu, test/test_transformers.py::TestAttnBiasCPU::test_is_causal_equals_upper_left_shape3_cpu 2025-08-26T21:03:41.2768138Z 2025-08-26T21:03:45.4015330Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:03:45.4018487Z import pkg_resources 2025-08-26T21:03:45.5972333Z Running test_mkldnn_verbose 1/1 ... [2025-08-26 21:03:45.596816] 2025-08-26T21:03:45.5973204Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:03:45.5976006Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_verbose.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:03:45.597274] 2025-08-26T21:03:54.1275966Z 2025-08-26T21:03:54.1277501Z test_mkldnn_verbose 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_verbose_1.1_2672e395256e368c_.log 2025-08-26T21:03:54.1280387Z Running 2 items in this shard: test/test_mkldnn_verbose.py::TestMKLDNNVerbose::test_verbose_off, test/test_mkldnn_verbose.py::TestMKLDNNVerbose::test_verbose_on 2025-08-26T21:03:54.1281861Z 2025-08-26T21:03:58.9564403Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:03:58.9567405Z import pkg_resources 2025-08-26T21:03:59.1657323Z Running test_utils_config_module 1/1 ... [2025-08-26 21:03:59.165288] 2025-08-26T21:03:59.1658193Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:03:59.1660991Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_utils_config_module.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:03:59.165761] 2025-08-26T21:04:04.8416665Z 2025-08-26T21:04:04.8418161Z test_utils_config_module 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_utils_config_module_1.1_09c835fb6e309f5d_.log 2025-08-26T21:04:04.8433179Z Running 22 items in this shard: test/test_utils_config_module.py::TestConfigModule::test_alias, test/test_utils_config_module.py::TestConfigModule::test_bad_jk_type, test/test_utils_config_module.py::TestConfigModule::test_base_value_loading, test/test_utils_config_module.py::TestConfigModule::test_codegen_config, test/test_utils_config_module.py::TestConfigModule::test_codegen_config_function, test/test_utils_config_module.py::TestConfigModule::test_dict_copy_semantics, test/test_utils_config_module.py::TestConfigModule::test_env_name_semantics, test/test_utils_config_module.py::TestConfigModule::test_env_name_string_semantics, test/test_utils_config_module.py::TestConfigModule::test_get_hash, test/test_utils_config_module.py::TestConfigModule::test_invalid_config_float, test/test_utils_config_module.py::TestConfigModule::test_invalid_config_int, test/test_utils_config_module.py::TestConfigModule::test_make_closur_patcher, test/test_utils_config_module.py::TestConfigModule::test_multi_env, test/test_utils_config_module.py::TestConfigModule::test_none_override_semantics, test/test_utils_config_module.py::TestConfigModule::test_overrides, test/test_utils_config_module.py::TestConfigModule::test_patch, test/test_utils_config_module.py::TestConfigModule::test_reference_is_default, test/test_utils_config_module.py::TestConfigModule::test_reference_semantics, test/test_utils_config_module.py::TestConfigModule::test_save_config, test/test_utils_config_module.py::TestConfigModule::test_save_config_portable, test/test_utils_config_module.py::TestConfigModule::test_type_loading, test/test_utils_config_module.py::TestConfigModule::test_unittest_patch 2025-08-26T21:04:04.8447606Z 2025-08-26T21:04:08.6330195Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:04:08.6333440Z import pkg_resources 2025-08-26T21:04:08.7586791Z Running test_ops_jit 1/2 ... [2025-08-26 21:04:08.758289] 2025-08-26T21:04:08.7587556Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:04:08.7590025Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_jit.py', '-m', 'not serial', '--shard-id=1', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:04:08.758694] 2025-08-26T21:04:21.2796197Z 2025-08-26T21:04:21.2797044Z test_transformers 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_transformers_2.2_1e28588ddf14026f_.log 2025-08-26T21:04:21.5777834Z Running 1600 items in this shard: test/test_transformers.py::TestTransformersCPU::test_decoder_padding_and_src_mask_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_disable_fastpath_cpu, test/test_transformers.py::TestTransformersCPU::test_encoder_is_causal_cpu, test/test_transformers.py::TestTransformersCPU::test_math_backend_high_precision_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_1_bias_True_cpu, test/test_transformers.py::TestTransformersCPU::test_mha_native_args_nb_heads_8_bias_False_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_mask_dim1_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim2_key_padding_mask_dim_2_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_2_key_padding_mask_dim1_bool_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_2_key_padding_mask_dim1_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_multiheadattention_fastpath_attn_mask_attn_mask_dim_3_key_padding_mask_dim_2_float32_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_2D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_3D_causal_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_3D_input_dim_no_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_causal_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_2D_causal_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_causal_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_4D_causal_attn_mask_dropout_p_0_2_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_no_attn_mask_dropout_p_0_0_cpu, test/test_transformers.py::TestTransformersCPU::test_scaled_dot_product_attention_4D_input_dim_no_attn_mask_dropout_p_0_5_cpu, test/test_transformers.py::TestTransformersCPU::test_script_encoder_subclass_cpu, test/test_transformers.py::TestTransformersCPU::test_train_with_is_causal_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_True_training_False_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_True_training_False_enable_nested_tensor_True_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_batch_first_True_training_True_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_True_use_autocast_False_d_model_12_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_True_use_autocast_True_d_model_12_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_fastpath_use_torchscript_False_enable_nested_tensor_True_use_autocast_True_d_model_256_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_square_input_with_no_grad_False_training_False_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_square_input_with_no_grad_True_training_False_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoder_square_input_with_no_grad_True_training_True_enable_nested_tensor_False_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_no_fastpath_with_hooks_nhead_3_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_no_fastpath_with_hooks_nhead_4_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_src_mask_nhead_1_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_src_mask_nhead_8_cpu, test/test_transformers.py::TestTransformersCPU::test_transformerencoderlayer_subclass_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_dispatch_fails_no_backend_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_autocast_fp32_bfloat16_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_autocast_fp32_float16_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_backward_failure_sm86plus_head_dim_193_dropout_p_0_2_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_flash_backward_failure_sm86plus_head_dim_256_dropout_p_0_0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_fused_inputs_head_dim_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_1_dimensional_inputs_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_datatypes_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_inputs_different_devices_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_invalid_sdpa_kernel_grouped_query_attention_cuda_fused_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_mask_invalid_last_dim_stride_kernel0_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_mask_invalid_last_dim_stride_kernel1_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_mem_eff_attention_fail_with_batch_size_geq_65536_cpu, test/test_transformers.py::TestSDPAFailureModesCPU::test_mem_eff_attention_large_seq_len_uniform_attention_cpu, test/test_transformers.py::TestSDPACPU::test_scaled_dot_product_attention_math_with_negative_scale_kernel0_cpu, test/test_transformers.py::TestSDPACPU::test_sdp_math_gradcheck_contiguous_inputs_False_cpu, test/test_transformers.py::TestSDPACPU::test_sdp_math_gradcheck_contiguous_inputs_True_cpu, test/test_transformers.py::TestSDPACpuOnlyCPU::test_cpu_flash_attn_nan_propagation_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_32_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_32_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend0_seq_len_64_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_128_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_128_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_128_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_32_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_16_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_16_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_32_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fully_masked_out_rows_backend1_seq_len_64_head_dim_32_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_0_bfloat16_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_7_bfloat16_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_7_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_dense_dropout_0_7_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_0_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_0_float32_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_0_float64_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_fused_sdp_choice_cpu_type_nested_dropout_0_7_float16_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_non_masked_rows_nan_props_float16_fill_val_inf_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads0_train_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads1_train_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads2_train_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads2_train_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads3_train_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_bfloat16_n_heads3_train_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads2_train_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads3_train_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float16_n_heads3_train_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads0_train_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads1_train_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads1_train_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float32_n_heads3_train_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads0_train_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads0_train_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads1_train_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads2_train_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads2_train_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads3_train_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_gqa_vs_math_cpu_fused_kernel0_float64_n_heads3_train_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_bfloat16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_bfloat16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float16_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float16, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float32_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float32, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_12_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_1030_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_11_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_17_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_1_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_2_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_False_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_False_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_False_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_False_casual_False_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_False_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_scaled_dot_product_fused_attention_mask_vs_math_cpu_fused_kernel0_float64_batch_size_2_q_seq_len_514_kv_seq_len_514_n_head_3_head_dim_8_mask_dim_4_bool_mask_True_train_True_casual_True_set_attn_mask_True_cpu_float64, test/test_transformers.py::TestSDPACpuOnlyCPU::test_sdpa_backward_with_gradient_cpu, test/test_transformers.py::TestSDPACpuOnlyCPU::test_sdpa_with_inf_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_1_shape3_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_causal_variant_2_shape0_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_1_shape0_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_1_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_1_shape3_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_2_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_2_shape2_cpu, test/test_transformers.py::TestAttnBiasCPU::test_causal_variants_compile_causal_variant_2_shape3_cpu, test/test_transformers.py::TestAttnBiasCPU::test_is_causal_equals_upper_left_shape0_cpu, test/test_transformers.py::TestAttnBiasCPU::test_is_causal_equals_upper_left_shape1_cpu, test/test_transformers.py::TestAttnBiasCPU::test_is_causal_equals_upper_left_shape2_cpu 2025-08-26T21:04:21.9133714Z 2025-08-26T21:04:24.7236578Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:04:24.7240059Z import pkg_resources 2025-08-26T21:04:24.8460484Z Running functorch/test_ops 4/6 ... [2025-08-26 21:04:24.845718] 2025-08-26T21:04:24.8461315Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:04:24.8464222Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_ops.py', '-m', 'not serial', '--shard-id=4', '--num-shards=6', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:04:24.846072] 2025-08-26T21:06:51.2631381Z 2025-08-26T21:06:51.2632192Z test_decomp 1/11 was successful, full logs can be found in artifacts with path test/test-reports/test_decomp_1.11_d0067b7477610f37_.log 2025-08-26T21:06:51.2893642Z Running 781 items in this shard: test/test_decomp.py::TestDecompCPU::test_comprehensive_T_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rdiv___cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmatmul___cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rmul___cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive___ror___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive___rpow___cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rsub___cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive___rxor___cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__batch_norm_with_update_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive__chunk_cat_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_lengths_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive__segment_reduce_offsets_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive__softmax_backward_data_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive__unsafe_masked_index_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_add_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addbmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addcmul_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmm_decomposed_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_addmv_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_alias_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_all_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_allclose_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_amax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_amin_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_aminmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_any_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argmin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_argsort_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_as_strided_partial_views_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_asin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_asinh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_atan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_atanh_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_atleast_1d_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_atleast_1d_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_atleast_1d_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_atleast_2d_cpu_complex64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_fftshift_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ifft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_ihfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_irfft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_fft_rfft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_fliplr_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_flipud_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_flipud_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_float_power_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_floor_divide_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_frac_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_full_cpu_bool, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_heaviside_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_hsplit_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_hsplit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_hstack_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_add_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_put_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_put_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_put_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_amin_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_mean_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_reduce_prod_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_index_select_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_inner_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_int_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_int_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_isnan_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_isposinf_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_isreal_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_istft_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_4inputs_with_extra_args_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_unary_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_jiterator_unary_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_kron_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_kthvalue_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_lcm_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_ldexp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_le_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_lerp_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_lgamma_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cholesky_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_cross_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_det_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_det_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eig_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_eigvalsh_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_factor_ex_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_lu_solve_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_norm_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_matrix_rank_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_multi_dot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_norm_subgradients_at_zero_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_pinv_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_solve_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_svdvals_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_tensorsolve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vander_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vecdot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_linalg_vector_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_linspace_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_log10_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log1p_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_log2_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_logcumsumexp_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_logdet_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_logical_xor_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_logspace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_logspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_long_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_lt_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_solve_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_lu_unpack_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amax_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_amin_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_argmin_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_cumprod_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_fill_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_logsumexp_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_scatter_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_scatter_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_select_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_select_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_sum_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_masked_var_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_max_reduction_with_dim_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_maximum_cpu_float16, test/test_decomp.py::TestDecompCPU::test_comprehensive_median_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_meshgrid_list_of_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_binary_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_binary_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_min_reduction_no_dim_cpu_float64, 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test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_unfold_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_uniform_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_comprehensive_unique_consecutive_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_unravel_index_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_mean_unbiased_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_comprehensive_var_unbiased_cpu_float64, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_float32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vdot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_as_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_view_copy_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vsplit_cpu_int8, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_bool, test/test_decomp.py::TestDecompCPU::test_comprehensive_vstack_cpu_int32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_comprehensive_where_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_comprehensive_xlogy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_comprehensive_zeros_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__batch_norm_with_update_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick__chunk_cat_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick__native_batch_norm_legit_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick__unsafe_masked_index_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick__upsample_bilinear2d_aa_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_acos_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_acosh_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_add_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_addcdiv_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_addmm_decomposed_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_addmv_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_addr_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_all_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_amax_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_amin_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_aminmax_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_any_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_copy_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_as_strided_scatter_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_asin_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_atan2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_atanh_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_bitwise_and_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_bucketize_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_cauchy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_clamp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_clamp_max_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_clamp_min_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_complex_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_conj_physical_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_constant_pad_nd_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_copysign_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_alias_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_baddbmm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_dot_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_logsumexp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_mv_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_take_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_transpose_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_tril_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_core_backward_zero__cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_cos_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_cosh_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_count_nonzero_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_cumprod_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_diag_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_diag_embed_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_digamma_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_dist_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_div_floor_rounding_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_div_no_rounding_mode_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_div_trunc_rounding_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_dot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_empty_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_empty_strided_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_eq_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_exp_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_expand_copy_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expand_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_expm1_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_eye_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fft_fft2_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft2_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_ifft_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfftn_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_fft_ihfftn_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft2_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_fft_irfft_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_fmin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_frac_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_frexp_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_full_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_geometric_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_gt_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_i0_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_igammac_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_index_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_index_fill_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_index_select_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_isinf_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_isnan_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_item_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_le_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_linalg_diagonal_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linalg_vector_norm_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_linspace_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_log_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_log_normal_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_log_softmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logaddexp2_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_logical_and_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_logical_not_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_logical_or_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_logspace_tensor_overload_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_masked_fill_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_maximum_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_list_of_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_meshgrid_variadic_tensors_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_mv_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_mvlgamma_mvlgamma_p_3_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nan_to_num_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_nansum_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_narrow_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_native_dropout_backward_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_ne_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_neg_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_new_full_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_new_ones_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_binary_cross_entropy_with_logits_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_elu_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_hardshrink_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_logsigmoid_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_pad_constant_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_softplus_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_nn_functional_unfold_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_norm_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_fro_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_norm_nuc_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_normal_number_mean_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_complex32, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_ones_like_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_permute_copy_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_pow_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_prod_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_renorm_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_rot90_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_round_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_rsub_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_sigmoid_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_signbit_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sin_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_sinc_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_slice_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_slice_scatter_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_softmax_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_entr_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_special_erfcx_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_special_i0e_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_special_i1_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_special_zeta_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_list_args_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_split_with_sizes_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_sqrt_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_copy_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_squeeze_multiple_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_stack_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_std_mean_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_std_unbiased_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_sub_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_t_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_t_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_take_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_tan_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_trace_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_tril_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_tril_indices_cpu_int32, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_triu_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_float32, test/test_decomp.py::TestDecompCPU::test_quick_unbind_copy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_bfloat16, test/test_decomp.py::TestDecompCPU::test_quick_unbind_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_unfold_copy_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_copy_cpu_bool, test/test_decomp.py::TestDecompCPU::test_quick_unsqueeze_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_var_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_vdot_cpu_uint8, test/test_decomp.py::TestDecompCPU::test_quick_view_copy_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_float16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_view_cpu_int64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex128, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_complex64, test/test_decomp.py::TestDecompCPU::test_quick_where_cpu_int8, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_float64, test/test_decomp.py::TestDecompCPU::test_quick_xlogy_cpu_int16, test/test_decomp.py::TestDecompCPU::test_quick_zeros_like_cpu_float16, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_GRU_train_mode_cpu_float32, test/test_decomp.py::TestDecompCPU::test_rnn_decomp_module_nn_RNN_eval_mode_cpu_float32, test/test_decomp.py::DecompOneOffTestsCPU::test_exponential_non_inf_cpu, test/test_decomp.py::DecompOneOffTestsCPU::test_sdpa_nn_functional_scaled_dot_product_attention_cpu_bfloat16 2025-08-26T21:06:51.3147223Z 2025-08-26T21:06:54.3481577Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:06:54.3483194Z import pkg_resources 2025-08-26T21:06:54.4727534Z Running test_ops 3/7 ... [2025-08-26 21:06:54.472410] 2025-08-26T21:06:54.4727954Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:06:54.4730339Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'not serial', '--shard-id=3', '--num-shards=7', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:06:54.472754] 2025-08-26T21:12:16.4830555Z 2025-08-26T21:12:16.4831792Z test_ops_jit 1/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_jit_1.2_85cd491acd165a72_.log 2025-08-26T21:12:16.5255574Z Running 598 items in this shard: test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_acos_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_asin_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_atan2_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_clamp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_div_trunc_rounding_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_erfinv_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_exp2_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_expm1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_ge_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_i0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_igamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_igammac_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_lgamma_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_linalg_det_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_lt_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_matmul_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_matrix_exp_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_min_binary_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_movedim_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mvlgamma_mvlgamma_p_1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_jit_alias_remapping_mvlgamma_mvlgamma_p_3_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_channel_shuffle_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_channel_shuffle_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv1d_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv1d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv_transpose1d_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv_transpose1d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv_transpose2d_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv_transpose2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_conv_transpose3d_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_ctc_loss_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_dropout3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_embedding_bag_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_feature_alpha_dropout_without_train_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_fractional_max_pool2d_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_linear_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_linear_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_local_response_norm_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_max_pool2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_max_pool3d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_max_unpool2d_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_max_unpool2d_grad_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_max_unpool3d_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_unfold_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_upsample_bilinear_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nn_functional_upsample_nearest_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_nonzero_static_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_fro_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_inf_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_norm_inf_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_normal_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_normal_in_place_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ones_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ormqr_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_outer_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pca_lowrank_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pca_lowrank_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_permute_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pinverse_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pinverse_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polar_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_polygamma_polygamma_n_1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_pow_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_prod_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_put_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_put_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_quantile_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_randint_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_randint_like_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_randn_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_randn_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_randn_like_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_ravel_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_real_cpu_float32, 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test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_scatter_reduce_prod_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_select_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_select_scatter_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_short_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sigmoid_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sigmoid_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_signal_windows_cosine_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_signal_windows_exponential_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_signal_windows_gaussian_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_signal_windows_general_cosine_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_signal_windows_nuttall_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_signbit_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sin_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sin_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sinc_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sinc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sinh_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_slice_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_slice_scatter_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_softmax_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_softmax_with_dtype_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_softmax_with_dtype_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sort_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sparse_mm_reduce_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_airy_ai_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_bessel_y0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_chebyshev_polynomial_t_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_chebyshev_polynomial_u_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_chebyshev_polynomial_v_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_chebyshev_polynomial_w_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_entr_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_erfcx_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_hermite_polynomial_he_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_i1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_laguerre_polynomial_l_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_modified_bessel_i0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_modified_bessel_i1_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_ndtr_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_shifted_chebyshev_polynomial_t_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_shifted_chebyshev_polynomial_v_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_spherical_bessel_j0_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_special_xlog1py_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_list_args_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_list_args_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_with_sizes_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_with_sizes_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_split_with_sizes_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sqrt_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_square_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_squeeze_multiple_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_stack_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_mean_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_mean_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_std_mean_unbiased_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_stft_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sub_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sum_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_sum_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_svd_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_svd_lowrank_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_svd_lowrank_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_t_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_t_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_t_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tan_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tanh_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tanh_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tensor_split_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tile_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tile_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_to_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_to_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_to_sparse_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trace_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_transpose_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_transpose_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_transpose_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trapz_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_triangular_solve_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_tril_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_triu_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_trunc_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unbind_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unbind_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unbind_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unfold_copy_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unfold_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unfold_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_uniform_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unique_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsafe_chunk_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsafe_split_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsafe_split_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_unsqueeze_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_unbiased_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_mean_unbiased_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_var_unbiased_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_as_real_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_view_copy_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_vsplit_cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_where_cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zero__cpu_complex64, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zero__cpu_float32, test/test_ops_jit.py::TestJitCPU::test_variant_consistency_jit_zeros_like_cpu_float32 2025-08-26T21:12:16.5533868Z 2025-08-26T21:12:19.6894969Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:12:19.6896561Z import pkg_resources 2025-08-26T21:12:19.8127990Z Running test_ops 6/7 ... [2025-08-26 21:12:19.812530] 2025-08-26T21:12:19.8128410Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:12:19.8130995Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops.py', '-m', 'not serial', '--shard-id=6', '--num-shards=7', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:12:19.812870] 2025-08-26T21:13:51.9679985Z 2025-08-26T21:13:51.9680874Z functorch/test_ops 4/6 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_ops_4.6_88007b4acb41ffb4_.log 2025-08-26T21:13:52.1029699Z Running 1724 items in this shard: test/functorch/test_ops.py::TestOperatorsCPU::test_grad_H_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad__native_batch_norm_legit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_abs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_arange_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_asinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_atanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_atleast_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_char_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_clone_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_einsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_fft_ihfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_hypot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_put_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_jiterator_binary_return_by_ref_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_eig_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_householder_product_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_ldl_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_multi_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_log_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_logdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_logical_or_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_matmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_dropout3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_logsigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_pad_constant_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_nn_functional_smooth_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_pinverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_polygamma_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_rad2deg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_round_decimals_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_rsqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_rsub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_scatter_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_scatter_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signal_windows_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_sin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_airy_ai_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_entr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_special_i1e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_t_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_true_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_unbind_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_grad_where_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp___getitem___functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp___rsub___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_abs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_alias_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_arange_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_as_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_bfloat16_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_bool_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cartesian_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cauchy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_expand_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_fftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_float_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_index_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_ldl_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_slogdet_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_linalg_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_log1p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_logical_or_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_logsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_min_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_min_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_minimum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nanquantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_native_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_new_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_dropout3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_interpolate_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pad_constant_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_silu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_ops_aten_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_randn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_scatter_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_scatter_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signal_windows_general_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_erfcx_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_special_i0e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_split_list_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_sum_to_size_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unsafe_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_var_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvp_vstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpjvpvmap_SelectAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp___rmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_asinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_bool_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_cartesian_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_chalf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_clamp_min_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_constant_pad_nd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_contiguous_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_deg2rad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_diff_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_erfinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_ifftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_grid_sampler_3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_index_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_isneginf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_item_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_eigvalsh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_lstsq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_solve_triangular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_logical_and_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_mvlgamma_mvlgamma_p_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nanmean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nanquantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_narrow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_new_empty_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_new_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_celu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv_transpose2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_group_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_hinge_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_leaky_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_pad_circular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_softmin_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_nn_functional_softsign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_ones_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_ormqr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_polygamma_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_pow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_randint_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_reshape_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_resize__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_resolve_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_scatter_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_bartlett_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_hermite_polynomial_h_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_laguerre_polynomial_l_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_transpose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unbind_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unfold_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_uniform_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjp_vsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjpvmap_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjpvmap_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvjpvmap_ScaleGradGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_NumpyCubeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_NumpyCubeNotComposableAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmap_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmapvmap_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_jvpvmapvmap_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_amax_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_ceil_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_clamp_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_gt_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_le_cpu_complex64, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_minimum_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_ordered_complex_raises_topk_cpu_complex32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_T_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_broadcast_to_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_hsplit_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_split_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_list_return_unbind_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_permute_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_positive_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_positive_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_real_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_resolve_conj_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_transpose_grad_op_jvp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_transpose_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_view_then_inplace_view_as_grad_op_vjp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp___rsub___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__segment_reduce_offsets_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp__upsample_bilinear2d_aa_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_atan2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_atleast_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_chalf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_corrcoef_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_cummin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_div_floor_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_empty_permuted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_equal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_fft_rfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_index_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_lgamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_cond_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_matrix_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_log1p_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_logspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_masked_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_mv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nanmean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_ne_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_new_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_stride_padding_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv2d_stride_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_nn_functional_l1_loss_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_polygamma_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_repeat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_resolve_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_scalar_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sgn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_gaussian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_signal_windows_nuttall_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_i0e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_polygamma_special_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_special_shifted_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_topk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_trunc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_unsafe_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjp_unsafe_split_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_bfloat16_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cauchy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cholesky_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_diagonal_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_empty_permuted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_eq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_hfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fft_irfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_fmod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_geqrf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_index_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_inner_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_le_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_eigh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_lstsq_grad_oriented_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_lu_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_vander_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_linspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_long_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_lt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_mH_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_masked_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_multinomial_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_adaptive_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_dropout3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_gaussian_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_group_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_interpolate_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_max_unpool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pad_circular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_normal_number_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_positive_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_resize__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_resize_as__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_scalar_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_bartlett_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_signbit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_sort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_sparse_mm_reduce_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_airy_ai_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_bessel_y1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjp_squeeze_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvjpvmap_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_ForwardHasDefaultArgsAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_H_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_NumpyTakeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap___getitem___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap___getitem___functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_atanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_bool_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_cfloat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_clone_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_erf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_fft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_index_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_isin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_cholesky_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_eigvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_lstsq_grad_oriented_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_norm_subgradients_at_zero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_vander_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_log10_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_log_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_logical_not_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_masked_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_stride_groups_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_stride_padding_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_stride_padding_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_conv2d_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_group_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_huber_loss_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_softsign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_ops_aten_index_put_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_ormqr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_outer_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_rad2deg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_rand_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_randint_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_reshape_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_resize_as__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_resolve_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_round_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sign_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_special_shifted_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_t_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_tanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_where_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmap_zero__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vjpvmapvmap_ScaleGradGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_CubeGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_CubeGenVmapAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ForwardHasDefaultArgsAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_MulGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_NumpyExpMarkDirtyAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_NumpyMulAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_NumpySortAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_SortGenVmapAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ZeroGradientsGenVmapAutogradFunction_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmatmul___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmod___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rmul___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad___rpow___cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__batch_norm_with_update_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__batch_norm_with_update_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad__unsafe_masked_index_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addbmm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_addcmul_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_alias_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_any_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_arange_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_argwhere_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_asin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_asinh_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atan2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_atleast_1d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_chalf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_char_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_clamp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_clamp_max_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_column_stack_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_conj_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_copysign_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_corrcoef_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_count_nonzero_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cummax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_cumsum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_diag_embed_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_div_floor_rounding_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_double_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_dsplit_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_dstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_einsum_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_empty_like_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_empty_strided_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_eq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_erfc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_erfinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_exp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_fft2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_fft_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_fftn_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_ifftn_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_irfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fft_irfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_flipud_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_fmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_histogram_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_add_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_put_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_reduce_prod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_index_select_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isclose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isclose_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isin_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isnan_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_isneginf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_item_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_jiterator_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_kron_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_le_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_det_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_eigvalsh_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_svdvals_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log10_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_normal_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_log_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logaddexp2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logical_not_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_logsumexp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_long_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_long_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lu_solve_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_lu_unpack_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_cumprod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_cumsum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_fill_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_logsumexp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_mean_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_normalize_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_masked_softmax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_matrix_exp_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_max_pool2d_with_indices_backward_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_max_reduction_no_dim_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_meshgrid_list_of_tensors_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mul_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_mvlgamma_mvlgamma_p_5_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nan_to_num_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nanquantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_narrow_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_native_layer_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ne_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_new_full_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_adaptive_avg_pool2d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_adaptive_max_pool2d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_adaptive_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_alpha_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_celu_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv2d_stride_padding_no_bias_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_conv_transpose2d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_cosine_embedding_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_dropout2d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_dropout3d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_embedding_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_feature_alpha_dropout_with_train_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_fractional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_grid_sample_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_group_norm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_interpolate_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_kl_div_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_linear_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_margin_ranking_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_max_pool1d_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_mse_loss_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_normalize_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pad_reflect_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pad_replicate_negative_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_pixel_shuffle_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_poisson_nll_loss_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_prelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_relu6_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_softmin_with_dtype_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_norm_inf_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_normal_in_place_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ones_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_ones_like_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_2_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_3_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_polygamma_polygamma_n_4_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_prod_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_put_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_qr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_renorm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_renorm_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_repeat_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_repeat_interleave_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_repeat_interleave_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resize__cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resize_as__cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_resolve_conj_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_round_decimals_3_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_round_decimals_neg_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_rsub_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_scatter_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_short_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_short_functorch_no_channels_last_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_cosine_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_hann_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_signal_windows_kaiser_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sinc_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_slice_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_softmax_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_sparse_mm_reduce_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_bessel_j1_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_chebyshev_polynomial_u_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_i1e_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_modified_bessel_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_modified_bessel_k0_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_ndtri_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_ndtri_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_polygamma_special_polygamma_n_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_special_spherical_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_split_with_sizes_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_squeeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_squeeze_multiple_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_std_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_std_mean_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_std_unbiased_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_take_along_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_to_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_topk_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_torch_ops_aten__safe_softmax_default_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_torch_ops_aten__safe_softmax_default_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_transpose_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_transpose_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_trapezoid_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_true_divide_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unfold_copy_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unique_consecutive_cpu_float64, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_var_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmap_autograd_grad_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_NumpyCubeAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_addcmul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_addmv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_as_strided_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_atleast_2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_broadcast_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_byte_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_char_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cholesky_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_div_trunc_rounding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_exp2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_expand_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_fftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_hfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_fft_hfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule__softmax_backward_data_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_all_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_any_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_argsort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_atan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_atleast_1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_bmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_char_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_cholesky_inverse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_combinations_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_diagonal_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_digamma_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_exponential_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_fft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_fft_ihfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_frac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_gather_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_gt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_histogramdd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_index_reduce_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_index_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isfinite_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_isnan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_jiterator_2inputs_2outputs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_lerp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_eig_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_lu_factor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_pinv_singular_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_solve_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logical_xor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_logspace_tensor_overload_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_lu_unpack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_median_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_msort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_narrow_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_new_full_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_adaptive_max_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_stride_depthwise_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_conv2d_strided_padding_dilation_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_cosine_similarity_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_fractional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_hardswish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_instance_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_kl_div_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_multilabel_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_pairwise_distance_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_pixel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_nn_functional_softplus_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_norm_nuc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_pow_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_quantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_round_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_rsub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_scalar_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_signal_windows_kaiser_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_sin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_chebyshev_polynomial_w_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_hermite_polynomial_he_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_laguerre_polynomial_l_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_special_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_split_with_sizes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_trace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_triu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_unsqueeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_view_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_has_batch_rule_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_hash_tensor_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_histc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_igammac_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_index_fill_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_int_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_int_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_isreal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_jiterator_unary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_kron_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_kthvalue_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_lerp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_inv_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_ldl_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_lstsq_grad_oriented_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_multi_dot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logcumsumexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_logspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_long_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_masked_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_max_reduction_no_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_meshgrid_variadic_tensors_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_movedim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mul_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_mvlgamma_mvlgamma_p_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_narrow_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_native_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_adaptive_avg_pool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_adaptive_avg_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_adaptive_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_alpha_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_avg_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_channel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_conv2d_stride_padding_with_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_embedding_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_fractional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_gaussian_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_glu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_hardtanh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_hinge_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_interpolate_area_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_interpolate_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_max_unpool1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_max_unpool2d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_mish_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_poisson_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_silu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_smooth_l1_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_pca_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_polar_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_resolve_neg_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_round_decimals_neg_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_rsqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_scatter_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_signal_windows_kaiser_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_slice_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_softmax_with_dtype_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_bessel_j1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_bessel_y1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_laguerre_polynomial_l_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_modified_bessel_i0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_scaled_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_scaled_modified_bessel_k1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_special_zeta_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_split_with_sizes_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_sum_to_size_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_take_along_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_take_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_tile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_to_sparse_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpall_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_NumpyExpMarkDirtyAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp___rdiv___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp___rpow___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_angle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_as_strided_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_bucketize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cartesian_prod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_chunk_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cov_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cross_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cummax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_cumulative_trapezoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_diagonal_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_dist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_double_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_dsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_eq_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_equal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_eye_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_hfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_ifftshift_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_flatten_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_flip_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_flipud_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_fmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_ge_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_gt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_half_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_histogram_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_jiterator_binary_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_kthvalue_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_det_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_eig_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_lu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_lu_factor_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_tensorsolve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_linalg_vector_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_log_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_log_softmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_logspace_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_argmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_fill_functorch_Scalar_only_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_softmin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_masked_var_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_matrix_exp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_max_reduction_with_dim_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_mm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_msort_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nan_to_num_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_new_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_new_zeros_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv1d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_cosine_embedding_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_max_unpool1d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_max_unpool2d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_max_unpool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_normalize_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_nn_functional_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_norm_fro_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_normal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_ops_aten__new_zeros_with_same_feature_meta_functorchonly_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_outer_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_polar_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_rand_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_randint_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_ravel_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_round_decimals_0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_round_decimals_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_scatter_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_scatter_reduce_sum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_searchsorted_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_select_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_short_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_short_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_sigmoid_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_signal_windows_general_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_signal_windows_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_signal_windows_nuttall_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_sin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_sparse_mm_reduce_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_erfcx_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_modified_bessel_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_modified_bessel_k0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_ndtri_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_special_shifted_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_split_list_args_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_std_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_to_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_transpose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_unsafe_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_unsqueeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_vdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvjp_view_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvmap_SortGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapjvpvmap_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp__chunk_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp__softmax_backward_data_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_abs_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_acosh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_addcdiv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_addr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_all_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_aminmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_argmax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_asinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_bfloat16_functorch_no_channels_last_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_block_diag_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_broadcast_shapes_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_cdouble_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_clamp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_conj_physical_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_copysign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_diagonal_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_expm1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_fft_ifft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_fft_ifftn_cpu_float32, 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test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_channel_shuffle_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_conv2d_stride_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_conv2d_strided_padding_dilation_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_conv3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_ctc_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_dropout_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_elu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_embedding_functorch_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_interpolate_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_leaky_relu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_linear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_max_pool3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_max_unpool3d_grad_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_multi_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_poisson_nll_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_softsign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_threshold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_nn_functional_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_norm_inf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_normal_in_place_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_outer_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_permute_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_permute_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_polygamma_polygamma_n_4_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_randn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_real_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_resolve_conj_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_roll_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_sign_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_signal_windows_blackman_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_signal_windows_cosine_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_signal_windows_general_hamming_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_sinc_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_bessel_j0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_bessel_y0_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_special_chebyshev_polynomial_v_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_t_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_tan_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_transpose_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_triangular_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unbind_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_uniform_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unsqueeze_copy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_unsqueeze_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_var_mean_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjp_zeros_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_SelectGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_T_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp___getitem___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp___rmatmul___cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp__native_batch_norm_legit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp__segment_reduce_offsets_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_acos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_addbmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_asinh_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cat_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cauchy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_clamp_max_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_column_stack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_corrcoef_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cos_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_count_nonzero_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_cumprod_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_double_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_empty_like_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_empty_strided_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_expand_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_ihfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_irfft_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_rfft2_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fft_rfftn_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_fliplr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_float_power_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_floor_divide_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_heaviside_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_histogram_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_hsplit_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_hstack_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_reduce_amax_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_index_reduce_amin_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_isinf_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_jiterator_binary_return_by_ref_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_kron_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_inv_ex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_matrix_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_matrix_rank_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_pinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_pinv_hermitian_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_tensorinv_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_linalg_vecdot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_log_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_lt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_lu_solve_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_logaddexp_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_masked_std_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_maximum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nansum_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_native_batch_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_native_layer_norm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_new_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_binary_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv2d_no_bias_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_conv_transpose3d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_cross_entropy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_dropout2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_gelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_interpolate_nearest-exact_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_max_pool2d_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_pad_reflect_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_pad_replicate_negative_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_pdist_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_rrelu_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_soft_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_tanhshrink_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_triplet_margin_loss_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_upsample_bilinear_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_nn_functional_upsample_nearest_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_ones_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_polygamma_polygamma_n_1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_polygamma_polygamma_n_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_quantile_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_remainder_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_reshape_as_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_round_decimals_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_round_decimals_neg_3_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_scatter_add_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_scatter_reduce_mean_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_select_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_signal_windows_hann_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_slice_scatter_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sparse_sampled_addmm_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_airy_ai_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_bessel_y1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_chebyshev_polynomial_u_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_log_ndtr_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_modified_bessel_i1_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_ndtri_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_shifted_chebyshev_polynomial_t_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_special_xlog1py_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_split_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sqrt_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_std_unbiased_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_sub_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_svd_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_svd_lowrank_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_tensordot_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_tril_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_unfold_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_unique_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_view_as_complex_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_where_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvjp_xlogy_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_NumpyMulAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_NumpySortAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_ScaleGradGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvjpvmap_ZeroGradientsGenVmapAutogradFunction_cpu_float32, test/functorch/test_ops.py::TestOperatorsCPU::test_vmapvmapjvp_linalg_solve_cpu 2025-08-26T21:13:52.2381366Z 2025-08-26T21:13:53.3092836Z Uploading artifacts took 1.34 seconds 2025-08-26T21:13:55.8117745Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:13:55.8120396Z import pkg_resources 2025-08-26T21:13:55.9919950Z Running test_jiterator 1/1 ... [2025-08-26 21:13:55.991556] 2025-08-26T21:13:55.9920884Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:13:55.9922777Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_jiterator.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:13:55.991991] 2025-08-26T21:13:59.8426601Z 2025-08-26T21:13:59.8431333Z test_jiterator 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_jiterator_1.1_ebb97649c5c091c7_.log 2025-08-26T21:13:59.8432198Z Running 0 items in this shard: 2025-08-26T21:13:59.8432397Z 2025-08-26T21:14:04.4153155Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:14:04.4154750Z import pkg_resources 2025-08-26T21:14:04.5409742Z Running test_ops_gradients 2/2 ... [2025-08-26 21:14:04.540660] 2025-08-26T21:14:04.5410209Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:14:04.5412474Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_ops_gradients.py', '-m', 'not serial', '--shard-id=2', '--num-shards=2', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:14:04.541030] 2025-08-26T21:15:17.7868162Z 2025-08-26T21:15:17.7869453Z test_ops 3/7 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_3.7_c6b7e90087f70ccc_.log 2025-08-26T21:15:17.9652665Z Running 4942 items in this shard: test/test_ops.py::TestCommonCPU::test_compare_cpu___rmatmul___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_cdouble_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_char_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_int_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_addcmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_chunk_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_copysign_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_diag_embed_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_diagonal_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_div_trunc_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fft_fftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_hsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_igamma_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nextafter_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_norm_cpu_float32, 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test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_asin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_atan2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_baddbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cat_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ceil_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_diff_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_div_floor_rounding_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_fft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_hfft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ifft2_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_fft_ifft_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_frexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_lu_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_matrix_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_log_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logical_or_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_matmul_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_max_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mode_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_msort_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nanquantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_normalize_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_softplus_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_rad2deg_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_round_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_round_decimals_3_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sinc_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_i1_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_triangular_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_unbind_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_vstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_zeros_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_H_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rand___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rdiv___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rmatmul___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices___rpow___cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rpow___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices__chunk_cat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices__segment_reduce_offsets_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__softmax_backward_data_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_addcmul_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addmm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_alias_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_angle_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_as_strided_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bincount_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_not_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_or_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_tensors_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_broadcast_to_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cfloat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_char_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_chunk_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cov_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cov_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_cumprod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagflat_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_dstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_like_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_equal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_erf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_as_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_expand_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_expm1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_eye_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfft2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifft_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ifftshift_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_irfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_flip_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_flipud_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_histc_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_hstack_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_i0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_index_select_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_inner_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isfinite_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_isfinite_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_isinf_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_4inputs_with_extra_args_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_kron_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_kthvalue_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_lcm_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_ldexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_le_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cholesky_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_eig_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_eigvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_inv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lstsq_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_multi_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_pinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_solve_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_svdvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_tensorinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linspace_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log2_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_log_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logit_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mT_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_argmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_reduction_no_dim_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_msort_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mul_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mvlgamma_mvlgamma_p_1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nanmean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nanquantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_narrow_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_narrow_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_ne_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_new_full_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_adaptive_max_pool3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool1d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_avg_pool3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_celu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_channel_shuffle_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv_transpose2d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_replicate_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_selu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softsign_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_polygamma_polygamma_n_1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_put_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_qr_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_randint_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_resize__cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_roll_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_rot90_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_rsqrt_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sgn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_short_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_exponential_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_hamming_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sort_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_u_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_legendre_polynomial_p_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_u_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_squeeze_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_std_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_stft_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sub_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_take_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tile_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_triu_indices_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_true_divide_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unfold_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_view_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_xlogy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_zeros_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_zeros_like_cpu_int64, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values__unsafe_masked_index_put_accumulate_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_asin_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_atanh_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_cdouble_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_clamp_min_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_column_stack_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_constant_pad_nd_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_diagonal_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_expand_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_expm1_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_fft_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_hfft2_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_ihfft2_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_ihfft_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_flipud_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_float_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_hstack_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_index_fill_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_int_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_isinf_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_isposinf_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_jiterator_2inputs_2outputs_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_log10_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_logical_xor_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_logit_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_masked_scatter_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_masked_select_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_masked_sum_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_msort_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_narrow_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_permute_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_polygamma_polygamma_n_3_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_ravel_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_resolve_neg_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_scatter_reduce_amax_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_softmax_with_dtype_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_airy_ai_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_bessel_y0_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_chebyshev_polynomial_t_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_chebyshev_polynomial_w_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_hermite_polynomial_he_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_special_modified_bessel_i0_cpu_bool, 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test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_index_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_istft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_item_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_linalg_vector_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_logaddexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_logical_xor_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_narrow_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_new_empty_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_pixel_shuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_softmin_with_dtype_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_ones_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_prod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_renorm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_roll_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_sin_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_stft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_view_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__unsafe_masked_index_put_accumulate_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_addcmul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_any_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_argwhere_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_asin_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_asinh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atleast_2d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_bfloat16_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_char_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_cholesky_inverse_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_chunk_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_clone_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_constant_pad_nd_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_count_nonzero_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diagonal_scatter_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_double_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_dsplit_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_einsum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_empty_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_equal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_expand_as_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_fftshift_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_ifft2_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_flipud_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_imag_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_isreal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_cholesky_ex_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_cross_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_eigh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lstsq_grad_oriented_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_qr_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_tensorsolve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linspace_tensor_overload_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logical_not_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_long_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_select_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_var_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_mul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_narrow_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ne_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_empty_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_full_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv1d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv3d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv_transpose1d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_conv_transpose3d_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_l1_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_pad_constant_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_rms_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nonzero_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nonzero_static_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_norm_inf_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_pca_lowrank_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_permute_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_put_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_real_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_reshape_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_resize_as__cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_rot90_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_scatter_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sigmoid_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sinc_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_squeeze_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_t_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_take_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_trapezoid_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_trapz_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tril_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_triu_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unfold_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unsafe_chunk_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_var_mean_unbiased_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_vdot_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_where_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_T_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_float_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_as_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_as_strided_partial_views_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_cosh_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_cumsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_diag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_diagonal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expand_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expm1_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_fft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_ifftshift_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isnan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isreal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_linalg_vector_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log1p_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_logaddexp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_movedim_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_neg_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_nn_functional_pixel_shuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_prod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_rot90_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_square_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_std_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_std_mean_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sub_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_true_divide_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unsqueeze_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_acos_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_addcdiv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_as_strided_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_atleast_1d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_bfloat16_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_broadcast_to_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_byte_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cumprod_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cumsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diagonal_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_empty_like_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_expand_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_hfft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_imag_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_item_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cross_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_householder_product_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_pinv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_svdvals_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_tensorsolve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_not_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_lu_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_select_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_matmul_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_narrow_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_full_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_conv3d_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pad_constant_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pad_reflect_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_pixel_shuffle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_nn_functional_triplet_margin_loss_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_normal_in_place_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_ones_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_outer_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_put_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_resize__cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_squeeze_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_std_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_trapezoid_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unfold_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unsafe_split_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unsqueeze_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_unsqueeze_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_view_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_view_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_vsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_view_H_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__native_batch_norm_legit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_cfloat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_float_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_long_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_addr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_as_strided_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_asinh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atan2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atan_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atleast_1d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_atleast_2d_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_block_diag_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_broadcast_to_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_bucketize_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_conj_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cosh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_diagonal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_div_trunc_rounding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_empty_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_eq_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_fft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ifft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_ifftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_irfft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fmax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fmod_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ge_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_index_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_isclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_item_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_le_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_cross_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_diagonal_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_matrix_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linalg_vecdot_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_logical_xor_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_neg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_new_full_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_new_zeros_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_hardtanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_huber_loss_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_layer_norm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_pixel_unshuffle_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_prelu_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_nn_functional_softplus_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ones_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_pow_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_rad2deg_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_randn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_repeat_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sigmoid_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_entr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_multigammaln_mvlgamma_p_5_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_ndtr_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_squeeze_multiple_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_t_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_take_along_dim_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_tanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_transpose_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unbind_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unflatten_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_unfold_copy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_all_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_as_strided_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_as_strided_partial_views_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_atanh_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_baddbmm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_char_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cholesky_inverse_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_clone_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_cummax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diag_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_diff_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_einsum_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_empty_like_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_fftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_hfftn_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_fft_irfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view_flip_cpu_float64, 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test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_to_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_transpose_copy_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_trunc_divide_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_unfold_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_view_copy_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_vstack_cpu, test/test_ops.py::TestFakeTensorCPU::test_fake___radd___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_addcdiv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_as_strided_partial_views_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_asin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___ror___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_alias_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_as_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_baddbmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bfloat16_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_byte_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_column_stack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cummax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_diag_embed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_div_floor_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_empty_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_eq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_erf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_expand_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_fft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ifft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_irfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_rfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_full_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_geqrf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_hash_tensor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_imag_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isnan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isneginf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_istft_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_jiterator_2inputs_2outputs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lcm_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_le_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_eig_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_slogdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_svdvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logical_and_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logical_or_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_argmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_std_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_minimum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nanmean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nanmedian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_celu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_unpool3d_grad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_softplus_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nonzero_static_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polygamma_polygamma_n_1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_real_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sinc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_triu_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_trunc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unique_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_var_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_xlogy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_and_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_byte_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp__batch_norm_with_update_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_as_strided_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_broadcast_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_chalf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cummax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_irfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_gather_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_hstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_matrix_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_pinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_matmul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_min_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_celu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_embedding_bag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_embedding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_softplus_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_permute_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_pinverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_positive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_renorm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_round_decimals_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_ndtri_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unsqueeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_xlogy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___getitem___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_acosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_atanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_block_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_broadcast_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ceil_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cholesky_inverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_clamp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_div_trunc_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_dstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_fftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_hfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_hfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ifftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ihfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_hypot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ldexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_lu_factor_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_cumsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_matrix_exp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_conv_transpose3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_feature_alpha_dropout_without_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_glu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_mish_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_multi_head_attention_forward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_ravel_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_remainder_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_repeat_interleave_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_reshape_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_round_decimals_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_round_decimals_neg_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_rsub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sinc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_tensordot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_transpose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_var_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_deg2rad_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diff_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_erfc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_expm1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_eye_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_fftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_hfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ifftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ihfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_flipud_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_float_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_floor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_geqrf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_grid_sampler_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_half_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_heaviside_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_histogramdd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_igamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isfinite_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_inv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_inv_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_matrix_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_multi_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_multinomial_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mvlgamma_mvlgamma_p_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_narrow_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_native_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_embedding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_local_response_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_softmin_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nonzero_static_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_pinverse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_randint_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_nuttall_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_scaled_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_zeta_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_split_list_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_triu_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rmod___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___ror___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__upsample_bilinear2d_aa_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_addmm_decomposed_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_angle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_argmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bitwise_and_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bitwise_not_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_block_diag_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_byte_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_clamp_min_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_combinations_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_div_trunc_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_expand_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fliplr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_float_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_gcd_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_geometric_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_half_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_inner_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_int_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isfinite_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_jiterator_4inputs_with_extra_args_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_le_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_eigvalsh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logcumsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logical_and_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_long_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_new_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_bicubic_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_nearest-exact_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_max_unpool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_silu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_norm_nuc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_permute_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_positive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_randn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_general_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_signal_windows_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_slice_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sparse_mm_reduce_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_airy_ai_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_xlog1py_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_split_with_sizes_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_std_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_t_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tril_indices_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_linspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_uint8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_complex32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_int8, test/test_ops.py::TestTagsCPU::test_tags__refs_T_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_byte_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_cdouble_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_chalf_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_complex_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_addcdiv_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_all_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_amax_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_as_strided_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_bucketize_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cauchy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_cumprod_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_deg2rad_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_diagonal_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_expm1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_hfft_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_irfft2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_floor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_gcd_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_hsplit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_hstack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_hypot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_igamma_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_lcm_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs_linalg_diagonal_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_linalg_vector_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_log1p_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logaddexp2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logical_and_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logical_not_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_mean_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_celu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_channel_shuffle_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_softplus_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_tanhshrink_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_ones_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_pow_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_roll_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_rot90_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_rsub_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_sinh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_special_bessel_j1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_special_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_special_multigammaln_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_special_ndtri_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_squeeze_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_stack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_t_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_t_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_tan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_transpose_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_trunc_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__softmax_backward_data_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_addr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_arange_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_atan2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_bernoulli_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_bitwise_not_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_cdist_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_clamp_max_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_column_stack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_copysign_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_cosh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_cumsum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_exponential_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_eye_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_fft_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_fftn_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_hfft2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_ifftn_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_ihfft_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_flipud_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fmin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_frac_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_gather_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_hsplit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_igammac_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_index_reduce_amin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_istft_cpu_complex64, test/test_ops.py::TestTagsCPU::test_tags_lcm_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_linalg_cross_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_eigvals_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_inv_ex_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_lu_factor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_lu_solve_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_solve_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linspace_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_log2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_logical_and_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_masked_argmin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_masked_prod_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_masked_sum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_median_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_min_binary_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_mm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_multinomial_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nanquantile_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_native_layer_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nextafter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_celu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_hardsigmoid_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_hardtanh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_hinge_embedding_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_linear_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_max_unpool1d_grad_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_multilabel_soft_margin_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_pdist_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_poisson_nll_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_relu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_silu_complex_cpu_complex64, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_softplus_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_reciprocal_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_round_decimals_3_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_select_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_select_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sgn_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_signbit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_entr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_squeeze_multiple_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_std_mean_unbiased_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_svd_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_t_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tensordot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_to_sparse_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_transpose_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unique_consecutive_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_var_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_var_mean_unbiased_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_zeros_like_cpu_float32 2025-08-26T21:15:18.1353674Z 2025-08-26T21:15:21.1136710Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:15:21.1140405Z import pkg_resources 2025-08-26T21:15:21.2368153Z Running lazy/test_step_closures 1/1 ... [2025-08-26 21:15:21.236373] 2025-08-26T21:15:21.2369179Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:15:21.2371402Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_step_closures.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:15:21.236738] 2025-08-26T21:15:27.7116720Z 2025-08-26T21:15:27.7118284Z lazy/test_step_closures 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_step_closures_1.1_dd974d3f7a98ba40_.log 2025-08-26T21:15:27.7122327Z Running 4 items in this shard: test/lazy/test_step_closures.py::ClosuresTest::test_asynchronous, test/lazy/test_step_closures.py::ClosuresTest::test_asynchronous_exception, test/lazy/test_step_closures.py::ClosuresTest::test_synchronous, test/lazy/test_step_closures.py::ClosuresTest::test_synchronous_exception 2025-08-26T21:15:27.7125150Z 2025-08-26T21:15:31.3567408Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:15:31.3570580Z import pkg_resources 2025-08-26T21:15:31.4812548Z Running test_sparse_semi_structured 1/1 ... [2025-08-26 21:15:31.480841] 2025-08-26T21:15:31.4813532Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:15:31.4815841Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sparse_semi_structured.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:15:31.481200] 2025-08-26T21:15:39.6071470Z 2025-08-26T21:15:39.6072651Z test_sparse_semi_structured 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sparse_semi_structured_1.1_39ee0ae050d2b6a3_.log 2025-08-26T21:15:39.6112797Z Running 42 items in this shard: test/test_sparse_semi_structured.py::SparseSemiStructuredTensorCompileTest::test_mlp_contiguous_relu_compile_cusparselt, test/test_sparse_semi_structured.py::SparseSemiStructuredTensorCompileTest::test_mlp_contiguous_relu_compile_cutlass, test/test_sparse_semi_structured.py::SparseSemiStructuredTensorCompileTest::test_sp24_compile, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_indices, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_linear, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_min_sparse_shape, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mlp, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_first_NN, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_first_NT, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_first_TN, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_second_NN, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_mm_sparse_second_NT, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_to_sparse_semi_structured, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_unsupported_dim, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_unsupported_dtype, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_unsupported_shape, test/test_sparse_semi_structured.py::TestSparseSemiStructured::test_values, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_gemm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pack_both_ways_edge_case1, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pack_both_ways_id, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pack_both_ways_meta_correctness, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_prune_dense_static_sort, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_pruning_algo_largest_abs_values_greedy, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_apply, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_apply_dense, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_matmuls, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_matmuls_bmm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredTraining::test_sp24_matmuls_mat_vec, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_conversions, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_conversions_all_patterns, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_linear_cutlass, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUTLASS::test_sparse_semi_structured_ops_cutlass, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_alpha, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_alpha_compile_autotune, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_alpha_mixed_dtype, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_mixed_dtype, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cslt_sparse_mm_search, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_csrc_cslt_sparse_mm_search, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_cusparselt_backend, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_sparse_fp8fp8_mm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_sparse_semi_structured_scaled_mm, test/test_sparse_semi_structured.py::TestSparseSemiStructuredCUSPARSELT::test_sparse_semi_structured_scaled_mm_fp8 2025-08-26T21:15:39.6152302Z 2025-08-26T21:15:43.6127724Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:15:43.6130972Z import pkg_resources 2025-08-26T21:15:43.7943987Z Running nn/test_packed_sequence 1/1 ... [2025-08-26 21:15:43.793978] 2025-08-26T21:15:43.7945031Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:15:43.7950687Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_packed_sequence.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:15:43.794621] 2025-08-26T21:15:48.5169565Z 2025-08-26T21:15:48.5171107Z nn/test_packed_sequence 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_packed_sequence_1.1_7903c9f4947cbe08_.log 2025-08-26T21:15:48.5181235Z Running 12 items in this shard: test/nn/test_packed_sequence.py::PackedSequenceTest::test_pack_padded_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pack_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence_with_non_iterable_sequences, test/nn/test_packed_sequence.py::PackedSequenceTest::test_pad_sequence_with_tensor_sequences, test/nn/test_packed_sequence.py::PackedSequenceTest::test_to, test/nn/test_packed_sequence.py::PackedSequenceTest::test_to_memory_format, test/nn/test_packed_sequence.py::PackedSequenceTest::test_total_length, test/nn/test_packed_sequence.py::PackedSequenceTest::test_type_casts, test/nn/test_packed_sequence.py::PackedSequenceTest::test_unpack_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_unpad_sequence, test/nn/test_packed_sequence.py::PackedSequenceTest::test_wrong_order 2025-08-26T21:15:48.5189801Z 2025-08-26T21:15:51.8324542Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:15:51.8327834Z import pkg_resources 2025-08-26T21:15:51.9572716Z Running profiler/test_record_function 1/1 ... [2025-08-26 21:15:51.956843] 2025-08-26T21:15:51.9573717Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:15:51.9576097Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_record_function.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:15:51.957261] 2025-08-26T21:15:55.2280399Z 2025-08-26T21:15:55.2282015Z profiler/test_record_function 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_record_function_1.1_b2e7e166457642af_.log 2025-08-26T21:15:55.2287137Z Running 4 items in this shard: test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_delegation_with_profiler, test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_with_record_function, test/profiler/test_record_function.py::TestRecordFunction::test_datapipe_with_record_function_fork, test/profiler/test_record_function.py::TestRecordFunction::test_record_function 2025-08-26T21:15:55.2290990Z 2025-08-26T21:15:58.3387509Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:15:58.3390653Z import pkg_resources 2025-08-26T21:15:58.4612306Z Running nn/test_lazy_modules 1/1 ... [2025-08-26 21:15:58.460827] 2025-08-26T21:15:58.4613188Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:15:58.4615711Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_lazy_modules.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:15:58.461237] 2025-08-26T21:16:02.6818380Z 2025-08-26T21:16:02.6819854Z nn/test_lazy_modules 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_lazy_modules_1.1_303e5944bbb5dfb7_.log 2025-08-26T21:16:02.6860261Z Running 59 items in this shard: test/nn/test_lazy_modules.py::TestLazyModules::test_chained_initialization, test/nn/test_lazy_modules.py::TestLazyModules::test_invalid_functions, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_batchnorm_with_dict_input, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose1d_kwargs, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d_kwargs, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d_kwargs, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transpose3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_conv_transposed1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_forward_hook, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm1d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm1d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm1d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm2d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm2d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm2d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm3d, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm3d_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_instancenorm3d_state, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_linear_pickle, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_linear_state_and_forward, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_buffer, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_jit_buffer, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_jit_param, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_module_parameter, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_pre_forward_hook, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_share_memory_buffer, test/nn/test_lazy_modules.py::TestLazyModules::test_lazy_share_memory_param, test/nn/test_lazy_modules.py::TestLazyModules::test_linear, test/nn/test_lazy_modules.py::TestLazyModules::test_linear_state, test/nn/test_lazy_modules.py::TestLazyModules::test_materialize_device, test/nn/test_lazy_modules.py::TestLazyModules::test_materialize_dtype, test/nn/test_lazy_modules.py::TestLazyModules::test_optimizer_pass, test/nn/test_lazy_modules.py::TestLazyModules::test_spectral_norm, test/nn/test_lazy_modules.py::TestLazyModules::test_weight_norm 2025-08-26T21:16:02.6899365Z 2025-08-26T21:16:06.3494267Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:16:06.3495873Z import pkg_resources 2025-08-26T21:16:06.4714533Z Running test_fx_reinplace_pass 1/1 ... [2025-08-26 21:16:06.471152] 2025-08-26T21:16:06.4715000Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:16:06.4718119Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_fx_reinplace_pass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:16:06.471533] 2025-08-26T21:16:10.1908073Z 2025-08-26T21:16:10.1909576Z test_fx_reinplace_pass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_fx_reinplace_pass_1.1_2cbe70a5c30c127d_.log 2025-08-26T21:16:10.1920277Z Running 12 items in this shard: test/test_fx_reinplace_pass.py::TestReinplacePass::test_out_node_updated, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_basic, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_different_metadata, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_index_mutation, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_overlapping_memory, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_op, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_invalid, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_invalid2, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_scatter_twice_with_different_view_op_valid, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_sym_input, test/test_fx_reinplace_pass.py::TestReinplacePass::test_reinplace_with_view 2025-08-26T21:16:10.1930447Z 2025-08-26T21:16:14.0283568Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:16:14.0286750Z import pkg_resources 2025-08-26T21:16:14.2083879Z Running profiler/test_cpp_thread 1/1 ... [2025-08-26 21:16:14.207951] 2025-08-26T21:16:14.2084817Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:16:14.2089947Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_cpp_thread.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:16:14.208583] 2025-08-26T21:16:17.9289679Z 2025-08-26T21:16:17.9291230Z profiler/test_cpp_thread 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_cpp_thread_1.1_fde9108a33a54f43_.log 2025-08-26T21:16:17.9297728Z Running 6 items in this shard: test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_profile_memory_cuda, test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_with_enable_profiler_in_child_thread_cuda, test/profiler/test_cpp_thread.py::CppThreadTestCUDA::test_without_enable_profiler_in_child_thread_cuda, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_profile_memory_xpu, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_with_enable_profiler_in_child_thread_xpu, test/profiler/test_cpp_thread.py::CppThreadTestXPU::test_without_enable_profiler_in_child_thread_xpu 2025-08-26T21:16:17.9303086Z 2025-08-26T21:16:21.3811732Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:16:21.3815192Z import pkg_resources 2025-08-26T21:16:21.5051534Z Running test_cuda_expandable_segments 1/1 ... [2025-08-26 21:16:21.504826] 2025-08-26T21:16:21.5052620Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:16:21.5055396Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_cuda_expandable_segments.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:16:21.505205] 2025-08-26T21:16:26.8443012Z 2025-08-26T21:16:26.8444169Z test_cuda_expandable_segments 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_cuda_expandable_segments_1.1_3cdecf9e1c9b633b_.log 2025-08-26T21:16:26.8444947Z 2025-08-26T21:16:31.0434253Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:16:31.0437887Z import pkg_resources 2025-08-26T21:16:31.2256340Z Running test_numba_integration 1/1 ... [2025-08-26 21:16:31.225093] 2025-08-26T21:16:31.2257262Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:16:31.2259598Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_numba_integration.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:16:31.225529] 2025-08-26T21:16:35.0456395Z 2025-08-26T21:16:35.0457858Z test_numba_integration 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_numba_integration_1.1_03120bcb5271d8d4_.log 2025-08-26T21:16:35.0465663Z Running 8 items in this shard: test/test_numba_integration.py::TestNumbaIntegration::test_active_device, test/test_numba_integration.py::TestNumbaIntegration::test_array_adaptor, test/test_numba_integration.py::TestNumbaIntegration::test_conversion_errors, test/test_numba_integration.py::TestNumbaIntegration::test_cuda_array_interface, test/test_numba_integration.py::TestNumbaIntegration::test_from_cuda_array_interface, test/test_numba_integration.py::TestNumbaIntegration::test_from_cuda_array_interface_active_device, test/test_numba_integration.py::TestNumbaIntegration::test_from_cuda_array_interface_inferred_strides, test/test_numba_integration.py::TestNumbaIntegration::test_from_cuda_array_interface_lifetime 2025-08-26T21:16:35.0472426Z 2025-08-26T21:16:38.9993753Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:16:38.9996951Z import pkg_resources 2025-08-26T21:16:39.1824255Z Running test_segment_reductions 1/1 ... [2025-08-26 21:16:39.181974] 2025-08-26T21:16:39.1825435Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:16:39.1832147Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_segment_reductions.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:16:39.182589] 2025-08-26T21:16:43.5630906Z 2025-08-26T21:16:43.5632587Z test_segment_reductions 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_segment_reductions_1.1_708af8c3583fcd91_.log 2025-08-26T21:16:43.5707917Z Running 74 items in this shard: test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_multi_d_simple_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_max_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_mean_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_min_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_prod_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_pytorch_scatter_test_cases_reduce_sum_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_1d_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_bfloat16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float16_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float32_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_simple_zero_length_cpu_float64_int64, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int32, test/test_segment_reductions.py::TestSegmentReductionsCPU::test_unsafe_flag_cpu_int64 2025-08-26T21:16:43.5782063Z 2025-08-26T21:16:46.6467080Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:16:46.6470250Z import pkg_resources 2025-08-26T21:16:46.7706385Z Running test_logging 1/1 ... [2025-08-26 21:16:46.770149] 2025-08-26T21:16:46.7707157Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:16:46.7709272Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_logging.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:16:46.770593] 2025-08-26T21:16:52.3946718Z 2025-08-26T21:16:52.3948009Z test_logging 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_logging_1.1_844368347f2917aa_.log 2025-08-26T21:16:52.3949887Z Running 1 items in this shard: test/test_logging.py::LoggingTest::testApiUsage 2025-08-26T21:16:52.3950923Z 2025-08-26T21:16:56.7195000Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:16:56.7198153Z import pkg_resources 2025-08-26T21:16:56.9034052Z Running test_functionalization_of_rng_ops 1/1 ... [2025-08-26 21:16:56.902960] 2025-08-26T21:16:56.9035082Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:16:56.9040682Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_functionalization_of_rng_ops.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:16:56.903682] 2025-08-26T21:17:01.9770251Z 2025-08-26T21:17:01.9772283Z test_functionalization_of_rng_ops 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_functionalization_of_rng_ops_1.1_fbbee4785be75363_.log 2025-08-26T21:17:01.9774958Z Running 1 items in this shard: test/test_functionalization_of_rng_ops.py::NegativeTestCPU::test_on_cpu_cpu_float32 2025-08-26T21:17:01.9776176Z 2025-08-26T21:17:06.1999114Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:17:06.2000680Z import pkg_resources 2025-08-26T21:17:06.3238255Z Running functorch/test_aot_joint_with_descriptors 1/1 ... [2025-08-26 21:17:06.323499] 2025-08-26T21:17:06.3238822Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:17:06.3241135Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_aot_joint_with_descriptors.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:17:06.323856] 2025-08-26T21:17:17.4548037Z 2025-08-26T21:17:17.4549911Z functorch/test_aot_joint_with_descriptors 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_aot_joint_with_descriptors_1.1_1f1af529b1401f1c_.log 2025-08-26T21:17:17.4562198Z Running 10 items in this shard: test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_conv_bn_module, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_export_and_compile, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_conv_bn_module, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_multiple_outputs, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_node_consistency, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_fx_utils_simple_linear, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_in_out_specs, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_module_with_kwargs, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_multiple_outputs_module, test/functorch/test_aot_joint_with_descriptors.py::TestAOTJointWithDescriptors::test_simple_linear_module 2025-08-26T21:17:17.4572735Z 2025-08-26T21:17:20.9582876Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:17:20.9586056Z import pkg_resources 2025-08-26T21:17:21.0826522Z Running test_subclass 1/1 ... [2025-08-26 21:17:21.082303] 2025-08-26T21:17:21.0826991Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:17:21.0829486Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_subclass.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:17:21.082669] 2025-08-26T21:17:25.1538076Z 2025-08-26T21:17:25.1539417Z test_subclass 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_subclass_1.1_7d4a8e6f895358a8_.log 2025-08-26T21:17:25.1616890Z Running 100 items in this shard: test/test_subclass.py::TestSubclass::test_deepcopy_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_deepcopy_wrapper_with_custom_strides_as_param_True, test/test_subclass.py::TestSubclass::test_lazy_module_base_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_diag_tensor_below, test/test_subclass.py::TestSubclass::test_lazy_module_logging_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_non_wrapper_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_sparse_tensor, test/test_subclass.py::TestSubclass::test_lazy_module_wrapper_with_custom_sizes, test/test_subclass.py::TestSubclass::test_lazy_module_wrapper_with_custom_strides, test/test_subclass.py::TestSubclass::test_module_optimization_base_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_diag_tensor_below, test/test_subclass.py::TestSubclass::test_module_optimization_logging_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_non_wrapper_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_sparse_tensor, test/test_subclass.py::TestSubclass::test_module_optimization_wrapper_with_custom_sizes, test/test_subclass.py::TestSubclass::test_module_optimization_wrapper_with_custom_strides, test/test_subclass.py::TestSubclass::test_non_rewrapping_torch_dispatch_subclass_as_parameter_throws_for_detach, test/test_subclass.py::TestSubclass::test_param_invariants_base_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_base_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_diag_tensor_below_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_diag_tensor_below_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_logging_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_logging_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_non_wrapper_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_non_wrapper_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_sparse_tensor_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_sparse_tensor_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_sizes_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_sizes_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_strides_tensor_requires_grad_False, test/test_subclass.py::TestSubclass::test_param_invariants_wrapper_with_custom_strides_tensor_requires_grad_True, test/test_subclass.py::TestSubclass::test_parametrization_base_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_base_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_diag_tensor_below_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_diag_tensor_below_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_logging_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_logging_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_non_wrapper_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_non_wrapper_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_sparse_tensor_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_sparse_tensor_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_sizes_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_sizes_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_strides_leave_parametrized_False, test/test_subclass.py::TestSubclass::test_parametrization_wrapper_with_custom_strides_leave_parametrized_True, test/test_subclass.py::TestSubclass::test_repr_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_repr_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_repr_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_repr_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_repr_wrapper_with_custom_strides_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_serialization_wrapper_with_custom_strides_as_param_True, test/test_subclass.py::TestSubclass::test_tensor_subclass_storage_data_accesses_throw, test/test_subclass.py::TestSubclass::test_type_propagation_base_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_base_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_diag_tensor_below_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_diag_tensor_below_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_logging_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_logging_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_non_wrapper_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_non_wrapper_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_sparse_tensor_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_sparse_tensor_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_sizes_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_sizes_as_param_True, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_strides_as_param_False, test/test_subclass.py::TestSubclass::test_type_propagation_wrapper_with_custom_strides_as_param_True 2025-08-26T21:17:25.1703388Z 2025-08-26T21:17:29.6461887Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:17:29.6465017Z import pkg_resources 2025-08-26T21:17:29.8320055Z Running test_itt 1/1 ... [2025-08-26 21:17:29.831569] 2025-08-26T21:17:29.8320833Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:17:29.8326634Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_itt.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:17:29.832323] 2025-08-26T21:17:34.4056313Z 2025-08-26T21:17:34.4057617Z test_itt 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_itt_1.1_d390263c890223d2_.log 2025-08-26T21:17:34.4058820Z Running 1 items in this shard: test/test_itt.py::TestItt::test_itt 2025-08-26T21:17:34.4059330Z 2025-08-26T21:17:38.3325253Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:17:38.3328425Z import pkg_resources 2025-08-26T21:17:38.5048401Z Running profiler/test_torch_tidy 1/1 ... [2025-08-26 21:17:38.504467] 2025-08-26T21:17:38.5049565Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:17:38.5053949Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'profiler/test_torch_tidy.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:17:38.504927] 2025-08-26T21:17:48.0826931Z 2025-08-26T21:17:48.0828494Z profiler/test_torch_tidy 1/1 was successful, full logs can be found in artifacts with path test/test-reports/profiler.test_torch_tidy_1.1_8897d2691918d283_.log 2025-08-26T21:17:48.0846977Z Running 22 items in this shard: test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocation_id_uniqueness, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocation_ids, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocation_ids_with_other_ops, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_allocations, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_extra_fields, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_impl_reuse, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_mkldnn_tensors, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_module_and_optimizer_ids, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_nnmodule_params, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_optimizer, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_optimizer_parameters_adam, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_optimizer_parameters_sgd, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_pointers_and_ids, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_refcounts, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_scalar_ins, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_sparse_tensors, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensor_lists, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensor_properties, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_full, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_keep_alive, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_scalar_args, test/profiler/test_torch_tidy.py::TestTorchTidyProfiler::test_tensorimpl_invalidation_set 2025-08-26T21:17:48.0864636Z 2025-08-26T21:17:51.8689063Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:17:51.8692881Z import pkg_resources 2025-08-26T21:17:51.9927336Z Running torch_np/numpy_tests/core/test_numeric 1/1 ... [2025-08-26 21:17:51.992288] 2025-08-26T21:17:51.9928953Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:17:51.9931680Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_numeric.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:17:51.992644] 2025-08-26T21:18:03.0784450Z 2025-08-26T21:18:03.0786236Z torch_np/numpy_tests/core/test_numeric 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_numeric_1.1_0b1a21b1108af405_.log 2025-08-26T21:18:03.1050597Z Running 273 items in this shard: test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_copies, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_negative_resize, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_repeats, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_reshape_from_zero, test/torch_np/numpy_tests/core/test_numeric.py::TestResize::test_zeroresize, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_choose, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_clip, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_compress, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_count_nonzero, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_cumproduct, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_diagonal, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_accuracy, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype2, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype3, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype4, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype5, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype6, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_dtype7, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-1, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-10, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_dunder_round_edgecases_val_2147483647_ndigits_-9, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_mean, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_prod, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_ptp, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_ravel, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_repeat, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_reshape, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round_2, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_round_py_consistency, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_searchsorted, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_size, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_squeeze, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_std, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_sum, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_swapaxes, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_take, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_trace, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_transpose, test/torch_np/numpy_tests/core/test_numeric.py::TestNonarrayArgs::test_var, test/torch_np/numpy_tests/core/test_numeric.py::TestIsscalar::test_isscalar, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_and_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_and_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_or_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_or_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_xor_eq, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_bitwise_xor_is, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolScalar::test_logical, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_all_any, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_logical_and_or_xor, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolArray::test_logical_not_abs, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolCmp::test_double, test/torch_np/numpy_tests/core/test_numeric.py::TestBoolCmp::test_float, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_default, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_divide_err, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_errobj, test/torch_np/numpy_tests/core/test_numeric.py::TestSeterr::test_set, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_D, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_F, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_d, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_e, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_floating_exceptions_typecode_f, test/torch_np/numpy_tests/core/test_numeric.py::TestFloatExceptions::test_warnings, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast_2, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_can_cast_values, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_coercion, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_coercion_2, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_promote_types_endian, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_result_type, test/torch_np/numpy_tests/core/test_numeric.py::TestTypes::test_tesult_type_2, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_2592_dtype0_count_10_error_index_5, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_2592_dtype0_count_10_error_index_9, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_empty_result, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_failed_itemsetting, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_lengths, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_too_few_items, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_types, test/torch_np/numpy_tests/core/test_numeric.py::TestFromiter::test_values, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_?, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_B, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_D, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_F, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_b, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_d, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_e, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_f, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_h, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_i, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_axis_all_dtypes_typecode_l, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_count_nonzero_list, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_countnonzero_axis_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_countnonzero_keepdims, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_onedim, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_onedim_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_trivial, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_trivial_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_twodim, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_zerod, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_nonzero_zerod_differs, test/torch_np/numpy_tests/core/test_numeric.py::TestNonzeroAndCountNonzero::test_sparse, test/torch_np/numpy_tests/core/test_numeric.py::TestIndex::test_boolean, test/torch_np/numpy_tests/core/test_numeric.py::TestIndex::test_boolean_edgecase, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_large_neg_int64, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_neg_width_boundaries, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_negative, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_positive, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_sufficient_width, test/torch_np/numpy_tests/core/test_numeric.py::TestBinaryRepr::test_zero, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_base3, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_base_range, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_negative, test/torch_np/numpy_tests/core/test_numeric.py::TestBaseRepr::test_positive, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equal, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equal_equal_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_array_equiv, test/torch_np/numpy_tests/core/test_numeric.py::TestArrayComparisons::test_none_compares_elementwise, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_array_double, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_func_takes_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_inplace_array, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_inplace_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_non_contig, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_property, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_scalar_nan_propagation_arr0_amin0_amax0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin2_amax2, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin_1_amax1, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_value_min_max_flip_amin_1_amax_0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_array_int32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_array_outint32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_memory_overlap, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple2, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_simple_int32, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_clip_with_out_transposed, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_noncontig_inplace, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_D, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_F, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_2_dtype_e, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_?, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_B, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_b, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_d, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_f, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_h, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_i, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_ones_pathological_dtype_l, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_double, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_inplace_01, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_inplace_02, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_inout_casting0, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_inout_casting_unsafe, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int32_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int64_inout, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_int64_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_nonnative, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_simple_out, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_01, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_02, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_03, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_04, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_05, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_06, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_07, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_08, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_09, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_10, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_11, test/torch_np/numpy_tests/core/test_numeric.py::TestClip::test_type_cast_12, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_equalnan, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_ip_allclose, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_ip_not_allclose, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_min_int, test/torch_np/numpy_tests/core/test_numeric.py::TestAllclose::test_no_parameter_modification, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_equal_nan, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_all_isclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_isclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_isclose_allclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_ip_none_isclose, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_no_parameter_modification, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_non_finite_scalar, test/torch_np/numpy_tests/core/test_numeric.py::TestIsclose::test_scalar_return, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_basic, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_ddof1, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_ddof2, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_out_scalar, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVar::test_scalars, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVarComplex::test_basic, test/torch_np/numpy_tests/core/test_numeric.py::TestStdVarComplex::test_scalars, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_for_reference_leak, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_full, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_ones, test/torch_np/numpy_tests/core/test_numeric.py::TestCreationFuncs::test_zeros, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc0_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc0_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc1_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc1_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc2_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc2_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc3_dtype0, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_dtype_str_bytes_likefunc3_dtype1, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_empty_like, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_filled_like, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_ones_like, test/torch_np/numpy_tests/core/test_numeric.py::TestLikeFuncs::test_zeros_like, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_complex, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_float, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_mode, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_no_overwrite, test/torch_np/numpy_tests/core/test_numeric.py::TestCorrelate::test_zero_size, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_mode, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_no_overwrite, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_numpy_doc_examples, test/torch_np/numpy_tests/core/test_numeric.py::TestConvolve::test_object, test/torch_np/numpy_tests/core/test_numeric.py::TestDtypePositional::test_dtype_positional, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_2D, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_list, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_0, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_1, test/torch_np/numpy_tests/core/test_numeric.py::TestArgwhere::test_nd_nd_2, test/torch_np/numpy_tests/core/test_numeric.py::TestStringFunction::test_set_string_function, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll1d, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll2d, test/torch_np/numpy_tests/core/test_numeric.py::TestRoll::test_roll_empty, test/torch_np/numpy_tests/core/test_numeric.py::TestRollaxis::test_exceptions, test/torch_np/numpy_tests/core/test_numeric.py::TestRollaxis::test_results, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_errors, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_multiples, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_new_position, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_move_to_end, test/torch_np/numpy_tests/core/test_numeric.py::TestMoveaxis::test_preserve_order, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_2x2, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_2x3, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_3x3, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_broadcasting, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_broadcasting_shapes, test/torch_np/numpy_tests/core/test_numeric.py::TestCross::test_uint8_int32_mixed_dtypes, test/torch_np/numpy_tests/core/test_numeric.py::TestOuterMisc::test_outer_out_param, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype0_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype1_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype2_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims0, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims1, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_return_type_dtype3_dims2, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_scalar_input, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_simple, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_single_input, test/torch_np/numpy_tests/core/test_numeric.py::TestIndices::test_sparse, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_C_and_F_simul, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_non_array_input, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_require_each, test/torch_np/numpy_tests/core/test_numeric.py::TestRequire::test_unknown_requirement, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_error_kwargs, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_in_args, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_broadcast_single_arg, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_number_of_arguments, test/torch_np/numpy_tests/core/test_numeric.py::TestBroadcast::test_shape_mismatch_error_message, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimension, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimension_einsum, test/torch_np/numpy_tests/core/test_numeric.py::TestTensordot::test_zero_dimensional 2025-08-26T21:18:03.1259933Z 2025-08-26T21:18:06.9839439Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:18:06.9842880Z import pkg_resources 2025-08-26T21:18:07.1065806Z Running test_bundled_inputs 1/1 ... [2025-08-26 21:18:07.106254] 2025-08-26T21:18:07.1066284Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:18:07.1068714Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_bundled_inputs.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:18:07.106596] 2025-08-26T21:18:11.4282956Z 2025-08-26T21:18:11.4284281Z test_bundled_inputs 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_bundled_inputs_1.1_d90161e6fcecdc8a_.log 2025-08-26T21:18:11.4290036Z Running 12 items in this shard: test/test_bundled_inputs.py::TestBundledInputs::test_bad_inputs, test/test_bundled_inputs.py::TestBundledInputs::test_dict_args, test/test_bundled_inputs.py::TestBundledInputs::test_double_augment_fail, test/test_bundled_inputs.py::TestBundledInputs::test_double_augment_non_mutator, test/test_bundled_inputs.py::TestBundledInputs::test_double_augment_success, test/test_bundled_inputs.py::TestBundledInputs::test_large_tensor_with_inflation, test/test_bundled_inputs.py::TestBundledInputs::test_multiple_methods_with_inputs, test/test_bundled_inputs.py::TestBundledInputs::test_multiple_methods_with_inputs_both_defined_failure, test/test_bundled_inputs.py::TestBundledInputs::test_multiple_methods_with_inputs_neither_defined_failure, test/test_bundled_inputs.py::TestBundledInputs::test_non_tensors, test/test_bundled_inputs.py::TestBundledInputs::test_rejected_tensors, test/test_bundled_inputs.py::TestBundledInputs::test_single_tensors 2025-08-26T21:18:11.4294279Z 2025-08-26T21:18:14.7956242Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:18:14.7959486Z import pkg_resources 2025-08-26T21:18:14.9183425Z Running test_masked 1/1 ... [2025-08-26 21:18:14.917979] 2025-08-26T21:18:14.9184228Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:18:14.9186785Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_masked.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:18:14.918324] 2025-08-26T21:18:56.0884712Z 2025-08-26T21:18:56.0885776Z test_masked 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_masked_1.1_3e79e3d1666940be_.log 2025-08-26T21:18:56.0955130Z Running 194 items in this shard: test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amax_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_amin_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_mean_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_prod_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_coo_masked_sum_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amax_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_amin_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_mean_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_prod_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_sparse_csr_masked_sum_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amax_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_amin_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_mean_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_prod_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_bool, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_float16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_float32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_float64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int16, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int32, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int64, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_int8, test/test_masked.py::TestMaskedCPU::test_mask_layout_strided_masked_sum_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_log_softmax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_norm_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_normalize_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmax_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_softmin_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_int8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_std_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_bfloat16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_complex128, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_complex64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_float16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_float32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_float64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int16, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int32, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int64, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_int8, test/test_masked.py::TestMaskedCPU::test_reference_masked_masked_var_cpu_uint8, test/test_masked.py::TestMaskedCPU::test_where_coo_fill_value_0_cpu, test/test_masked.py::TestMaskedCPU::test_where_coo_fill_value_123_cpu, test/test_masked.py::TestMaskedCPU::test_where_csr_fill_value_0_cpu, test/test_masked.py::TestMaskedCPU::test_where_csr_fill_value_123_cpu, test/test_masked.py::TestMaskedCPU::test_where_hybrid_coo_fill_value_0_cpu, test/test_masked.py::TestMaskedCPU::test_where_hybrid_coo_fill_value_123_cpu 2025-08-26T21:18:56.1022648Z 2025-08-26T21:18:59.4887138Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:18:59.4888736Z import pkg_resources 2025-08-26T21:18:59.6115107Z Running test_monitor 1/1 ... [2025-08-26 21:18:59.611255] 2025-08-26T21:18:59.6115548Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:18:59.6117999Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_monitor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:18:59.611589] 2025-08-26T21:19:03.3310281Z 2025-08-26T21:19:03.3311279Z test_monitor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_monitor_1.1_06c9b30edd297f64_.log 2025-08-26T21:19:03.3313821Z Running 6 items in this shard: test/test_monitor.py::TestMonitor::test_event_handler, test/test_monitor.py::TestMonitor::test_fixed_count_stat, test/test_monitor.py::TestMonitor::test_interval_stat, test/test_monitor.py::TestMonitor::test_log_event, test/test_monitor.py::TestMonitor::test_wait_counter, test/test_monitor.py::TestMonitorTensorboard::test_event_handler 2025-08-26T21:19:03.3315433Z 2025-08-26T21:19:06.9946723Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:19:06.9949653Z import pkg_resources 2025-08-26T21:19:07.1189494Z Running test_sympy_utils 1/1 ... [2025-08-26 21:19:07.118556] 2025-08-26T21:19:07.1190286Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:19:07.1192666Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_sympy_utils.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:19:07.118928] 2025-08-26T21:19:30.5158680Z 2025-08-26T21:19:30.5159624Z test_sympy_utils 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_sympy_utils_1.1_4351508896ed18be_.log 2025-08-26T21:19:30.5225589Z Running 209 items in this shard: test/test_sympy_utils.py::TestNumbers::test_float_cast, test/test_sympy_utils.py::TestNumbers::test_int_infinity, test/test_sympy_utils.py::TestNumbers::test_lt_self, test/test_sympy_utils.py::TestNumbers::test_mixed_oo_int_oo, test/test_sympy_utils.py::TestNumbers::test_relation, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_and_, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_bitwise_and, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_bitwise_or, test/test_sympy_utils.py::TestValueRanges::test_binary_bool_ref_range_fn_or_, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_add_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_add_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_and_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_and_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_or_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_bitwise_or_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_floordiv_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_floordiv_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_maximum_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_maximum_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_minimum_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_minimum_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mod_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mod_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mul_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_mul_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_by_natural_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_by_natural_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_pow_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_sub_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_sub_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_truediv_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_fn_truediv_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_add, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_bitwise_and, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_bitwise_or, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_eq, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_floordiv, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_ge, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_gt, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_le, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_lt, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_maximum, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_minimum, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_mod, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_mul, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_ne, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_pow, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_pow_by_natural, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_sub, test/test_sympy_utils.py::TestValueRanges::test_binary_ref_range_fn_truediv, test/test_sympy_utils.py::TestValueRanges::test_bitwise_ref_range_fn_bitwise_and, test/test_sympy_utils.py::TestValueRanges::test_bitwise_ref_range_fn_bitwise_or, test/test_sympy_utils.py::TestValueRanges::test_mul_zero_unknown, test/test_sympy_utils.py::TestValueRanges::test_pow_half, test/test_sympy_utils.py::TestValueRanges::test_unary_bool_ref_range_fn_not_, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_abs_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_abs_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_ceil_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_ceil_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_exp_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_exp_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_floor_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_floor_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_log_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_log_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_neg_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_neg_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_reciprocal_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_reciprocal_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_sqrt_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_sqrt_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_square_dtype_float, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_fn_square_dtype_int, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_abs, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_ceil, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_exp, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_floor, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_log, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_neg, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_reciprocal, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_sqrt, test/test_sympy_utils.py::TestValueRanges::test_unary_ref_range_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_abs, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_add, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_and_, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_bitwise_and, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_bitwise_or, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_ceil, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_eq, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_exp, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_floor, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_floordiv, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_ge, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_gt, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_le, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_log, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_lt, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_maximum, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_minimum, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_mod, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_mul, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_ne, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_neg, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_not_, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_or_, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_pow, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_pow_by_natural, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_reciprocal, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_sqrt, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_sub, test/test_sympy_utils.py::TestSympyInterp::test_interp_fn_truediv, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_abs, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_add, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_and_, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_bitwise_and, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_bitwise_or, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_ceil, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_eq, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_exp, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_floor, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_floordiv, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_ge, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_gt, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_le, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_log, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_lt, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_maximum, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_minimum, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_mod, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_mul, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_ne, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_neg, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_not_, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_or_, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_pow, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_pow_by_natural, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_reciprocal, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_sqrt, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_sub, test/test_sympy_utils.py::TestSympyInterp::test_python_interp_fx_fn_truediv, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_abs, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_add, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_and_, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_bitwise_and, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_bitwise_or, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_ceil, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_eq, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_exp, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_floor, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_floordiv, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_ge, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_gt, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_le, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_log, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_lt, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_maximum, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_minimum, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_mod, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_mul, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_ne, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_neg, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_not_, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_or_, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_pow, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_pow_by_natural, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_reciprocal, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_sqrt, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_square, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_sub, test/test_sympy_utils.py::TestSympyInterp::test_tensor_interp_fn_truediv, test/test_sympy_utils.py::TestSympySolve::test_addition, test/test_sympy_utils.py::TestSympySolve::test_floordiv_Equality, test/test_sympy_utils.py::TestSympySolve::test_floordiv_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_LessThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_floordiv_Unequality, test/test_sympy_utils.py::TestSympySolve::test_floordiv_eq_simplify, test/test_sympy_utils.py::TestSympySolve::test_give_up, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_Equality, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_Unequality, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_LessThan, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_multiplication_division_inequality_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_Equality, test/test_sympy_utils.py::TestSympySolve::test_noop_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_LessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_Unequality, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_Equality, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_GreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_LessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_StrictGreaterThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_StrictLessThan, test/test_sympy_utils.py::TestSympySolve::test_noop_rhs_Unequality, test/test_sympy_utils.py::TestSympySolve::test_simple_floordiv_gcd, test/test_sympy_utils.py::TestSympySolve::test_z3_proof_floordiv_eq_simplify, test/test_sympy_utils.py::TestSympyFunctions::test_pickle, test/test_sympy_utils.py::TestSingletonInt::test_basic, test/test_sympy_utils.py::TestIdentity::test_cast_identity_float, test/test_sympy_utils.py::TestIdentity::test_cast_identity_illegal, test/test_sympy_utils.py::TestIdentity::test_cast_identity_int, test/test_sympy_utils.py::TestIdentity::test_expand_identity, test/test_sympy_utils.py::TestTypedExpr::test_typed_expr 2025-08-26T21:19:30.5287375Z 2025-08-26T21:19:33.5805094Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:19:33.5808321Z import pkg_resources 2025-08-26T21:19:33.7036061Z Running torch_np/numpy_tests/lib/test_function_base 1/1 ... [2025-08-26 21:19:33.703229] 2025-08-26T21:19:33.7037135Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:19:33.7039818Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_function_base.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:19:33.703585] 2025-08-26T21:19:39.8296804Z 2025-08-26T21:19:39.8298702Z torch_np/numpy_tests/lib/test_function_base 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_function_base_1.1_ebf6f64a8f08c4a7_.log 2025-08-26T21:19:39.8757219Z Running 505 items in this shard: test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestRot90::test_rotation_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis0, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis1, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_3d_swap_axis2, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_4d, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_basic_lr, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_basic_ud, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_default_axis, test/torch_np/numpy_tests/lib/test_function_base.py::TestFlip::test_multiple_axes, test/torch_np/numpy_tests/lib/test_function_base.py::TestAny::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAny::test_nd, test/torch_np/numpy_tests/lib/test_function_base.py::TestAll::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestAll::test_nd, test/torch_np/numpy_tests/lib/test_function_base.py::TestCopy::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestCopy::test_order, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_average_class_without_dtype, test/torch_np/numpy_tests/lib/test_function_base.py::TestAverage::test_basic, 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test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single_item_array_[1], test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single_item_array_array([1]), test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_single_item_array_non_int, test/torch_np/numpy_tests/lib/test_function_base.py::TestDelete::test_slices, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_args, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_badargs, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_decreasing_unsigned_int_f_dtype0, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_signed_int_big_jump_f_dtype0, test/torch_np/numpy_tests/lib/test_function_base.py::TestGradient::test_f_signed_int_big_jump_f_dtype1, 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test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype7_expected_dtype7_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_B_expected_dtype0_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_b_expected_dtype1_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_h_expected_dtype2_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_i_expected_dtype3_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_averaged_inverted_cdf_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_closest_observation_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_hazen_expected_27_5, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_interpolated_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_inverted_cdf_expected_20, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_linear_expected_29, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_median_unbiased_expected_27, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_normal_unbiased_expected_27_125, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_interpolation_input_dtype_l_expected_dtype4_method_weibull_expected_26, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_nan_1D_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_nan_1D_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_linear_nan_1D_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_lower_higher_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_midpoint_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nan_behavior, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nan_q, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_d, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_e, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_f, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_nearest_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_no_p_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_out, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_out_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_empty_dim, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_list, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_no_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_out, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_percentile_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_scalar_q, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_scalar_q_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestPercentile::test_sequence, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_complex, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_correct_quantile_value, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_fraction, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_max_ulp, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_no_p_overwrite, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_hypo, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_averaged_inverted_cdf, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_closest_observation, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_hazen, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_higher, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_interpolated_inverted_cdf, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_inverted_cdf, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_linear, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_lower, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_median_unbiased, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_midpoint, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_nearest, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_normal_unbiased, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_monotonic_method_weibull, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_B, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_b, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_h, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_i, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_preserve_int_type_dtype_l, test/torch_np/numpy_tests/lib/test_function_base.py::TestQuantile::test_quantile_scalar_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_array_like, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_axis_keyword, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_basic, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_basic_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_empty, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_extended_axis, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_extended_axis_invalid, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis0, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis3, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis4, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_keepdims_out_axis_1, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior_2, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_nan_behavior_3, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_out, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_out_nan, test/torch_np/numpy_tests/lib/test_function_base.py::TestMedian::test_overwrite_keyword, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_complex, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_B_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_H_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_b_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_g_type_out_G, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_h_type_out_F, test/torch_np/numpy_tests/lib/test_function_base.py::TestSortComplex::test_sort_real_type_in_l_type_out_D 2025-08-26T21:19:39.9207486Z 2025-08-26T21:19:43.2479775Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:19:43.2482923Z import pkg_resources 2025-08-26T21:19:43.3700531Z Running functorch/test_vmap_registrations 1/1 ... [2025-08-26 21:19:43.369654] 2025-08-26T21:19:43.3701525Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:19:43.3704415Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'functorch/test_vmap_registrations.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:19:43.370040] 2025-08-26T21:19:52.4010856Z 2025-08-26T21:19:52.4012705Z functorch/test_vmap_registrations 1/1 was successful, full logs can be found in artifacts with path test/test-reports/functorch.test_vmap_registrations_1.1_20166e488025dde0_.log 2025-08-26T21:19:52.6230220Z Running 1721 items in this shard: test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::cat], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::get_first], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[_test::leaky_relu], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_register_a_batching_rule_for_composite_implicit_autograd_[aten::__and__.Scalar], 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test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_erf], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_erfc], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_erfinv], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_exp2], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_expit], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_expm1], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_gammainc], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_gammaincc], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_gammaln], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_i0], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_log1p], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_log_softmax], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_logit], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_logsumexp], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_multigammaln], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_ndtr], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_polygamma], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_psi], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_round], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_sinc], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_softmax], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_xlogy.other_scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_xlogy.self_scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::special_xlogy], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::split.sizes], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::square], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::square_], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sspaddmm], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::std_mean], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::stft.center], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::stft], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::stride.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract_.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::subtract_.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sum_to_size], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::svd.U], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::svd], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapaxes], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapaxes_], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapdims], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::swapdims_], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_numel], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_size.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_storage_offset], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::sym_stride.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::take_along_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensor_split.indices], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensor_split.sections], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensor_split.tensor_indices_or_sections], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tensordot], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::thnn_conv2d], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::tile], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.device], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.dtype], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.dtype_layout], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to.other], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to_dense], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to_dense_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::to_mkldnn_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trace_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapezoid.dx], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapezoid.x], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapz.dx], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::trapz.x], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::triplet_margin_loss], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide_.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::true_divide_.Tensor], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::type_as], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unflatten.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unflatten_dense_tensors], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::unsafe_chunk], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_bicubic2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_bilinear2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_linear1d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest1d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest2d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_nearest3d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::upsample_trilinear3d.vec], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::value_selecting_reduction_backward], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vander], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.correction_names], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean.names_dim], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::var_mean], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::view_as], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vsplit.array], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vsplit.int], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::vstack], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.ScalarOther], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.ScalarSelf], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where.Scalar], test/functorch/test_vmap_registrations.py::TestFunctorchDispatcher::test_unimplemented_batched_registrations_[aten::where] 2025-08-26T21:19:52.8353424Z 2025-08-26T21:19:56.3126361Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:19:56.3129493Z import pkg_resources 2025-08-26T21:19:56.4354409Z Running torch_np/test_indexing 1/1 ... [2025-08-26 21:19:56.435040] 2025-08-26T21:19:56.4356470Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:19:56.4358393Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:19:56.435442] 2025-08-26T21:20:03.7126231Z 2025-08-26T21:20:03.7132875Z torch_np/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.test_indexing_1.1_d605d8099553eaa6_.log 2025-08-26T21:20:03.7155297Z Running 5 items in this shard: test/torch_np/test_indexing.py::TestAdvancedIndexing::test_advanced_separation_patterns, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_broadcast_and_numpy_compatibility, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_comprehensive_indexing, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_ellipsis, test/torch_np/test_indexing.py::TestAdvancedIndexing::test_special_index_types 2025-08-26T21:20:03.7166625Z 2025-08-26T21:20:08.4885374Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:20:08.4888772Z import pkg_resources 2025-08-26T21:20:08.6708153Z Running cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 ... [2025-08-26 21:20:08.670346] 2025-08-26T21:20:08.6709670Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:20:08.6712502Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:20:08.670778] 2025-08-26T21:20:17.0010100Z 2025-08-26T21:20:17.0012620Z cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp_extensions.libtorch_agnostic_extension.test.test_libtorch_agnostic_1.1_50a5e02b4c8c6b46_.log 2025-08-26T21:20:17.0043105Z Running 23 items in this shard: test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_default_constructor_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_device_guard_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_device_guard_set_index_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_divide_neg_exp_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_exp_neg_is_leaf_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_fill_infinity_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_get_current_device_index_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_identity_does_not_hog_memory_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_is_contiguous_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_abs_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_amax_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_amax_vec_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_empty_like_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_is_cpu_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_narrow_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_new_empty_dtype_variant_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_ones_like_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_pad_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_transpose_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_my_zero__cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_neg_exp_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_slow_sgd_cpu, test/cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic.py::TestLibtorchAgnosticCPU::test_stream_cpu 2025-08-26T21:20:17.0071770Z 2025-08-26T21:20:20.4680915Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:20:20.4683962Z import pkg_resources 2025-08-26T21:20:20.5910869Z Running test_mkldnn_fusion 1/1 ... [2025-08-26 21:20:20.590710] 2025-08-26T21:20:20.5913057Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:20:20.5915102Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_mkldnn_fusion.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:20:20.591075] 2025-08-26T21:20:28.9790732Z 2025-08-26T21:20:28.9792384Z test_ops_gradients 2/2 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_gradients_2.2_321e04f674972d5d_.log 2025-08-26T21:20:29.2153762Z Running 2660 items in this shard: test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_H_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyCatCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpyMulCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_NumpySplitCopyCustomOp_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad_T_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___getitem___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___radd___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rdiv___cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rmatmul___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rmul___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad___rsub___cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__batch_norm_with_update_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__segment_reduce_offsets_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__unsafe_masked_index_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__unsafe_masked_index_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_fn_fail_gradgrad__unsafe_masked_index_put_accumulate_cpu_complex128, 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test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tensor_split_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tensordot_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tensordot_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tile_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_tile_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_to_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_topk_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trace_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trace_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_transpose_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapezoid_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapezoid_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapz_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trapz_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_triangular_solve_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_triu_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_triu_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_true_divide_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_trunc_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unbind_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unbind_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unfold_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unfold_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unfold_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_uniform_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_uniform_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unique_consecutive_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unique_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsqueeze_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_unsqueeze_copy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_mean_unbiased_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_mean_unbiased_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_unbiased_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_var_unbiased_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_as_real_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_copy_cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_view_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vsplit_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_vstack_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_xlogy_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zero__cpu_complex128, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zeros_cpu_float64, test/test_ops_gradients.py::TestBwdGradientsCPU::test_inplace_gradgrad_zeros_like_cpu_float64 2025-08-26T21:20:29.4418723Z 2025-08-26T21:20:33.8032508Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:20:33.8035711Z import pkg_resources 2025-08-26T21:20:34.0287951Z Running test_import_stats 1/1 ... [2025-08-26 21:20:34.028343] 2025-08-26T21:20:34.0288778Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:20:34.0290633Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_import_stats.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:20:34.028717] 2025-08-26T21:20:41.3565753Z 2025-08-26T21:20:41.3567034Z test_import_stats 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_import_stats_1.1_65ef0f3c0c4dd786_.log 2025-08-26T21:20:41.3568355Z Running 2 items in this shard: test/test_import_stats.py::TestImportTime::test_time_cuda_device_count, test/test_import_stats.py::TestImportTime::test_time_import_torch 2025-08-26T21:20:41.3569161Z 2025-08-26T21:20:45.4681417Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:20:45.4685405Z import pkg_resources 2025-08-26T21:20:45.6433627Z Running test_tensorboard 1/1 ... [2025-08-26 21:20:45.642904] 2025-08-26T21:20:45.6434448Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:20:45.6438630Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_tensorboard.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:20:45.643444] 2025-08-26T21:20:52.3963086Z 2025-08-26T21:20:52.3964424Z test_tensorboard 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_tensorboard_1.1_5e263c2e9c163e0c_.log 2025-08-26T21:20:52.4000497Z Running 50 items in this shard: test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_autograd_np, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_histogram, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_histogram_raw, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_np, test/test_tensorboard.py::TestTensorBoardPyTorchNumpy::test_pytorch_write, test/test_tensorboard.py::TestTensorBoardUtils::test_convert_to_HWC_dtype_remains_same, test/test_tensorboard.py::TestTensorBoardUtils::test_numpy_vid_uint8, test/test_tensorboard.py::TestTensorBoardUtils::test_prepare_video, test/test_tensorboard.py::TestTensorBoardUtils::test_to_HWC, test/test_tensorboard.py::TestTensorBoardWriter::test_writer, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_pathlib, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_summary_writer_close, test/test_tensorboard.py::TestTensorBoardSummaryWriter::test_summary_writer_ctx, test/test_tensorboard.py::TestTensorBoardEmbedding::test_embedding, test/test_tensorboard.py::TestTensorBoardEmbedding::test_embedding_64, test/test_tensorboard.py::TestTensorBoardSummary::test_audio, test/test_tensorboard.py::TestTensorBoardSummary::test_custom_scalars, test/test_tensorboard.py::TestTensorBoardSummary::test_empty_input, test/test_tensorboard.py::TestTensorBoardSummary::test_float32_image, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_auto, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_doane, test/test_tensorboard.py::TestTensorBoardSummary::test_histogram_fd, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_3_channel_batched, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_boxes, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_one_channel, test/test_tensorboard.py::TestTensorBoardSummary::test_image_with_one_channel_batched, test/test_tensorboard.py::TestTensorBoardSummary::test_image_without_channel, test/test_tensorboard.py::TestTensorBoardSummary::test_list_input, test/test_tensorboard.py::TestTensorBoardSummary::test_mesh, test/test_tensorboard.py::TestTensorBoardSummary::test_scalar_new_style, test/test_tensorboard.py::TestTensorBoardSummary::test_text, test/test_tensorboard.py::TestTensorBoardSummary::test_uint8_image, test/test_tensorboard.py::TestTensorBoardSummary::test_video, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_mlp_graph, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_nested_nn_squential, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_pytorch_graph, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_pytorch_graph_dict_input, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_torchvision_smoke, test/test_tensorboard.py::TestTensorBoardPytorchGraph::test_wrong_input_size, test/test_tensorboard.py::TestTensorBoardFigure::test_figure, test/test_tensorboard.py::TestTensorBoardFigure::test_figure_list, test/test_tensorboard.py::TestTensorBoardNumpy::test_pytorch_np_expect_fail, test/test_tensorboard.py::TestTensorBoardNumpy::test_scalar, test/test_tensorboard.py::TestTensorProtoSummary::test_complex_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_empty_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_float_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_half_tensor_proto_bfloat16_proto_type_14, test/test_tensorboard.py::TestTensorProtoSummary::test_half_tensor_proto_float16_proto_type_19, test/test_tensorboard.py::TestTensorProtoSummary::test_int_tensor_proto, test/test_tensorboard.py::TestTensorProtoSummary::test_scalar_tensor_proto 2025-08-26T21:20:52.4035576Z 2025-08-26T21:20:56.9881945Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:20:56.9885092Z import pkg_resources 2025-08-26T21:20:57.1184722Z Running nn/test_embedding 1/1 ... [2025-08-26 21:20:57.118011] 2025-08-26T21:20:57.1185580Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:20:57.1187650Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_embedding.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:20:57.118410] 2025-08-26T21:21:09.9631775Z 2025-08-26T21:21:09.9632937Z test_mkldnn_fusion 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_mkldnn_fusion_1.1_257c313c3f03a289_.log 2025-08-26T21:21:09.9636141Z Running 8 items in this shard: test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_binary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_transpose_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_nnc, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_conv_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_linear_binary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_linear_unary_fusion_ops, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_single_conv, test/test_mkldnn_fusion.py::TestMkldnnFusion::test_unsupported_conv 2025-08-26T21:21:09.9638961Z 2025-08-26T21:21:10.0071413Z 2025-08-26T21:21:10.0073836Z nn/test_embedding 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_embedding_1.1_328dde84b11c282a_.log 2025-08-26T21:21:10.0253620Z Running 165 items in this shard: test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_bag_from_pretrained, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_bag_from_pretrained_padding_idx, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_bag_functional, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_bag_padding_idx_error, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_float32, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_float64, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_int16, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_int32, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_int64, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_int8, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_options, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_padding_idx, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_from_pretrained_uint8, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_functional, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_max_norm, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_max_norm_unsorted_repeating_indices, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_sparse_basic, test/nn/test_embedding.py::TestEmbeddingNN::test_embedding_sparse_empty_tensor, test/nn/test_embedding.py::TestEmbeddingNN::test_embeddingbag_from_pretrained, test/nn/test_embedding.py::TestEmbeddingNN::test_embeddingbag_from_pretrained_options, test/nn/test_embedding.py::TestEmbeddingNN::test_embeddingbag_include_last_offset, test/nn/test_embedding.py::TestEmbeddingNN::test_large_tensors, test/nn/test_embedding.py::TestEmbeddingNN::test_move_sparse_half_embedding, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int32_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_empty_per_sample_weights_and_offsets_cpu_int64_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int32_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_new_offsets_cpu_int64_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_no_offsets_cpu_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_no_offsets_cpu_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_no_offsets_cpu_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_no_offsets_cpu_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int32_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_and_offsets_cpu_int64_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_failures_cpu_int32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_failures_cpu_int32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_failures_cpu_int64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_EmbeddingBag_per_sample_weights_failures_cpu_int64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_backward_cpu_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_1D_padding_idx_cpu_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_1D_padding_idx_cpu_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_2D_padding_idx_cpu_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_2D_padding_idx_cpu_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_bfloat16_cpu_int32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_bfloat16_cpu_int32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_bfloat16_cpu_int64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_bfloat16_cpu_int64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int32_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_device_cpu_int64_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_dimension_errors_cpu, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_empty_input_cpu_int32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_empty_input_cpu_int32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_empty_input_cpu_int64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_empty_input_cpu_int64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_half_cpu_int32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_half_cpu_int32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_half_cpu_int64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_half_cpu_int64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int32_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int32_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int32_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int32_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int32_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int64_bfloat16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int64_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int64_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_non_contiguous_weight_cpu_int64_int64_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_max_cpu_float32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_max_cpu_float32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_max_cpu_float64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_max_cpu_float64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_mean_cpu_float32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_mean_cpu_float32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_mean_cpu_float64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_mean_cpu_float64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_sum_cpu_float32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_sum_cpu_float32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_sum_cpu_float64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx0_mode_sum_cpu_float64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_max_cpu_float32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_max_cpu_float32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_max_cpu_float64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_max_cpu_float64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_mean_cpu_float32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_mean_cpu_float32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_mean_cpu_float64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_mean_cpu_float64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_sum_cpu_float32_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_sum_cpu_float32_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_sum_cpu_float64_int32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_out_of_bounds_idx_padding_idx_0_mode_sum_cpu_float64_int64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_per_sample_weights_grad_bag_use_grad_False_per_sample_weights_use_grad_False_cpu, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_per_sample_weights_grad_bag_use_grad_False_per_sample_weights_use_grad_True_cpu, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_per_sample_weights_grad_bag_use_grad_True_per_sample_weights_use_grad_False_cpu, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_bag_per_sample_weights_grad_bag_use_grad_True_per_sample_weights_use_grad_True_cpu, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_dense_grad_cpu, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_max_norm_backward_cpu_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_max_norm_device_cpu_float16, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_max_norm_device_cpu_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_max_norm_device_cpu_float64, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_max_norm_fwd_AD_cpu_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_padding_idx_cpu_float32, test/nn/test_embedding.py::TestEmbeddingNNDeviceTypeCPU::test_embedding_scalar_weight_error_cpu 2025-08-26T21:21:10.0431490Z 2025-08-26T21:21:13.2999169Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:13.3002426Z import pkg_resources 2025-08-26T21:21:13.4262199Z Running nn/test_dropout 1/1 ... [2025-08-26 21:21:13.425862] 2025-08-26T21:21:13.4263013Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:13.4265819Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'nn/test_dropout.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:13.426243] 2025-08-26T21:21:13.7934997Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:13.7938201Z import pkg_resources 2025-08-26T21:21:13.9770705Z Running torch_np/numpy_tests/lib/test_type_check 1/1 ... [2025-08-26 21:21:13.976631] 2025-08-26T21:21:13.9771788Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:13.9774769Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_type_check.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:13.977086] 2025-08-26T21:21:17.3962806Z 2025-08-26T21:21:17.3964297Z nn/test_dropout 1/1 was successful, full logs can be found in artifacts with path test/test-reports/nn.test_dropout_1.1_f5e88c9a9c2f9209_.log 2025-08-26T21:21:17.3971082Z Running 9 items in this shard: test/nn/test_dropout.py::TestDropoutNN::test_AlphaDropout, test/nn/test_dropout.py::TestDropoutNN::test_FeatureAlphaDropout, test/nn/test_dropout.py::TestDropoutNN::test_invalid_dropout_p, test/nn/test_dropout.py::TestDropoutNN::test_native_dropout_corner_case, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout1d_cpu_float64, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout2d_cpu, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout3d_cpu, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_Dropout_cpu, test/nn/test_dropout.py::TestDropoutNNDeviceTypeCPU::test_empty_dropout_cpu 2025-08-26T21:21:17.3976786Z 2025-08-26T21:21:17.6965403Z 2025-08-26T21:21:17.6966561Z torch_np/numpy_tests/lib/test_type_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_type_check_1.1_71b626e53607457b_.log 2025-08-26T21:21:17.6983953Z Running 50 items in this shard: test/torch_np/numpy_tests/lib/test_type_check.py::TestCommonType::test_basic, test/torch_np/numpy_tests/lib/test_type_check.py::TestMintypecode::test_default_1, test/torch_np/numpy_tests/lib/test_type_check.py::TestMintypecode::test_default_2, test/torch_np/numpy_tests/lib/test_type_check.py::TestMintypecode::test_default_3, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsscalar::test_basic, test/torch_np/numpy_tests/lib/test_type_check.py::TestReal::test_cmplx, test/torch_np/numpy_tests/lib/test_type_check.py::TestReal::test_real, test/torch_np/numpy_tests/lib/test_type_check.py::TestImag::test_cmplx, test/torch_np/numpy_tests/lib/test_type_check.py::TestImag::test_real, test/torch_np/numpy_tests/lib/test_type_check.py::TestIscomplex::test_fail, test/torch_np/numpy_tests/lib/test_type_check.py::TestIscomplex::test_pass, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsreal::test_fail, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsreal::test_isreal_real, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsreal::test_pass, test/torch_np/numpy_tests/lib/test_type_check.py::TestIscomplexobj::test_basic, test/torch_np/numpy_tests/lib/test_type_check.py::TestIscomplexobj::test_list, test/torch_np/numpy_tests/lib/test_type_check.py::TestIscomplexobj::test_scalar, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsrealobj::test_basic, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsnan::test_complex, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsnan::test_complex1, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsnan::test_goodvalues, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsnan::test_ind, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsnan::test_integer, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsnan::test_neginf, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsnan::test_posinf, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsfinite::test_complex, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsfinite::test_complex1, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsfinite::test_goodvalues, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsfinite::test_ind, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsfinite::test_integer, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsfinite::test_neginf, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsfinite::test_posinf, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsinf::test_goodvalues, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsinf::test_ind, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsinf::test_neginf, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsinf::test_neginf_scalar, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsinf::test_posinf, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsinf::test_posinf_scalar, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsposinf::test_generic, test/torch_np/numpy_tests/lib/test_type_check.py::TestIsneginf::test_generic, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_array, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_complex_bad, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_complex_bad2, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_complex_good, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_do_not_rewrite_previous_keyword, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_float, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_generic, test/torch_np/numpy_tests/lib/test_type_check.py::TestNanToNum::test_integer, test/torch_np/numpy_tests/lib/test_type_check.py::TestRealIfClose::test_basic, test/torch_np/numpy_tests/lib/test_type_check.py::TestArrayConversion::test_asfarray 2025-08-26T21:21:17.7000625Z 2025-08-26T21:21:20.7571226Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:20.7574204Z import pkg_resources 2025-08-26T21:21:20.8816794Z Running test_public_bindings 1/1 ... [2025-08-26 21:21:20.881332] 2025-08-26T21:21:20.8817569Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:20.8820200Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_public_bindings.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:20.881708] 2025-08-26T21:21:21.3127047Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:21.3128801Z import pkg_resources 2025-08-26T21:21:21.4816864Z Running torch_np/numpy_tests/core/test_indexing 1/1 ... [2025-08-26 21:21:21.481297] 2025-08-26T21:21:21.4817828Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:21.4820810Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/core/test_indexing.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:21.481735] 2025-08-26T21:21:25.4525049Z 2025-08-26T21:21:25.4526649Z torch_np/numpy_tests/core/test_indexing 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.core.test_indexing_1.1_1f99ac4a7923632c_.log 2025-08-26T21:21:25.4557553Z Running 67 items in this shard: test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_boolean_assignment_value_mismatch, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_boolean_indexing_list, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_boolean_indexing_onedim, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_boolean_indexing_twodim, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_boolean_shape_mismatch, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_broaderrors_indexing, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_broken_sequence_not_nd_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_ellipsis_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_ellipsis_index_2, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_empty_fancy_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_empty_tuple_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_everything_returns_views, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_index_no_array_to_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_index_no_floats, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_indexing_array_negative_strides, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_indexing_array_weird_strides, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_memory_order, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_none_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_nontuple_ndindex, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_reverse_strides_and_subspace_bufferinit, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_reversed_strides_result_allocation, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_same_kind_index_casting, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_scalar_array_bool, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_single_bool_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_single_int_index, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_slicing_no_floats, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_small_regressions, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index2_num_32_original_ndim_1, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index2_num_32_original_ndim_32, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index2_num_40_original_ndim_1, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index2_num_40_original_ndim_32, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_False_num_32_original_ndim_1, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_False_num_32_original_ndim_32, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_False_num_40_original_ndim_1, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_False_num_40_original_ndim_32, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_True_num_32_original_ndim_1, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_True_num_32_original_ndim_32, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_True_num_40_original_ndim_1, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_advanced_indices_index_True_num_40_original_ndim_32, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_too_many_fancy_indices_special_case, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_trivial_fancy_not_possible, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_trivial_fancy_out_of_bounds, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_tuple_subclass, test/torch_np/numpy_tests/core/test_indexing.py::TestIndexing::test_uncontiguous_subspace_assignment, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_broadcast_error_reports_correct_shape_index0, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_broadcast_error_reports_correct_shape_index1, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_broadcast_error_reports_correct_shape_index2, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_broadcast_subspace, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_index_is_larger, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_prepend_not_one, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_prepending_ones, test/torch_np/numpy_tests/core/test_indexing.py::TestBroadcastedAssignments::test_simple_broadcasting_errors, test/torch_np/numpy_tests/core/test_indexing.py::TestFancyIndexingCast::test_boolean_index_cast_assign, test/torch_np/numpy_tests/core/test_indexing.py::TestMultiIndexingAutomated::test_1d, test/torch_np/numpy_tests/core/test_indexing.py::TestMultiIndexingAutomated::test_boolean, test/torch_np/numpy_tests/core/test_indexing.py::TestMultiIndexingAutomated::test_multidim, test/torch_np/numpy_tests/core/test_indexing.py::TestFloatNonIntegerArgument::test_non_integer_argument_errors, test/torch_np/numpy_tests/core/test_indexing.py::TestFloatNonIntegerArgument::test_non_integer_sequence_multiplication, test/torch_np/numpy_tests/core/test_indexing.py::TestFloatNonIntegerArgument::test_reduce_axis_float_index, test/torch_np/numpy_tests/core/test_indexing.py::TestFloatNonIntegerArgument::test_valid_indexing, test/torch_np/numpy_tests/core/test_indexing.py::TestFloatNonIntegerArgument::test_valid_slicing, test/torch_np/numpy_tests/core/test_indexing.py::TestBooleanIndexing::test_bool_as_int_argument_errors, test/torch_np/numpy_tests/core/test_indexing.py::TestBooleanIndexing::test_boolean_indexing_fast_path, test/torch_np/numpy_tests/core/test_indexing.py::TestBooleanIndexing::test_boolean_indexing_weirdness, test/torch_np/numpy_tests/core/test_indexing.py::TestArrayToIndexDeprecation::test_array_to_index_error, test/torch_np/numpy_tests/core/test_indexing.py::TestNonIntegerArrayLike::test_basic, test/torch_np/numpy_tests/core/test_indexing.py::TestMultipleEllipsisError::test_basic 2025-08-26T21:21:25.4587407Z 2025-08-26T21:21:28.7270655Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:28.7273942Z import pkg_resources 2025-08-26T21:21:28.8531411Z Running test_maskedtensor 1/1 ... [2025-08-26 21:21:28.852762] 2025-08-26T21:21:28.8531899Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:28.8533919Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_maskedtensor.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:28.853163] 2025-08-26T21:21:32.2635775Z 2025-08-26T21:21:32.2636768Z test_public_bindings 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_public_bindings_1.1_95a7d9e31b06768c_.log 2025-08-26T21:21:32.2639406Z Running 4 items in this shard: test/test_public_bindings.py::TestPublicBindings::test_correct_module_names, test/test_public_bindings.py::TestPublicBindings::test_modules_can_be_imported, test/test_public_bindings.py::TestPublicBindings::test_no_new_bindings, test/test_public_bindings.py::TestPublicBindings::test_no_new_reexport_callables 2025-08-26T21:21:32.2640945Z 2025-08-26T21:21:35.5057317Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:35.5060332Z import pkg_resources 2025-08-26T21:21:35.6309262Z Running torch_np/numpy_tests/lib/test_histograms 1/1 ... [2025-08-26 21:21:35.630536] 2025-08-26T21:21:35.6310320Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:35.6313572Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'torch_np/numpy_tests/lib/test_histograms.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:35.630933] 2025-08-26T21:21:39.7010412Z 2025-08-26T21:21:39.7012264Z torch_np/numpy_tests/lib/test_histograms 1/1 was successful, full logs can be found in artifacts with path test/test-reports/torch_np.numpy_tests.lib.test_histograms_1.1_18ff18e198fdc2df_.log 2025-08-26T21:21:39.7063869Z Running 60 items in this shard: test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_arr_weights_mismatch, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_big_arrays, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_bin_array_dims, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_bin_edge_cases, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_bool_conversion, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_density, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_empty, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_error_binnum_type, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_exotic_weights, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_f32_rounding, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_finite_range, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_histogram_bin_edges, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_invalid_range, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_last_bin_inclusive_range, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_no_side_effects, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_object_array_of_0d, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_one_bin, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_outliers, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_precision, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_signed_overflow_bounds, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_signed_overflow_bounds_2, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_simple, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_some_nan_values, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_type, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_unsigned_monotonicity_check, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogram::test_weights, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_empty, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_incorrect_methods, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_limited_variance, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_novariance, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_outlier, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_scott_vs_stone, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_signed_integer_data_bins_auto, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_signed_integer_data_bins_doane, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_signed_integer_data_bins_fd, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_signed_integer_data_bins_rice, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_signed_integer_data_bins_scott, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_signed_integer_data_bins_stone, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_signed_integer_data_bins_sturges, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_simple, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_simple_range, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_simple_weighted, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramOptimBinNums::test_small, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_bins_array, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_bins_error_2, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_bins_errors, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_density_non_uniform_1d, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_density_non_uniform_2d, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_edge_dtype, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_empty, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_equal_edges, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_finite_range, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_identical_samples, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_inf_edges, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_large_integers, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_rightmost_binedge, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_shape_3d, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_shape_4d, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_simple, test/torch_np/numpy_tests/lib/test_histograms.py::TestHistogramdd::test_weights 2025-08-26T21:21:39.7113664Z 2025-08-26T21:21:43.0943127Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:43.0946468Z import pkg_resources 2025-08-26T21:21:43.2163724Z Running lazy/test_ts_opinfo 1/1 ... [2025-08-26 21:21:43.216023] 2025-08-26T21:21:43.2164581Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:43.2166805Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'lazy/test_ts_opinfo.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:43.216354] 2025-08-26T21:21:47.4473844Z 2025-08-26T21:21:47.4474718Z test_maskedtensor 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_maskedtensor_1.1_d4b02d0f7da572a5_.log 2025-08-26T21:21:47.4813444Z Running 955 items in this shard: test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn0, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn1, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn10, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn11, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn12, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn13, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn14, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn15, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn16, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn17, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn18, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn19, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn2, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn20, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn21, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn22, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn23, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn24, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn25, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn26, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn27, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn28, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn29, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn3, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn30, test/test_maskedtensor.py::TestUnary::test_inplace_unary_fn31, 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test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rad2deg_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_reciprocal_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_0_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_3_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_3_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_3_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_3_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_3_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_3_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_neg_3_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_neg_3_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_neg_3_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_neg_3_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_neg_3_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_decimals_neg_3_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_round_layout0_cpu_float32, 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test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rsqrt_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rsqrt_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rsqrt_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rsqrt_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_rsqrt_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sgn_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sigmoid_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sign_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_signbit_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sin_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinc_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sinh_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_sqrt_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_square_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tan_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_tanh_layout2_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout0_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout0_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout0_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout1_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout1_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout1_cpu_float64, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout2_cpu_float16, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout2_cpu_float32, test/test_maskedtensor.py::TestOperatorsCPU::test_unary_core_trunc_layout2_cpu_float64, test/test_maskedtensor.py::TestBasicsCPU::test_add_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_contiguous_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_diff_dim_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_diff_layouts_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_diff_sizes_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_grad_warning_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_invalid_sparse_coo_values_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_invalid_sparse_csr_values_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_invalid_sparse_layout_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_invalid_tensor_inputs_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_nn_unfold_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_softmax_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_stack_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_to_dense_and_sparse_coo_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_to_dense_and_sparse_csr_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_to_dense_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_to_device_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_to_dtype_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_to_sparse_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_unfold_cpu, test/test_maskedtensor.py::TestBasicsCPU::test_where_cpu 2025-08-26T21:21:47.5143319Z 2025-08-26T21:21:50.5719024Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:21:50.5722400Z import pkg_resources 2025-08-26T21:21:50.6946395Z Running test_schema_check 1/1 ... [2025-08-26 21:21:50.694261] 2025-08-26T21:21:50.6947144Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:21:50.6949709Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_schema_check.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:21:50.694634] 2025-08-26T21:21:59.3784660Z 2025-08-26T21:21:59.3785885Z test_ops 6/7 was successful, full logs can be found in artifacts with path test/test-reports/test_ops_6.7_365cd59757635eff_.log 2025-08-26T21:21:59.7423687Z Running 4929 items in this shard: test/test_ops.py::TestCommonCPU::test_compare_cpu_T_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___getitem___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu___rpow___cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_bfloat16_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_bool_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_byte_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_cfloat_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs__conversions_half_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_as_strided_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_atleast_3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_column_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_dot_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_flip_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_fmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_index_fill_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_log_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_stack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_true_divide_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_var_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu__refs_view_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_arange_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_baddbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_cholesky_inverse_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_corrcoef_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_diagonal_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_dsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_empty_permuted_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_gather_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_hstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_index_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_int_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_cholesky_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lstsq_grad_oriented_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_lu_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linalg_svdvals_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_linspace_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_logaddexp2_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_lu_unpack_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_masked_log_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_masked_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nanmedian_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nanquantile_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_narrow_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_alpha_dropout_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_grid_sample_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_hardswish_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_area_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_norm_inf_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_pca_lowrank_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_renorm_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_resize__cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_scalar_tensor_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_short_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_split_with_sizes_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_to_sparse_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_view_as_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_compare_cpu_view_as_cpu_float32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_alias_copy_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_as_strided_copy_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_as_strided_partial_views_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_atleast_1d_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_atleast_2d_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_chalf_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_diagonal_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_flatten_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_index_fill_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_linalg_diagonal_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_ravel_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_unflatten_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_unfold_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_unsqueeze_copy_cpu_complex32, test/test_ops.py::TestCommonCPU::test_complex_half_reference_testing_where_cpu_complex32, test/test_ops.py::TestCommonCPU::test_dtypes___radd___cpu, test/test_ops.py::TestCommonCPU::test_dtypes___rand___cpu, test/test_ops.py::TestCommonCPU::test_dtypes___rdiv___cpu, test/test_ops.py::TestCommonCPU::test_dtypes___rmul___cpu, test/test_ops.py::TestCommonCPU::test_dtypes___rsub___cpu, test/test_ops.py::TestCommonCPU::test_dtypes__chunk_cat_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__native_batch_norm_legit_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_T_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs__conversions_bfloat16_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs__conversions_bool_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs__conversions_char_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs__conversions_float_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs__conversions_short_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_addcdiv_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_addcmul_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_any_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_broadcast_to_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_cauchy_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_chunk_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_copysign_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_cumprod_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_diag_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_equal_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_expand_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_fft_hfftn_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_fft_ihfft2_cpu, 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test/test_ops.py::TestCommonCPU::test_dtypes__refs_ne_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_nextafter_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_nn_functional_pixel_shuffle_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_nn_functional_pixel_unshuffle_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_nn_functional_relu6_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_nn_functional_softmin_with_dtype_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_pow_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_rot90_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_sinc_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_special_multigammaln_mvlgamma_p_3_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_stack_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_sub_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_tanh_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_transpose_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_tril_indices_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_unbind_cpu, test/test_ops.py::TestCommonCPU::test_dtypes__refs_zeros_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_addbmm_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_addcdiv_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_as_strided_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_atleast_3d_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_bfloat16_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_bitwise_left_shift_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_bucketize_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_cauchy_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_cdouble_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_chalf_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_char_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_cholesky_solve_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_complex_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_contiguous_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_corrcoef_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_div_floor_rounding_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_div_trunc_rounding_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_einsum_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_empty_permuted_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_empty_strided_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_expand_copy_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_fft_ihfft2_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_fft_irfft_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_fill_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_float_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_float_power_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_fmod_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_frac_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_ge_cpu, 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test/test_ops.py::TestCommonCPU::test_dtypes_linalg_lstsq_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_linalg_lu_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_linalg_lu_factor_ex_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_linalg_matrix_norm_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_linalg_matrix_power_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_linalg_svdvals_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_logical_not_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_lt_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_masked_argmax_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_masked_argmin_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_masked_cumprod_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_masked_fill_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_masked_median_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_masked_scatter_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_masked_softmin_cpu, 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test/test_ops.py::TestCommonCPU::test_dtypes_round_decimals_neg_3_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_rsub_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_scatter_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_sign_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_signal_windows_cosine_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_sinc_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_sort_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_special_log_ndtr_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_split_list_args_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_squeeze_multiple_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_std_mean_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_sum_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_torch_ops_aten__safe_softmax_default_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_unfold_copy_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_unsqueeze_copy_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_vstack_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_xlogy_cpu, test/test_ops.py::TestCommonCPU::test_dtypes_zero__cpu, test/test_ops.py::TestCommonCPU::test_errors_copysign_cpu, test/test_ops.py::TestCommonCPU::test_errors_cov_cpu, test/test_ops.py::TestCommonCPU::test_errors_div_trunc_rounding_cpu, test/test_ops.py::TestCommonCPU::test_errors_fft_hfft_cpu, test/test_ops.py::TestCommonCPU::test_errors_fft_ihfft_cpu, test/test_ops.py::TestCommonCPU::test_errors_fft_rfft_cpu, test/test_ops.py::TestCommonCPU::test_errors_fft_rfftn_cpu, test/test_ops.py::TestCommonCPU::test_errors_fliplr_cpu, test/test_ops.py::TestCommonCPU::test_errors_geometric_cpu, test/test_ops.py::TestCommonCPU::test_errors_heaviside_cpu, test/test_ops.py::TestCommonCPU::test_errors_hsplit_cpu, test/test_ops.py::TestCommonCPU::test_errors_index_add_cpu, test/test_ops.py::TestCommonCPU::test_errors_item_cpu, test/test_ops.py::TestCommonCPU::test_errors_jiterator_binary_cpu, test/test_ops.py::TestCommonCPU::test_errors_le_cpu, test/test_ops.py::TestCommonCPU::test_errors_linalg_lstsq_cpu, test/test_ops.py::TestCommonCPU::test_errors_masked_fill_cpu, test/test_ops.py::TestCommonCPU::test_errors_movedim_cpu, test/test_ops.py::TestCommonCPU::test_errors_mul_cpu, test/test_ops.py::TestCommonCPU::test_errors_narrow_cpu, test/test_ops.py::TestCommonCPU::test_errors_native_layer_norm_cpu, test/test_ops.py::TestCommonCPU::test_errors_nn_functional_adaptive_max_pool2d_cpu, test/test_ops.py::TestCommonCPU::test_errors_nn_functional_adaptive_max_pool3d_cpu, test/test_ops.py::TestCommonCPU::test_errors_nn_functional_avg_pool2d_cpu, test/test_ops.py::TestCommonCPU::test_errors_nn_functional_hinge_embedding_loss_cpu, test/test_ops.py::TestCommonCPU::test_errors_ormqr_cpu, test/test_ops.py::TestCommonCPU::test_errors_signal_windows_general_cosine_cpu, test/test_ops.py::TestCommonCPU::test_errors_signal_windows_hann_cpu, test/test_ops.py::TestCommonCPU::test_errors_sparse_randn_like_layout1_cpu, test/test_ops.py::TestCommonCPU::test_errors_sparse_sum_layout2_cpu, test/test_ops.py::TestCommonCPU::test_errors_special_chebyshev_polynomial_v_cpu, test/test_ops.py::TestCommonCPU::test_errors_special_legendre_polynomial_p_cpu, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_addmm_decomposed_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_alias_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_asinh_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_cholesky_solve_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_dstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_eq_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_erfinv_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_exp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_float_power_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_full_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_heaviside_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_hypot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_ldexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_cond_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_lstsq_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_solve_ex_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_linalg_vecdot_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logspace_tensor_overload_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_logsumexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_lu_unpack_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_min_binary_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_minimum_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_normal_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polar_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_rsqrt_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sigmoid_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_slice_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_bessel_j0_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_special_shifted_chebyshev_polynomial_w_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_squeeze_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_sub_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_take_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_tan_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_triu_cpu_float32, test/test_ops.py::TestCommonCPU::test_meta_consistency_out_dtype_mismatch_var_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices___rmul___cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_abs_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_acos_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_addr_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_all_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmax_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_argmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_argsort_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_atleast_3d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_baddbmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_and_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bitwise_right_shift_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_block_diag_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_bucketize_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cauchy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cfloat_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_chalf_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_clamp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_combinations_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_cross_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_deg2rad_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagflat_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diagonal_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_diff_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_empty_permuted_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_fftshift_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_hfftn_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_fft_ihfftn_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fill_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmin_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_fmod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ge_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ge_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_gt_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_hash_tensor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_histogramdd_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_hsplit_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_hsplit_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_hstack_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_inner_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_2inputs_2outputs_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_jiterator_2inputs_2outputs_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cond_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_cross_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_lu_factor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_linalg_svd_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_log10_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_lt_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_mH_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_cumprod_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_logaddexp_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_masked_var_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nanmedian_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nansum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_native_batch_norm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_ne_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_conv1d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_cross_entropy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_elu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_glu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_hardtanh_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_bilinear_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool2d_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_max_pool3d_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_circular_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pdist_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pixel_shuffle_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_pixel_shuffle_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_relu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_rrelu_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_softmin_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_tanhshrink_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_triplet_margin_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_nonzero_static_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_normal_in_place_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_copy_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_permute_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_polar_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_pow_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_remainder_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_reshape_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_resize_as__cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_resolve_conj_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_resolve_neg_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rot90_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_rsub_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scalar_tensor_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_prod_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_scatter_reduce_sum_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_select_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_select_scatter_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_short_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_softmax_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_bessel_j1_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_chebyshev_polynomial_v_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_i1e_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_laguerre_polynomial_l_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_k0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_polygamma_special_polygamma_n_0_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_scaled_modified_bessel_k0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_shifted_chebyshev_polynomial_w_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_spherical_bessel_j0_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_xlog1py_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_special_zeta_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_split_with_sizes_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_square_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_stack_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_sum_to_size_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_t_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_topk_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_torch_ops_aten__safe_softmax_default_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_trapz_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_tril_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_unbind_copy_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unflatten_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_unique_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_unsafe_chunk_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_unsafe_split_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_unsafe_split_cpu_int64, test/test_ops.py::TestCommonCPU::test_multiple_devices_var_mean_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_var_unbiased_cpu_float32, test/test_ops.py::TestCommonCPU::test_multiple_devices_view_as_complex_cpu_float32, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_bitwise_xor_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_broadcast_tensors_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_byte_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_cfloat_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_cummax_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_double_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_dstack_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_empty_like_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_eq_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_erfc_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_expand_copy_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_eye_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_ifft2_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_ifftn_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_irfft2_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fft_irfft_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_fill_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_flip_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_heaviside_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_index_add_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_isfinite_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_isnan_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_ldexp_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_le_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_masked_prod_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_max_binary_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_maximum_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_min_reduction_no_dim_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_new_zeros_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_scalar_tensor_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_scatter_add_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_scatter_reduce_prod_cpu_bool, test/test_ops.py::TestCommonCPU::test_non_standard_bool_values_scatter_reduce_sum_cpu_bool, 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test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_scatter_reduce_amax_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_signal_windows_exponential_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_signal_windows_hamming_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_signbit_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_sin_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_softmax_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_chebyshev_polynomial_u_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_laguerre_polynomial_l_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_log_ndtr_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_special_modified_bessel_k1_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_split_with_sizes_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_squeeze_copy_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_squeeze_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_stft_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_tanh_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_tensordot_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_tile_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_topk_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_transpose_copy_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_tril_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_var_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_view_copy_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_vsplit_cpu_float32, test/test_ops.py::TestCompositeComplianceCPU::test_view_replay_zeros_cpu_float32, test/test_ops.py::TestMathBitsCPU::test_conj_view_T_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_T_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs__conversions_float_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_add_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_addcmul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_all_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_column_stack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_cumprod_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_dstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_equal_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_fft_ifftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_hstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_index_add_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_isclose_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_linalg_matrix_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_linalg_norm_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_channel_shuffle_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_l1_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_nn_functional_triplet_margin_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_positive_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_reshape_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_to_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view__refs_var_mean_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_abs_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_as_strided_scatter_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_atanh_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_bool_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_combinations_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_contiguous_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_diff_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_dist_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_ifftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_fft_irfftn_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_flip_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_hsplit_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_hstack_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_index_add_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_isnan_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_istft_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_jiterator_4inputs_with_extra_args_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_kron_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_cond_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_lu_solve_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_linalg_pinv_singular_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logcumsumexp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logical_and_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_logspace_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_std_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_masked_sum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_matmul_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_matrix_exp_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_meshgrid_list_of_tensors_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_new_zeros_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_feature_alpha_dropout_without_train_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_linear_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_triplet_margin_with_distance_loss_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_nn_functional_unfold_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_norm_nuc_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_normal_in_place_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_ones_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_pow_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_randn_like_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_repeat_interleave_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_resize__cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_roll_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_rsub_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_short_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_slice_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_squeeze_multiple_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sum_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_sum_to_size_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_tile_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unflatten_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_unsqueeze_copy_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_view_as_real_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_view_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_conj_view_zeros_cpu_complex64, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_T_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs__conversions_short_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_addcdiv_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_addr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_as_strided_scatter_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_dot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_dstack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_exp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expand_as_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_expand_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_hfft2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_hfft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_fft_hfftn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_flatten_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_flip_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_isclose_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log10_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_log_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_masked_fill_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_meshgrid_variadic_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_new_full_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_permute_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_ravel_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_renorm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sgn_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_sum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_tensor_split_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_transpose_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_unbind_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_vdot_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_view_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_vsplit_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_where_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__refs_zeros_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view__unsafe_masked_index_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_abs_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_all_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_angle_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_any_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_baddbmm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_broadcast_tensors_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cfloat_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_char_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_combinations_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_count_nonzero_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_cov_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_diag_embed_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_einsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_empty_strided_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_exp2_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_fft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_fftshift_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_ifft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fft_irfft_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_flatten_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_flip_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_fliplr_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_float_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_index_select_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_isnan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_isreal_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_jiterator_unary_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cholesky_ex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_cond_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_ldl_factor_ex_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_ldl_solve_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_linalg_matrix_rank_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_and_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_logical_xor_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_lu_unpack_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_masked_cumsum_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_matrix_exp_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_new_zeros_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_norm_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_norm_inf_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_permute_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_reshape_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_rsqrt_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_scatter_add_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_short_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sigmoid_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_softmax_with_dtype_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_split_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_squeeze_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_sub_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_take_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_tan_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_true_divide_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_var_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_var_unbiased_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_conj_view_view_copy_cpu_complex128, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_cdouble_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_complex_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_half_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs__conversions_int_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_add_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_addcdiv_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_addcmul_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_allclose_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_amax_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_cauchy_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ceil_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_clamp_min_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_div_floor_rounding_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_dsplit_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_erf_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_exponential_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_fft2_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_fftshift_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_hfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fft_rfft_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_fill_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_floor_divide_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_heaviside_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_igamma_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_igammac_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_linspace_tensor_overload_cpu_float64, 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test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_permute_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_ravel_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_remainder_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_renorm_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_roll_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_rsub_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sinc_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_softmax_with_dtype_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_bessel_j0_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_i1_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_special_xlog1py_cpu_float64, test/test_ops.py::TestMathBitsCPU::test_neg_view__refs_sum_to_size_cpu_float64, 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test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_square_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_tril_indices_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_triu_indices_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_view_as_complex_cpu, test/test_ops.py::TestRefsOpsInfoCPU::test_refs_are_in_python_ref_db_op__refs_where_cpu, test/test_ops.py::TestFakeTensorCPU::test_fake___rmatmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake___rmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake__segment_reduce_lengths_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake__unsafe_masked_index_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_addmv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_allclose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_argmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_atleast_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_atleast_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_H_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_T_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast___rmod___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__chunk_cat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast__unsafe_masked_index_put_accumulate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_abs_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atanh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atleast_1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_atleast_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_bincount_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_broadcast_to_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cartesian_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_clamp_min_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_clone_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_count_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_cummin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_digamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_div_trunc_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_dsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_dstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_expand_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_exponential_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_fftshift_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_hfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fft_ihfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_float_power_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_fmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_grid_sampler_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_gt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_igammac_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_index_reduce_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isclose_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isfinite_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_isreal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_item_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_jiterator_binary_return_by_ref_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_cond_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_eigh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_householder_product_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_ldl_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_matrix_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_pinv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_linalg_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log1p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_log_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logcumsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_long_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_amin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_masked_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_narrow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_native_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_new_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_constant_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_nonzero_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_normal_number_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_rsqrt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_scalar_tensor_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sgn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_gaussian_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_hann_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_signal_windows_nuttall_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_slice_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_bessel_y0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_hermite_polynomial_h_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_legendre_polynomial_p_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_modified_bessel_i0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_special_scaled_modified_bessel_k1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_tile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_torch_ops_aten__safe_softmax_default_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unfold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_autocast_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_bitwise_or_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_fake_cfloat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_alias_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_atleast_1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_bernoulli_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_bfloat16_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cdist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cdouble_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cholesky_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_clamp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_contiguous_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_diagonal_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_expand_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_irfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_rfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_fft_rfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_frexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_eigvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_inv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_multi_dot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_linalg_vander_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_log_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_lu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_masked_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_max_pool2d_with_indices_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_min_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_msort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_adaptive_max_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_batch_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_conv_transpose1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_max_unpool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_nll_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_norm_nuc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_polygamma_polygamma_n_4_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_scatter_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_std_mean_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_tensor_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unbind_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unflatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_unsqueeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_view_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_vstack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_amp_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp___rmatmul___cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp__unsafe_masked_index_put_accumulate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_acos_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_addcdiv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_complex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_conj_physical_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_diagonal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_dsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_einsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_fft_ihfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_flatten_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_grid_sampler_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_fill_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_index_reduce_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_kron_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lerp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lgamma_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_inv_ex_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_linalg_svdvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logaddexp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_logaddexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_masked_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_max_reduction_no_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_maximum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_meshgrid_list_of_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nan_to_num_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_binary_cross_entropy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_cosine_embedding_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_fractional_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_gelu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_huber_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_instance_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_margin_ranking_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_max_unpool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_replicate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_pixel_unshuffle_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_soft_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_softshrink_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_threshold_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_pca_lowrank_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_prod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_quantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_reciprocal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_repeat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_resolve_conj_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_resolve_neg_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_select_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_softmax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_softmax_with_dtype_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_square_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_sum_to_size_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_svd_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_true_divide_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_trunc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsafe_split_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_unsqueeze_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_var_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_crossref_backward_no_amp_vsplit_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_cumprod_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diagflat_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_diagonal_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_div_floor_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_expand_as_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_fft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_hfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_hfftn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_ifft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_irfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_fft_rfft2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_gather_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_histc_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_index_reduce_mean_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_isin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_jiterator_binary_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_jiterator_binary_return_by_ref_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_kron_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_kthvalue_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_cross_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_det_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_eigvals_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_lstsq_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_solve_triangular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_vander_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_linalg_vecdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_log_normal_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logaddexp2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_logical_and_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mH_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_logsumexp_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_masked_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_max_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_meshgrid_variadic_tensors_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_mul_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nansum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_narrow_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_native_dropout_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_new_empty_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_new_ones_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_avg_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_adaptive_max_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_conv3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_dropout3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_feature_alpha_dropout_with_train_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_fractional_max_pool3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_interpolate_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_logsigmoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_mse_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_multilabel_margin_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pad_reflect_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_pairwise_distance_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_nn_functional_upsample_nearest_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_ormqr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_outer_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_polygamma_polygamma_n_3_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_remainder_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_round_decimals_0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_rsub_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sgn_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_bartlett_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_cosine_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_general_hamming_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_signal_windows_hann_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_log_ndtr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_modified_bessel_k0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_special_ndtri_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_sum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_t_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_take_along_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_trapezoid_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_triangular_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unbind_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_unique_consecutive_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_var_unbiased_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_fake_view_as_real_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_fake_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rand___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops___rxor___cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__softmax_backward_data_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops__unsafe_masked_index_put_accumulate_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_acosh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_addmv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_as_strided_scatter_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atleast_1d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_atleast_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bool_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_bucketize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_cholesky_solve_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_clamp_max_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_contiguous_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_corrcoef_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_dist_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_div_floor_rounding_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_einsum_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_expand_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_fft_ihfft_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_gradient_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_grid_sampler_2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_grid_sampler_3d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_add_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_put_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_index_reduce_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isnan_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_isposinf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_istft_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_jiterator_binary_return_by_ref_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_linalg_pinv_singular_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_logdet_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lt_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_lu_unpack_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mT_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_amax_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_masked_select_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_min_reduction_with_dim_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_mv_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nan_to_num_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nanquantile_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_native_dropout_backward_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_native_layer_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_avg_pool2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_conv_transpose2d_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_cosine_similarity_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_dropout_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_linear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_normalize_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_pad_replicate_negative_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_relu6_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_rms_norm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_softmin_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_nn_functional_upsample_bilinear_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_norm_inf_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_normal_in_place_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_polygamma_polygamma_n_2_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_qr_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_rand_like_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_roll_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_rot90_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sinh_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sort_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_sparse_sampled_addmm_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_bessel_j1_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_special_bessel_y0_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_squeeze_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_take_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_to_sparse_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_tril_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_triu_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unbind_copy_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unique_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_unsafe_chunk_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_vdot_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_view_as_real_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_pointwise_ops_zero__cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_arange_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_linspace_tensor_overload_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_logspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_complex64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_float32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout__refs_zeros_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_arange_cpu_float64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_int32, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_full_cpu_int8, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_float16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_logspace_tensor_overload_cpu_int64, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_ones_cpu_int16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_bfloat16, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_complex128, test/test_ops.py::TestFakeTensorCPU::test_strided_layout_zeros_cpu_float64, test/test_ops.py::TestTagsCPU::test_tags___rmatmul___cpu_float32, test/test_ops.py::TestTagsCPU::test_tags___rxor___cpu_int64, test/test_ops.py::TestTagsCPU::test_tags__refs__conversions_float_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_add_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_addcmul_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_addr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_atleast_2d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_block_diag_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_constant_pad_nd_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_contiguous_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_copysign_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_digamma_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_empty_strided_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_eq_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_equal_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_hfftn_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_ifft2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_ifft_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_fft_ihfft2_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_flatten_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_frac_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_geometric_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_index_add_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_index_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_isnan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_lgamma_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_linalg_cross_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_linalg_vecdot_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_linspace_tensor_overload_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logical_or_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_logical_xor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_lt_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_movedim_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nan_to_num_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_narrow_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_new_zeros_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_elu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_glu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_group_norm_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_leaky_relu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_smooth_l1_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_nn_functional_softmax_with_dtype_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_rad2deg_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_real_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_true_divide_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_unbind_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_view_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__refs_where_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags__unsafe_masked_index_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_addmv_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_aminmax_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_any_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_argmin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_as_strided_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_atan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_bitwise_and_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_broadcast_to_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_cdouble_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_chunk_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_combinations_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_constant_pad_nd_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_cov_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_cumulative_trapezoid_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_diff_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_div_no_rounding_mode_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_double_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_dstack_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_empty_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_erf_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_exp_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_fftshift_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fft_rfft_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_flatten_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_flip_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_fliplr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_full_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_gcd_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_grid_sampler_2d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_grid_sampler_3d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_hash_tensor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_index_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_index_fill_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_index_reduce_amax_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_int_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_isclose_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_isnan_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_item_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_jiterator_binary_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_jiterator_unary_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_det_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_ldl_factor_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_ldl_factor_ex_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_matrix_rank_hermitian_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_norm_subgradients_at_zero_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_linalg_qr_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_logdet_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_logit_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_lu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_mH_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_masked_fill_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_masked_logaddexp_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_masked_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_mode_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_msort_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_mul_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_mvlgamma_mvlgamma_p_5_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nan_to_num_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nansum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_ne_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_neg_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_adaptive_avg_pool1d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_avg_pool1d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_avg_pool3d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_binary_cross_entropy_with_logits_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_dropout2d_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_gaussian_nll_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_hardshrink_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_interpolate_linear_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_interpolate_trilinear_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_kl_div_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_one_hot_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_prelu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_relu6_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_silu_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_threshold_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nn_functional_triplet_margin_with_distance_loss_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nonzero_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_nonzero_static_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_permute_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_permute_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_polygamma_polygamma_n_0_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_pow_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_roll_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_scatter_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_scatter_reduce_sum_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_short_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sign_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sin_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_sinc_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_chebyshev_polynomial_t_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_special_hermite_polynomial_he_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_split_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_split_with_sizes_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_square_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_squeeze_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tanh_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_transpose_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_trapezoid_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_triangular_solve_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_tril_indices_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_triu_indices_cpu_int64, test/test_ops.py::TestTagsCPU::test_tags_unfold_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unsqueeze_copy_cpu_float32, test/test_ops.py::TestTagsCPU::test_tags_unsqueeze_cpu_float32 2025-08-26T21:22:00.1069869Z 2025-08-26T21:22:02.7374628Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:22:02.7376240Z import pkg_resources 2025-08-26T21:22:02.8674045Z Running optim/test_optim 1/1 ... [2025-08-26 21:22:02.867071] 2025-08-26T21:22:02.8674492Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:22:02.8677333Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'optim/test_optim.py', '-m', 'not serial', '--shard-id=1', '--num-shards=1', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:22:02.867470] 2025-08-26T21:22:03.5575168Z 2025-08-26T21:22:03.5576054Z lazy/test_ts_opinfo 1/1 was successful, full logs can be found in artifacts with path test/test-reports/lazy.test_ts_opinfo_1.1_f2af7eac75be4b29_.log 2025-08-26T21:22:03.5694886Z Running 292 items in this shard: test/lazy/test_ts_opinfo.py::TestLazyTensor::testConvolutionBackward, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_tensor_ctr, test/lazy/test_ts_opinfo.py::TestLazyTensor::test_view_mark_step_preserved, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_block_diag_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diag_embed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_logsumexp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_min_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_narrow_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_new_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_norm_nuc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_block_diag_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diag_embed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_logsumexp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_min_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_narrow_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_new_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_norm_nuc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_correctness_with_reusing_ir_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy__softmax_backward_data_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_abs_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addcdiv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addcmul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_addmm_decomposed_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_alias_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_arange_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_as_strided_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_as_strided_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_baddbmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_bernoulli_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_bmm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_clamp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_clamp_min_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_constant_pad_nd_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cos_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_cumsum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_diagonal_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_diagonal_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_floor_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_no_rounding_mode_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_div_trunc_rounding_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_empty_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_empty_strided_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_eq_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_exp_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_expand_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_flip_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_floor_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_frac_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_gather_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_ge_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_grid_sampler_2d_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_gt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_le_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_log2_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_log_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_lt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_masked_fill_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_pool2d_with_indices_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_max_reduction_with_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_maximum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mean_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_min_binary_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_min_reduction_no_dim_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_minimum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mul_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_mv_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_batch_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_dropout_backward_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_native_layer_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_ne_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_neg_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_fro_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_norm_inf_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_permute_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_pow_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_reciprocal_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_remainder_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_repeat_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_rsqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_scatter_add_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_select_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sgn_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sigmoid_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_slice_scatter_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sort_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sqrt_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_squeeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_stack_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_std_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_std_unbiased_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sub_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_sum_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_t_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_tanh_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_topk_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_trace_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_transpose_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_tril_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_triu_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_trunc_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_unfold_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_uniform_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_unsqueeze_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyOpInfoCPU::test_dispatched_to_lazy_view_copy_cpu_float32, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_adaptiveavgpool3d_dynamic, test/lazy/test_ts_opinfo.py::TestLazyDynamicOps::test_nonzero_dynamic 2025-08-26T21:22:03.5811723Z 2025-08-26T21:22:06.0508465Z 2025-08-26T21:22:06.0509836Z optim/test_optim 1/1 was successful, full logs can be found in artifacts with path test/test-reports/optim.test_optim_1.1_af609d1d2692adb4_.log 2025-08-26T21:22:06.0510909Z 2025-08-26T21:22:06.7264285Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:22:06.7267255Z import pkg_resources 2025-08-26T21:22:06.8527455Z Running test_quantization 2/4 ... [2025-08-26 21:22:06.852403] 2025-08-26T21:22:06.8528295Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:22:06.8530986Z Executing ['/opt/conda/envs/py_3.13/bin/python', '-bb', 'test_quantization.py', '-m', 'not serial', '--shard-id=2', '--num-shards=4', '-v', '-vv', '-rfEX', '-p', 'no:xdist', '--use-pytest', '-x', '--reruns=2', '--import-slow-tests', '--import-disabled-tests'] ... [2025-08-26 21:22:06.852746] 2025-08-26T21:22:09.2955235Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:22:09.2956865Z import pkg_resources 2025-08-26T21:27:33.5595784Z 2025-08-26T21:27:33.5596691Z test_schema_check 1/1 was successful, full logs can be found in artifacts with path test/test-reports/test_schema_check_1.1_8b45adea89adb761_.log 2025-08-26T21:27:33.8468325Z Running 6027 items in this shard: test/test_schema_check.py::TestSchemaCheck::test_alias_check_fail_custom_ops_output_is_input, test/test_schema_check.py::TestSchemaCheck::test_alias_check_fail_custom_ops_secretly_aliasing, test/test_schema_check.py::TestSchemaCheck::test_alias_check_fail_custom_ops_secretly_mutating, test/test_schema_check.py::TestSchemaCheck::test_alias_check_fail_multiple_operators, test/test_schema_check.py::TestSchemaCheck::test_alias_check_fail_multiple_operators_centered, test/test_schema_check.py::TestSchemaCheck::test_alias_check_fail_outputs_unexpectedly_aliasing, test/test_schema_check.py::TestSchemaCheck::test_alias_check_fail_simple, test/test_schema_check.py::TestSchemaCheck::test_is_alias_of_basic, test/test_schema_check.py::TestSchemaCheck::test_is_alias_of_empty_container, test/test_schema_check.py::TestSchemaCheck::test_mutation_check_fail, test/test_schema_check.py::TestSchemaCheck::test_mutation_check_fail_multiple_operators, test/test_schema_check.py::TestSchemaCheck::test_overlaps_basic, test/test_schema_check.py::TestSchemaCheck::test_overlaps_empty_container, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_empty_list_input, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_aliasing_inputs, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_default_replaced, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_device_input, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_kwarg_tensor, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_list_input, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_mutable_inputs, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_nested_training_op, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_training_op, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_wildcard_after, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_with_multiple_outputs, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_functionality_with_multiple_outputs_aliasing, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_mutated_aliasing_aliasing_inputs, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_mutated_aliasing_aliasing_outputs, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_mutated_aliasing_as_strided, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_mutated_aliasing_multiple_outputs, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_mutated_aliasing_mutation, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_mutated_aliasing_none, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_mutated_aliasing_resize_, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_operator_order, test/test_schema_check.py::TestSchemaCheck::test_schema_check_mode_operator_order_without_grad, test/test_schema_check.py::TestSchemaCheck::test_schema_info_bind_basic, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_complex32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_H_cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_complex32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_T_cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_complex32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___getitem___cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___radd___cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rand___cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rand___cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rand___cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rand___cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rand___cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rand___cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness___rdiv___cpu_int64, 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test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_where_cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_xlogy_cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zero__cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_complex32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_cpu_uint8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_bfloat16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_bool, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_complex128, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_complex32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_complex64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_float16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_float32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_float64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_int16, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_int32, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_int64, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_int8, test/test_schema_check.py::TestSchemaCheckModeOpInfoCPU::test_schema_correctness_zeros_like_cpu_uint8 2025-08-26T21:27:34.1267487Z 2025-08-26T21:27:36.5710697Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:27:36.5712250Z import pkg_resources 2025-08-26T21:29:21.5607780Z 2025-08-26T21:29:21.5608715Z test_quantization 2/4 was successful, full logs can be found in artifacts with path test/test-reports/test_quantization_2.4_b5b3adea56e55a36_.log 2025-08-26T21:29:21.5719052Z Running 313 items in this shard: test/test_quantization.py::TestQuantizedOps::test_advanced_indexing, test/test_quantization.py::TestQuantizedOps::test_avg_pool2d, test/test_quantization.py::TestQuantizedOps::test_avg_pool3d_nhwc, test/test_quantization.py::TestQuantizedOps::test_batch_norm, test/test_quantization.py::TestQuantizedOps::test_cat, test/test_quantization.py::TestQuantizedOps::test_empty_batch, test/test_quantization.py::TestQuantizedOps::test_hardtanh, test/test_quantization.py::TestQuantizedOps::test_interpolate3d, test/test_quantization.py::TestQuantizedOps::test_leaky_relu, test/test_quantization.py::TestQuantizedOps::test_max_pool2d_nhwc, test/test_quantization.py::TestQuantizedOps::test_qadd_relu_cudnn, test/test_quantization.py::TestQuantizedOps::test_qadd_relu_cudnn_nhwc, test/test_quantization.py::TestQuantizedOps::test_qcelu, test/test_quantization.py::TestQuantizedOps::test_qelu, test/test_quantization.py::TestQuantizedOps::test_qgelu, test/test_quantization.py::TestQuantizedOps::test_qmul_broadcast, test/test_quantization.py::TestQuantizedOps::test_qrelu6, test/test_quantization.py::TestQuantizedOps::test_qtanh, test/test_quantization.py::TestQuantizedOps::test_std, test/test_quantization.py::TestQNNPackOps::test_mean, test/test_quantization.py::TestQNNPackOps::test_qnnpack_add, test/test_quantization.py::TestQNNPackOps::test_qnnpack_mul, test/test_quantization.py::TestQNNPackOps::test_qnnpack_relu, test/test_quantization.py::TestQNNPackOps::test_qnnpack_tanh, test/test_quantization.py::TestQuantizedLinear::test_qlinear_add_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_add_pt2e, test/test_quantization.py::TestQuantizedLinear::test_qlinear_add_relu_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_gelu_fp8, test/test_quantization.py::TestQuantizedLinear::test_qlinear_qnnpack_free_memory_and_unpack, test/test_quantization.py::TestQuantizedLinear::test_qlinear_sum_relu_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv1d, test/test_quantization.py::TestQuantizedConv::test_qconv1d_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv1d_relu_cudnn, test/test_quantization.py::TestQuantizedConv::test_qconv1d_unpack, test/test_quantization.py::TestQuantizedConv::test_qconv2d_fp8, test/test_quantization.py::TestQuantizedConv::test_qconv2d_hardtanh_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv2d_relu_pt2e, test/test_quantization.py::TestQuantizedConv::test_qconv3d, test/test_quantization.py::TestQuantizedConv::test_qconv3d_fp8, test/test_quantization.py::TestDynamicQuantizedOps::test_dynamic_convtranspose3d, test/test_quantization.py::TestDynamicQuantizedOps::test_qlinear, test/test_quantization.py::TestDynamicQuantizedOps::test_wrapped_fbgemm_linear_fp16, test/test_quantization.py::TestDynamicQuantizedOps::test_wrapped_fbgemm_pack_gemm_matrix_fp16_pt2_compliant, test/test_quantization.py::TestQuantizedEmbeddingOps::test_embedding_2d_indices, test/test_quantization.py::TestQuantizedEmbeddingOps::test_embedding_bag_2bit, test/test_quantization.py::TestQuantizedEmbeddingOps::test_embedding_bag_byte, test/test_quantization.py::TestQuantizedFunctionalOps::test_conv2d_api, test/test_quantization.py::TestQuantizedFunctionalOps::test_conv3d_api, test/test_quantization.py::TestQuantizedFunctionalOps::test_grid_sample, test/test_quantization.py::TestFakeQuantizeOps::test_backward_per_tensor, test/test_quantization.py::TestFakeQuantizeOps::test_backward_per_tensor_cachemask_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_fixed_qparams_fq_module, test/test_quantization.py::TestFakeQuantizeOps::test_forward_backward_per_tensor_with_amp, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_channel_cachemask_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_forward_per_tensor_cachemask_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_backward_per_channel_cuda, test/test_quantization.py::TestFakeQuantizeOps::test_learnable_forward_per_channel_cpu, test/test_quantization.py::TestFakeQuantizeOps::test_numerical_consistency_per_tensor, test/test_quantization.py::TestFusedObsFakeQuant::test_fused_obs_fake_quant_moving_avg, test/test_quantization.py::TestQuantizedTensor::test_clone, test/test_quantization.py::TestQuantizedTensor::test_cuda_quantization_does_not_pin_memory, test/test_quantization.py::TestQuantizedTensor::test_decomposed_dequantize_per_tensor, test/test_quantization.py::TestQuantizedTensor::test_dequantize_fp16_cpu, test/test_quantization.py::TestQuantizedTensor::test_per_channel_to_device, test/test_quantization.py::TestQuantizedTensor::test_qscheme_pickle, test/test_quantization.py::TestQuantizedTensor::test_qtensor_cpu, test/test_quantization.py::TestQuantizedTensor::test_qtensor_dtypes, test/test_quantization.py::TestQuantizedTensor::test_qtensor_equal, test/test_quantization.py::TestQuantizedTensor::test_qtensor_fill_per_channel_nhwc, test/test_quantization.py::TestQuantizedTensor::test_qtensor_fill_per_tensor_nhwc, test/test_quantization.py::TestQuantizedTensor::test_qtensor_index_put_cuda, test/test_quantization.py::TestQuantizedTensor::test_qtensor_int_repr, test/test_quantization.py::TestQuantizedTensor::test_qtensor_resize, test/test_quantization.py::TestQuantizedTensor::test_qtensor_unsqueeze, test/test_quantization.py::TestQuantizedTensor::test_quantize_per_channel_sub_byte, test/test_quantization.py::TestFakeQuantize::test_fq_module_per_channel, test/test_quantization.py::TestObserver::test_dynamic_quant_observer, test/test_quantization.py::TestObserver::test_histogram_observer_save_load_state_dict, test/test_quantization.py::TestObserver::test_per_tensor_observers, test/test_quantization.py::TestStaticQuantizedModule::test_batch_norm3d, test/test_quantization.py::TestStaticQuantizedModule::test_linear_tanh, test/test_quantization.py::TestStaticQuantizedModule::test_sigmoid, test/test_quantization.py::TestDynamicQuantizedModule::test_dynamic_conv3d, test/test_quantization.py::TestDynamicQuantizedModule::test_dynamic_convtranspose1d, test/test_quantization.py::TestDynamicQuantizedModule::test_linear_api, test/test_quantization.py::TestDynamicQuantizedModule::test_lstm_api, test/test_quantization.py::TestRecordHistogramObserver::test_record_observer, test/test_quantization.py::TestHistogramObserver::test_histogram_observer, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_correct_numel, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_same_inputs, test/test_quantization.py::TestHistogramObserver::test_histogram_observer_single_inputs, test/test_quantization.py::TestFusedObsFakeQuantModule::test_fused_obs_fq_module, test/test_quantization.py::TestBackendConfig::test_backend_config_from_dict, test/test_quantization.py::TestBackendConfig::test_backend_config_set_name, test/test_quantization.py::TestBackendConfig::test_backend_op_config_from_dict, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_root_module, test/test_quantization.py::TestBackendConfig::test_backend_op_config_set_root_node_getter, test/test_quantization.py::TestBackendConfig::test_backend_op_config_to_dict, test/test_quantization.py::TestUtils::test_get_fqn_to_example_inputs_default_kwargs, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_activations_in_non_leaf_module_list, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_dequant_stub, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_manual, test/test_quantization.py::TestQuantizeEagerPTQStatic::test_nested3, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_linear_relu_fusion, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_nested2, test/test_quantization.py::TestQuantizeEagerPTQDynamic::test_quantized_rnn_cell, test/test_quantization.py::TestQuantizeEagerOps::test_conv_transpose_3d, test/test_quantization.py::TestQuantizeEagerOps::test_leaky_relu, test/test_quantization.py::TestQuantizeEagerQAT::test_add_scalar_uses_input_qparams, test/test_quantization.py::TestQuantizeEagerQAT::test_conv_linear, test/test_quantization.py::TestQuantizeEagerQAT::test_dropout, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_leaky_relu, test/test_quantization.py::TestQuantizeEagerQATNumerics::test_relu, test/test_quantization.py::TestFuseEager::test_fusion_convtranspose_bn_eval, test/test_quantization.py::TestFuseEager::test_fusion_linear_bn_eval, test/test_quantization.py::TestModelNumericsEager::test_fake_quant_true_quant_compare, test/test_quantization.py::TestModelNumericsEager::test_weight_only_activation_only_fakequant, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_outputs_conv_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_outputs_functional_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_conv_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_model_stub_submodule_static, test/test_quantization.py::TestNumericSuiteEager::test_compare_weights_linear_dynamic, test/test_quantization.py::TestNumericSuiteEager::test_mobilenet_v2, test/test_quantization.py::TestBiasCorrectionEager::test_linear_chain, test/test_quantization.py::TestFuseFx::test_fuse_convtranspose_bn_eval, test/test_quantization.py::TestFuseFx::test_fusion_pattern_with_multiple_inputs, test/test_quantization.py::TestQuantizeFx::test_attention, test/test_quantization.py::TestQuantizeFx::test_convert_custom_config_set_preserved_attributes, test/test_quantization.py::TestQuantizeFx::test_convtranspose_per_channel_fails_early, test/test_quantization.py::TestQuantizeFx::test_custom_module_class_input_has_multiple_users, test/test_quantization.py::TestQuantizeFx::test_dynamic_linear_input_multiple_use, test/test_quantization.py::TestQuantizeFx::test_get_default_qconfig_valid_backend, test/test_quantization.py::TestQuantizeFx::test_getattr_with_nontensor_result, test/test_quantization.py::TestQuantizeFx::test_linear_leaky_relu_lowering, test/test_quantization.py::TestQuantizeFx::test_lowering_functional_linear_with_kwargs, test/test_quantization.py::TestQuantizeFx::test_not_used, test/test_quantization.py::TestQuantizeFx::test_pattern_match_constant, test/test_quantization.py::TestQuantizeFx::test_permute_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_set_float_to_observed_mapping, test/test_quantization.py::TestQuantizeFx::test_prepare_custom_config_to_dict, test/test_quantization.py::TestQuantizeFx::test_prepare_mode, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_list_args, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_split_list_args, test/test_quantization.py::TestQuantizeFx::test_propagate_dtypes_for_known_nodes_split_tuple_args, test/test_quantization.py::TestQuantizeFx::test_qconfig_function, test/test_quantization.py::TestQuantizeFx::test_qconfig_module_name_object_type_order, test/test_quantization.py::TestQuantizeFx::test_qnnpack_backend_config, test/test_quantization.py::TestQuantizeFx::test_qparams_buffers, test/test_quantization.py::TestQuantizeFx::test_ref_linear_module, test/test_quantization.py::TestQuantizeFx::test_save_observer_state_dict, test/test_quantization.py::TestQuantizeFx::test_shape_followed_by_quantized_op, test/test_quantization.py::TestQuantizeFx::test_standalone_module_float_interface, test/test_quantization.py::TestQuantizeFx::test_standalone_module_quantized_interface, test/test_quantization.py::TestQuantizeFx::test_state_dict, test/test_quantization.py::TestQuantizeFx::test_static_lstm_consume_tuple, test/test_quantization.py::TestQuantizeFx::test_symmetric_qnnpack_qconfig_mapping, test/test_quantization.py::TestQuantizeFx::test_torch_transpose_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFx::test_view_nontensor_args_not_observed, test/test_quantization.py::TestQuantizeFxOps::test_add_relu, test/test_quantization.py::TestQuantizeFxOps::test_add_relu_multiple_uses_of_relu, test/test_quantization.py::TestQuantizeFxOps::test_ave_pool_with_custom_cfg, test/test_quantization.py::TestQuantizeFxOps::test_cat, test/test_quantization.py::TestQuantizeFxOps::test_chunk, test/test_quantization.py::TestQuantizeFxOps::test_conv_transpose_2d, test/test_quantization.py::TestQuantizeFxOps::test_copy_node_fp32_input, test/test_quantization.py::TestQuantizeFxOps::test_div, test/test_quantization.py::TestQuantizeFxOps::test_elu, test/test_quantization.py::TestQuantizeFxOps::test_fixed_qparams_ops, test/test_quantization.py::TestQuantizeFxOps::test_gelu_normal, test/test_quantization.py::TestQuantizeFxOps::test_int8_input_no_unnecessary_fq, test/test_quantization.py::TestQuantizeFxOps::test_layer_norm, test/test_quantization.py::TestQuantizeFxOps::test_leaky_relu, test/test_quantization.py::TestQuantizeFxOps::test_linear_dynamic_fp16, test/test_quantization.py::TestQuantizeFxOps::test_norm_weight_bias, test/test_quantization.py::TestQuantizeFxOps::test_quantized_add_qat, test/test_quantization.py::TestQuantizeFxOps::test_quantized_conv_relu, test/test_quantization.py::TestQuantizeFxOps::test_silu_reference, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_graph_argument_order, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_pattern_is_entire_graph, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_placeholder_matching, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_rewriter_preserves_logic, test/test_quantization.py::TestSubgraphRewriter::test_subgraph_writer_replace_consecutive_submodules, test/test_quantization.py::TestGraphUtils::test_conv_bn_relu, test/test_quantization.py::TestDuplicateDQPass::test_simple_duplicate_dq, test/test_quantization.py::TestNumericDebugger::test_control_flow, test/test_quantization.py::TestNumericDebugger::test_prepare_for_propagation_comparison, test/test_quantization.py::TestQuantizePT2E::test_allow_exported_model_train_eval, test/test_quantization.py::TestQuantizePT2E::test_allow_exported_model_train_eval_idempotent, test/test_quantization.py::TestQuantizePT2E::test_conv_padding_bn_relu, test/test_quantization.py::TestQuantizePT2E::test_disallow_eval_train, test/test_quantization.py::TestQuantizePT2E::test_dont_fold_other_constant, test/test_quantization.py::TestQuantizePT2E::test_max_pool2d_quantizer, test/test_quantization.py::TestQuantizePT2E::test_prepare_obs_or_fq_callback, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_bfloat16_float8_e4m3fn, test/test_quantization.py::TestQuantizePT2E::test_quantization_dtype_bfloat16_float8_e5m2, test/test_quantization.py::TestQuantizePT2E::test_reentrant, test/test_quantization.py::TestQuantizePT2E::test_simple_quantizer, test/test_quantization.py::TestQuantizePT2EAffineQuantization::test_channel_group_quantization, test/test_quantization.py::TestPT2ERepresentation::test_dynamic_linear, test/test_quantization.py::TestPT2ERepresentation::test_qdq_per_channel, test/test_quantization.py::TestPT2ERepresentation::test_static_linear, test/test_quantization.py::TestXNNPACKQuantizer::test_mul_and_inplace_mul, test/test_quantization.py::TestXNNPACKQuantizer::test_obs_sharing_ops, test/test_quantization.py::TestXNNPACKQuantizer::test_qat_dynamic_linear, test/test_quantization.py::TestXNNPACKQuantizerModels::test_resnet18, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_conv2d_unary, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_dynamic_quant_linear, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_filter_conv2d_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_flatten_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_flatten_recipe2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary_dynamic_qat, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary_qat, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_binary_unary_serials, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_linear_unary_dynamic_qat, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_lowering_to_x86, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_maxpool2d_recipe, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_qat_dynamic_quant_linear, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_and_module_type_case2, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_and_module_type_with_mixed_configs, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_qconfig_with_underscores, test/test_quantization.py::TestQuantizePT2EX86Inductor::test_set_module_name_with_mixed_configs, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_fusion, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_fusion_literal_args, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_bn_per_channel_weight_bias, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_conv_transpose_bn, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_inplace_add_relu, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn1d::test_qat_preserve_source_fn_stack, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_fusion, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_conv_bn_relu_fusion_cuda, test/test_quantization.py::TestQuantizePT2EQAT_ConvBn2d::test_qat_preserve_source_fn_stack, test/test_quantization.py::TestFXGraphMatcher::test_simple_fun, test/test_quantization.py::TestFXGraphMatcher::test_simple_fusion, test/test_quantization.py::TestFXGraphMatcher::test_simple_tensor_ops, test/test_quantization.py::TestFXGraphMatcherModels::test_mobilenet_v2, test/test_quantization.py::TestFXGraphMatcherModels::test_mobilenet_v2_qat, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_shadow_loggers_cuda, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_add_shadow_loggers_meth_ptq, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_extract_weights_cuda, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_layer_names, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_linear_fp16_activations, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_match_activations_fun_ptq, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_mul_add_cat_stack_skips_shadowing, test/test_quantization.py::TestFXNumericSuiteCoreAPIs::test_user_defined_function, test/test_quantization.py::TestFXNumericSuiteNShadows::test_conv_bn_relu_mod, test/test_quantization.py::TestFXNumericSuiteNShadows::test_functions, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_deduplication, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_insert_padding, test/test_quantization.py::TestFXNumericSuiteNShadows::test_qconfig_multi_mapping_ordering, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_activations_linear, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_activations_lstm_dynamic, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_shadow_activations_lstm_dynamic, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_weights_conv, test/test_quantization.py::TestFXNumericSuiteCoreAPIsModels::test_compare_weights_linear, test/test_quantization.py::TestFxModelReportDetector::test_multi_linear_model_without_per_channel, test/test_quantization.py::TestFxModelReportDetector::test_simple_conv, test/test_quantization.py::TestFxModelReportObserver::test_zero_tensor_errors, test/test_quantization.py::TestFxModelReportClass::test_equalization_mapping_generation, test/test_quantization.py::TestFxModelReportClass::test_generate_report, test/test_quantization.py::TestFxDetectInputWeightEqualization::test_input_weight_equalization_report_gen, test/test_quantization.py::TestFxDetectOutliers::test_all_outlier_report_gen, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_prepare, test/test_quantization.py::TestEqualizeFx::test_input_weight_equalization_weights_bias, test/test_quantization.py::TestSerialization::test_conv2d_graph, test/test_quantization.py::TestSerialization::test_conv2d_graph_v3, test/test_quantization.py::TestSerialization::test_conv2d_nobias_graph, test/test_quantization.py::TestSerialization::test_conv2d_nobias_graph_v3, test/test_quantization.py::TestSerialization::test_conv2d_relu, test/test_quantization.py::TestSerialization::test_default_qat_qconfig, test/test_quantization.py::TestSerialization::test_linear_relu, test/test_quantization.py::TestQuantizeJitPasses::test_conv_trace, test/test_quantization.py::TestQuantizeJitPasses::test_dedup_module_uses, test/test_quantization.py::TestQuantizeJitPasses::test_finalize_for_linear, test/test_quantization.py::TestQuantizeJitPasses::test_foldbn_trivial_nobias, test/test_quantization.py::TestQuantizeJitPasses::test_insert_observers_for_if_consistent_observation, test/test_quantization.py::TestQuantizeJitPasses::test_replicate_dequantize_in_block, test/test_quantization.py::TestQuantizeJitOps::test_instance_norm, test/test_quantization.py::TestQuantizeJitOps::test_linear, test/test_quantization.py::TestQuantizeJitOps::test_quantized_cat, test/test_quantization.py::TestQuantizeJitOps::test_quantized_mul, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_quant_multi_uses, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_weight_observer, test/test_quantization.py::TestQuantizeDynamicJitPasses::test_dynamic_with_if, test/test_quantization.py::TestQuantizeDynamicJitOps::test_embedding_bag, test/test_quantization.py::TestDeprecatedJitQuantized::test_rnn_cell_quantized, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_quantize, test/test_quantization.py::TestAOMigrationQuantization::test_function_import_stubs, test/test_quantization.py::TestAOMigrationNNQuantized::test_functional_import, test/test_quantization.py::TestAOMigrationNNQuantized::test_import_nn_qat_dynamic_linear, test/test_quantization.py::TestAOMigrationNNQuantized::test_modules_dropout, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_qat_conv_fused, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_quantized_bn_relu, test/test_quantization.py::TestAOMigrationNNIntrinsic::test_modules_intrinsic_quantized_linear_relu, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_fuse, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_graph_module, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_fx_match_utils, test/test_quantization.py::TestAOMigrationQuantizationFx::test_function_import_quantize_fx, test/test_quantization.py::TestBitsCPU::test_cat_cpu, test/test_quantization.py::TestBitsCPU::test_types_cpu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_extremes_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_rte_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_rte_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_soak_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_cast_round_trip_subnormals_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_cat_cpu_float8_e5m2, test/test_quantization.py::TestFloat8DtypeCPU::test_cat_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_creation_with_zeros_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_creation_with_zeros_cpu_float8_e8m0fnu, test/test_quantization.py::TestFloat8DtypeCPU::test_empty_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_save_load_cpu_float8_e4m3fn, test/test_quantization.py::TestFloat8DtypeCPU::test_special_numbers_cpu_float8_e5m2fnuz, test/test_quantization.py::TestFloat8DtypeCPU::test_to_string_cpu_float8_e4m3fnuz 2025-08-26T21:29:21.5826389Z 2025-08-26T21:29:22.3406153Z Running test batch 'tests to run' cost 5988.71 seconds 2025-08-26T21:29:23.2874046Z 2025-08-26T21:29:23.2874455Z real 99m53.663s 2025-08-26T21:29:23.2874756Z user 610m16.610s 2025-08-26T21:29:23.2874999Z sys 45m6.860s 2025-08-26T21:29:23.2875230Z + assert_git_not_dirty 2025-08-26T21:29:23.2875549Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]] 2025-08-26T21:29:23.2875949Z + [[ linux-jammy-py3.13-clang12 != *xla* ]] 2025-08-26T21:29:23.2880568Z ++ git status --porcelain 2025-08-26T21:29:23.2881252Z ++ grep -v '?? third_party' 2025-08-26T21:29:52.4494777Z ++ true 2025-08-26T21:29:52.4495278Z + git_status= 2025-08-26T21:29:52.4495682Z + [[ -n '' ]] 2025-08-26T21:29:52.4496063Z + test_aten 2025-08-26T21:29:52.4496490Z + echo 'Running ATen tests with pytorch lib' 2025-08-26T21:29:52.4497094Z Running ATen tests with pytorch lib 2025-08-26T21:29:52.4497560Z + [[ -n '' ]] 2025-08-26T21:29:52.4498069Z + echo 'Running test with the build folder' 2025-08-26T21:29:52.4498597Z Running test with the build folder 2025-08-26T21:29:52.4499102Z + TEST_BASE_DIR=build/bin 2025-08-26T21:29:52.4499899Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libc10.so build/bin 2025-08-26T21:29:52.4525448Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libcaffe2*' build/bin 2025-08-26T21:29:52.4535601Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libmkldnn*' build/bin 2025-08-26T21:29:52.4546019Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libnccl*' build/bin 2025-08-26T21:29:52.4557422Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorchbind_test.so build/bin 2025-08-26T21:29:52.4565463Z + ls build/bin 2025-08-26T21:29:52.4609075Z BackoffTest c10_typeid_test 2025-08-26T21:29:52.4609529Z CMakeFiles cmake_install.cmake 2025-08-26T21:29:52.4609949Z CTestTestfile.cmake cpu_allocator_test 2025-08-26T21:29:52.4610396Z CppSignature_test cpu_generator_test 2025-08-26T21:29:52.4610887Z Dict_test cpu_profiling_allocator_test 2025-08-26T21:29:52.4611295Z Dimname_test cpu_rng_test 2025-08-26T21:29:52.4611684Z FileStoreTest dlconvertor_test 2025-08-26T21:29:52.4612076Z HashStoreTest example_allreduce 2025-08-26T21:29:52.4612869Z IListRef_test extension_backend_test 2025-08-26T21:29:52.4613501Z KernelFunction_test half_test 2025-08-26T21:29:52.4614079Z List_test inline_container_test 2025-08-26T21:29:52.4614571Z MaybeOwned_test ivalue_test 2025-08-26T21:29:52.4614958Z NamedTensor_test kernel_function_legacy_test 2025-08-26T21:29:52.4615410Z ProcessGroupGlooTest kernel_function_test 2025-08-26T21:29:52.4615835Z StorageUtils_test kernel_lambda_legacy_test 2025-08-26T21:29:52.4616234Z TCPStoreTest kernel_lambda_test 2025-08-26T21:29:52.4616616Z apply_utils_test kernel_stackbased_test 2025-08-26T21:29:52.4616980Z atest lazy_tensor_test 2025-08-26T21:29:52.4617310Z backend_fallback_test legacy_vmap_test 2025-08-26T21:29:52.4617765Z basic libc10.so 2025-08-26T21:29:52.4618054Z broadcast_test 'libcaffe2*' 2025-08-26T21:29:52.4618398Z c10_AllocatorConfig_test 'libmkldnn*' 2025-08-26T21:29:52.4618738Z c10_ArrayRef_test 'libnccl*' 2025-08-26T21:29:52.4619085Z c10_Bitset_test libtorch.so 2025-08-26T21:29:52.4619472Z c10_CompileTimeFunctionPointer_test libtorch_cpu.so 2025-08-26T21:29:52.4619927Z c10_ConstexprCrc_test libtorch_global_deps.so 2025-08-26T21:29:52.4620379Z c10_DeadlockDetection_test libtorch_python.so 2025-08-26T21:29:52.4620790Z c10_DeviceGuard_test libtorchbind_test.so 2025-08-26T21:29:52.4621232Z c10_Device_test make_boxed_from_unboxed_functor_test 2025-08-26T21:29:52.4621671Z c10_DispatchKeySet_test math_kernel_test 2025-08-26T21:29:52.4622071Z c10_Enumerate_test memory_format_test 2025-08-26T21:29:52.4622440Z c10_Half_test memory_overlapping_test 2025-08-26T21:29:52.4622865Z c10_InlineDeviceGuard_test mobile_memory_cleanup 2025-08-26T21:29:52.4623294Z c10_InlineStreamGuard_test native_test 2025-08-26T21:29:52.4623687Z c10_IntrusiveList_test op_allowlist_test 2025-08-26T21:29:52.4624090Z c10_LeftRight_test op_registration_test 2025-08-26T21:29:52.4624486Z c10_Metaprogramming_test operator_name_test 2025-08-26T21:29:52.4624887Z c10_NetworkFlow_test operators_test 2025-08-26T21:29:52.4625282Z c10_Scalar_test packedtensoraccessor_test 2025-08-26T21:29:52.4625685Z c10_Semaphore_test parallel_benchmark 2025-08-26T21:29:52.4626044Z c10_SizesAndStrides_test pow_test 2025-08-26T21:29:52.4626396Z c10_StreamGuard_test protoc 2025-08-26T21:29:52.4626729Z c10_SymInt_test protoc-3.13.0.0 2025-08-26T21:29:52.4627091Z c10_Synchronized_test quantized_test 2025-08-26T21:29:52.4627455Z c10_ThreadLocal_test reduce_ops_test 2025-08-26T21:29:52.4627847Z c10_TypeIndex_test reportMemoryUsage_test 2025-08-26T21:29:52.4628246Z c10_TypeList_test scalar_tensor_test 2025-08-26T21:29:52.4628606Z c10_TypeTraits_test scalar_test 2025-08-26T21:29:52.4628965Z c10_accumulate_test static_runtime_bench 2025-08-26T21:29:52.4629358Z c10_bfloat16_test static_runtime_test 2025-08-26T21:29:52.4629788Z c10_bit_cast_test stride_properties_test 2025-08-26T21:29:52.4630194Z c10_complex_math_test tensor_iterator_test 2025-08-26T21:29:52.4630592Z c10_complex_test test_api 2025-08-26T21:29:52.4630910Z c10_cow_test test_cpp_rpc 2025-08-26T21:29:52.4631238Z c10_error_test test_dist_autograd 2025-08-26T21:29:52.4631579Z c10_exception_test test_jit 2025-08-26T21:29:52.4631880Z c10_flags_test test_lazy 2025-08-26T21:29:52.4632206Z c10_generic_math_test test_nativert 2025-08-26T21:29:52.4632585Z c10_intrusive_ptr_benchmark test_parallel 2025-08-26T21:29:52.4632978Z c10_intrusive_ptr_test thread_init_test 2025-08-26T21:29:52.4633342Z c10_irange_test torch_shm_manager 2025-08-26T21:29:52.4633685Z c10_lazy_test type_ptr_test 2025-08-26T21:29:52.4634017Z c10_logging_test type_test 2025-08-26T21:29:52.4634404Z c10_optional_test undefined_tensor_test 2025-08-26T21:29:52.4634861Z c10_ordered_preserving_dict_test vec_test_all_types_AVX2 2025-08-26T21:29:52.4635314Z c10_registry_test vec_test_all_types_AVX512 2025-08-26T21:29:52.4635747Z c10_small_vector_test vec_test_all_types_DEFAULT 2025-08-26T21:29:52.4636165Z c10_ssize_test verify_api_visibility 2025-08-26T21:29:52.4636528Z c10_string_util_test weakref_test 2025-08-26T21:29:52.4636864Z c10_string_view_test wrapdim_test 2025-08-26T21:29:52.4637209Z c10_tempfile_test xla_tensor_test 2025-08-26T21:29:52.4638779Z + aten/tools/run_tests.sh build/bin 2025-08-26T21:29:52.4639098Z + set -e 2025-08-26T21:29:52.4639321Z ++ dirname aten/tools/run_tests.sh 2025-08-26T21:29:52.4653198Z + VALGRIND_SUP=/var/lib/jenkins/workspace/aten/tools/valgrind.sup 2025-08-26T21:29:52.4653753Z + export CPP_TESTS_DIR=build/bin 2025-08-26T21:29:52.4654069Z + CPP_TESTS_DIR=build/bin 2025-08-26T21:29:52.4654331Z + VALGRIND=ON 2025-08-26T21:29:52.4656209Z + python test/run_test.py --cpp --verbose -i cpp/basic cpp/atest cpp/scalar_test cpp/broadcast_test cpp/wrapdim_test cpp/apply_utils_test cpp/dlconvertor_test cpp/native_test cpp/scalar_tensor_test cpp/undefined_tensor_test cpp/extension_backend_test cpp/lazy_tensor_test cpp/tensor_iterator_test cpp/Dimname_test cpp/Dict_test cpp/NamedTensor_test cpp/cpu_generator_test cpp/legacy_vmap_test cpp/operators_test 2025-08-26T21:29:54.7595904Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:29:54.7597505Z import pkg_resources 2025-08-26T21:29:56.2749009Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-08-26T21:29:56.2876733Z Found test times from artifacts 2025-08-26T21:29:56.3389430Z Found test times from artifacts 2025-08-26T21:29:56.3404601Z Running all tests 2025-08-26T21:29:56.3408977Z Running parallel tests on 3 processes 2025-08-26T21:29:56.3410688Z Name: tests to run (est. time: 0.0min) 2025-08-26T21:29:56.3411012Z Serial tests (0): 2025-08-26T21:29:56.3411269Z Parallel tests (19): 2025-08-26T21:29:56.3411524Z cpp/Dict_test 1/1 2025-08-26T21:29:56.3411792Z cpp/Dimname_test 1/1 2025-08-26T21:29:56.3412076Z cpp/NamedTensor_test 1/1 2025-08-26T21:29:56.3412385Z cpp/apply_utils_test 1/1 2025-08-26T21:29:56.3412651Z cpp/atest 1/1 2025-08-26T21:29:56.3412892Z cpp/basic 1/1 2025-08-26T21:29:56.3413142Z cpp/broadcast_test 1/1 2025-08-26T21:29:56.3413441Z cpp/cpu_generator_test 1/1 2025-08-26T21:29:56.3413730Z cpp/dlconvertor_test 1/1 2025-08-26T21:29:56.3414035Z cpp/extension_backend_test 1/1 2025-08-26T21:29:56.3414354Z cpp/lazy_tensor_test 1/1 2025-08-26T21:29:56.3414653Z cpp/legacy_vmap_test 1/1 2025-08-26T21:29:56.3415109Z cpp/native_test 1/1 2025-08-26T21:29:56.3415392Z cpp/operators_test 1/1 2025-08-26T21:29:56.3415737Z cpp/scalar_tensor_test 1/1 2025-08-26T21:29:56.3416201Z cpp/scalar_test 1/1 2025-08-26T21:29:56.3416569Z cpp/tensor_iterator_test 1/1 2025-08-26T21:29:56.3416890Z cpp/undefined_tensor_test 1/1 2025-08-26T21:29:56.3417206Z cpp/wrapdim_test 1/1 2025-08-26T21:29:56.3417497Z Name: excluded (est. time: 0.0min) 2025-08-26T21:29:56.3417792Z Serial tests (0): 2025-08-26T21:29:56.3418048Z Parallel tests (0): 2025-08-26T21:29:56.3418392Z Running cpp/Dict_test 1/1 ... [2025-08-26 21:29:56.341507] 2025-08-26T21:29:56.3418800Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:29:56.3421981Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dict_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-5a67628f3e75230f.xml', '-x', '--reruns=2'] ... [2025-08-26 21:29:56.341985] 2025-08-26T21:29:57.8093155Z 2025-08-26T21:29:57.8094180Z cpp/Dict_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dict_test_1.1_def575aacf394c39_.log 2025-08-26T21:29:57.8094829Z 2025-08-26T21:29:59.3290329Z Uploading artifacts took 1.52 seconds 2025-08-26T21:29:59.3290823Z Running cpp/Dimname_test 1/1 ... [2025-08-26 21:29:59.328827] 2025-08-26T21:29:59.3291259Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:29:59.3295167Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dimname_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-c5b6103372675057.xml', '-x', '--reruns=2'] ... [2025-08-26 21:29:59.329264] 2025-08-26T21:30:00.7956568Z 2025-08-26T21:30:00.7957435Z cpp/Dimname_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dimname_test_1.1_be647116dc4f9da0_.log 2025-08-26T21:30:00.7958236Z 2025-08-26T21:30:00.7958466Z Running cpp/NamedTensor_test 1/1 ... [2025-08-26 21:30:00.795565] 2025-08-26T21:30:00.7958908Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:00.7961610Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/NamedTensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-ff33548255b89938.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:00.795932] 2025-08-26T21:30:02.3129646Z 2025-08-26T21:30:02.3130538Z cpp/NamedTensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.NamedTensor_test_1.1_9fde01abc88b0649_.log 2025-08-26T21:30:02.3131245Z 2025-08-26T21:30:02.3131459Z Running cpp/apply_utils_test 1/1 ... [2025-08-26 21:30:02.312843] 2025-08-26T21:30:02.3131917Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:02.3133845Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/apply_utils_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-69c92f717b449ce6.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:02.313180] 2025-08-26T21:30:03.8299356Z 2025-08-26T21:30:03.8300470Z cpp/apply_utils_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.apply_utils_test_1.1_bd26ed35aa86495e_.log 2025-08-26T21:30:03.8301171Z 2025-08-26T21:30:03.8301348Z Running cpp/atest 1/1 ... [2025-08-26 21:30:03.829798] 2025-08-26T21:30:03.8301747Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:03.8303844Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/atest', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-d8fc13077c306122.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:03.830155] 2025-08-26T21:30:05.3468380Z 2025-08-26T21:30:05.3469281Z cpp/atest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.atest_1.1_86a6bf92e736617d_.log 2025-08-26T21:30:05.3469894Z 2025-08-26T21:30:05.3470300Z Running cpp/basic 1/1 ... [2025-08-26 21:30:05.346700] 2025-08-26T21:30:05.3470683Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:05.3473183Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/basic', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-03f3ed1d4bbb17ff.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:05.347072] 2025-08-26T21:30:06.8136536Z 2025-08-26T21:30:06.8137562Z cpp/basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.basic_1.1_800ce68c05c0dec7_.log 2025-08-26T21:30:06.8138165Z 2025-08-26T21:30:06.8138364Z Running cpp/broadcast_test 1/1 ... [2025-08-26 21:30:06.813431] 2025-08-26T21:30:06.8138887Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:06.8140317Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/broadcast_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-2d222fa80d59c26b.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:06.813828] 2025-08-26T21:30:08.2801736Z 2025-08-26T21:30:08.2802668Z cpp/broadcast_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.broadcast_test_1.1_5dac14b404a8b280_.log 2025-08-26T21:30:08.2803351Z 2025-08-26T21:30:08.2803588Z Running cpp/cpu_generator_test 1/1 ... [2025-08-26 21:30:08.280075] 2025-08-26T21:30:08.2804022Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:08.2806481Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/cpu_generator_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-4ba216e15284c9b8.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:08.280423] 2025-08-26T21:30:09.7468154Z 2025-08-26T21:30:09.7469122Z cpp/cpu_generator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.cpu_generator_test_1.1_185a068ba3166880_.log 2025-08-26T21:30:09.7469882Z 2025-08-26T21:30:09.7470103Z Running cpp/dlconvertor_test 1/1 ... [2025-08-26 21:30:09.746741] 2025-08-26T21:30:09.7470552Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:09.7473631Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/dlconvertor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-35f0f40a1f8231f8.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:09.747142] 2025-08-26T21:30:11.2134842Z 2025-08-26T21:30:11.2135837Z cpp/dlconvertor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.dlconvertor_test_1.1_61ab7c403aaaeae5_.log 2025-08-26T21:30:11.2136548Z 2025-08-26T21:30:11.2136802Z Running cpp/extension_backend_test 1/1 ... [2025-08-26 21:30:11.213375] 2025-08-26T21:30:11.2137249Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:11.2139209Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/extension_backend_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-b24410828d453016.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:11.213693] 2025-08-26T21:30:12.6801274Z 2025-08-26T21:30:12.6802384Z cpp/extension_backend_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.extension_backend_test_1.1_2e6577b3f11ba6f5_.log 2025-08-26T21:30:12.6803132Z 2025-08-26T21:30:12.6803359Z Running cpp/lazy_tensor_test 1/1 ... [2025-08-26 21:30:12.680003] 2025-08-26T21:30:12.6803786Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:12.6805785Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/lazy_tensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-0ae0094b8f72bc45.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:12.680373] 2025-08-26T21:30:14.1467885Z 2025-08-26T21:30:14.1469596Z cpp/lazy_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.lazy_tensor_test_1.1_c03785a7eb60555e_.log 2025-08-26T21:30:14.1470770Z 2025-08-26T21:30:14.1471219Z Running cpp/legacy_vmap_test 1/1 ... [2025-08-26 21:30:14.146633] 2025-08-26T21:30:14.1471985Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:14.1474104Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/legacy_vmap_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-42b98d50e00e9a4b.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:14.147012] 2025-08-26T21:30:15.6134580Z 2025-08-26T21:30:15.6135516Z cpp/legacy_vmap_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.legacy_vmap_test_1.1_961ae24fee757dec_.log 2025-08-26T21:30:15.6136237Z 2025-08-26T21:30:15.6136431Z Running cpp/native_test 1/1 ... [2025-08-26 21:30:15.613363] 2025-08-26T21:30:15.6137027Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:15.6139340Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/native_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-2ee8574f40b37981.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:15.613702] 2025-08-26T21:30:17.0801779Z 2025-08-26T21:30:17.0803012Z cpp/native_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.native_test_1.1_add7f5c77204ccfe_.log 2025-08-26T21:30:17.0804070Z 2025-08-26T21:30:17.0804402Z Running cpp/operators_test 1/1 ... [2025-08-26 21:30:17.080034] 2025-08-26T21:30:17.0805071Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:17.0807461Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/operators_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-72ad203411d5c354.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:17.080429] 2025-08-26T21:30:18.5472321Z 2025-08-26T21:30:18.5473231Z cpp/operators_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.operators_test_1.1_de66b282cd28acb8_.log 2025-08-26T21:30:18.5473912Z 2025-08-26T21:30:18.5474162Z Running cpp/scalar_tensor_test 1/1 ... [2025-08-26 21:30:18.547130] 2025-08-26T21:30:18.5474600Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:18.5476577Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_tensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-e542201d93883393.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:18.547447] 2025-08-26T21:30:20.0143330Z 2025-08-26T21:30:20.0144640Z cpp/scalar_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_tensor_test_1.1_e5729d9bdfa72250_.log 2025-08-26T21:30:20.0145383Z 2025-08-26T21:30:20.0145582Z Running cpp/scalar_test 1/1 ... [2025-08-26 21:30:20.014204] 2025-08-26T21:30:20.0146022Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:20.0148231Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-4315e2c59eb8c180.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:20.014552] 2025-08-26T21:30:21.4809831Z 2025-08-26T21:30:21.4810680Z cpp/scalar_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_test_1.1_48302816ad882362_.log 2025-08-26T21:30:21.4811325Z 2025-08-26T21:30:21.4811572Z Running cpp/tensor_iterator_test 1/1 ... [2025-08-26 21:30:21.480853] 2025-08-26T21:30:21.4812021Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:21.4814887Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/tensor_iterator_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-3cb727c18beb27ac.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:21.481215] 2025-08-26T21:30:22.9476153Z 2025-08-26T21:30:22.9477335Z cpp/tensor_iterator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.tensor_iterator_test_1.1_a65f5b4b1261d48a_.log 2025-08-26T21:30:22.9478080Z 2025-08-26T21:30:22.9478342Z Running cpp/undefined_tensor_test 1/1 ... [2025-08-26 21:30:22.947491] 2025-08-26T21:30:22.9478798Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:22.9480635Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/undefined_tensor_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-2f510065bbd81b9a.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:22.947851] 2025-08-26T21:30:24.4147480Z 2025-08-26T21:30:24.4148412Z cpp/undefined_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.undefined_tensor_test_1.1_90ffc74f9614b433_.log 2025-08-26T21:30:24.4149423Z 2025-08-26T21:30:24.4149642Z Running cpp/wrapdim_test 1/1 ... [2025-08-26 21:30:24.414614] 2025-08-26T21:30:24.4150071Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:24.4152029Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/wrapdim_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-2f70bc3cb5d9524b.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:24.414977] 2025-08-26T21:30:25.8815583Z 2025-08-26T21:30:25.8816564Z cpp/wrapdim_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.wrapdim_test_1.1_57c06a9043c56291_.log 2025-08-26T21:30:25.8817224Z 2025-08-26T21:30:28.3394304Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:28.3396376Z import pkg_resources 2025-08-26T21:30:28.3443651Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:28.3445258Z import pkg_resources 2025-08-26T21:30:28.3704533Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:28.3706209Z import pkg_resources 2025-08-26T21:30:28.4644753Z Running cpp/Dict_test 1/1 ... [2025-08-26 21:30:28.464211] 2025-08-26T21:30:28.4645196Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:28.4648834Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dict_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-a46660d2ec10d6c7.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:28.464639] 2025-08-26T21:30:28.4686474Z Running cpp/Dimname_test 1/1 ... [2025-08-26 21:30:28.468476] 2025-08-26T21:30:28.4686907Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:28.4690882Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/Dimname_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-09fa8920530f524e.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:28.468858] 2025-08-26T21:30:28.4958960Z Running cpp/NamedTensor_test 1/1 ... [2025-08-26 21:30:28.495625] 2025-08-26T21:30:28.4959488Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:28.4963103Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/NamedTensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-5100031e7db3279b.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:28.496034] 2025-08-26T21:30:30.6873134Z 2025-08-26T21:30:30.6874083Z cpp/Dimname_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dimname_test_1.1_d723582f6410484f_.log 2025-08-26T21:30:30.6874757Z 2025-08-26T21:30:31.3157977Z 2025-08-26T21:30:31.3159215Z cpp/NamedTensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.NamedTensor_test_1.1_3857c684c09185b3_.log 2025-08-26T21:30:31.3160014Z 2025-08-26T21:30:34.1994661Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:34.1996459Z import pkg_resources 2025-08-26T21:30:34.3274466Z Running cpp/apply_utils_test 1/1 ... [2025-08-26 21:30:34.327134] 2025-08-26T21:30:34.3274970Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:34.3278299Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/apply_utils_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-25b3c4be911567e4.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:34.327571] 2025-08-26T21:30:34.6395638Z 2025-08-26T21:30:34.6396464Z cpp/Dict_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.Dict_test_1.1_8f6da1e8769aefea_.log 2025-08-26T21:30:34.6397372Z 2025-08-26T21:30:34.6831781Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:34.6833361Z import pkg_resources 2025-08-26T21:30:34.8092132Z Running cpp/atest 1/1 ... [2025-08-26 21:30:34.808839] 2025-08-26T21:30:34.8092565Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:34.8095700Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/atest', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-0099196edb01906e.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:34.809295] 2025-08-26T21:30:36.6461219Z 2025-08-26T21:30:36.6462776Z cpp/apply_utils_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.apply_utils_test_1.1_9e12aca868fa6cb6_.log 2025-08-26T21:30:36.6464067Z 2025-08-26T21:30:38.0619855Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:38.0621554Z import pkg_resources 2025-08-26T21:30:38.0789053Z 2025-08-26T21:30:38.0789550Z cpp/atest 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.atest_1.1_6078f15511428437_.log 2025-08-26T21:30:38.0790254Z 2025-08-26T21:30:38.1875762Z Running cpp/basic 1/1 ... [2025-08-26 21:30:38.187311] 2025-08-26T21:30:38.1876193Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:38.1879915Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/basic', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-e60c7baf76aa5672.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:38.187747] 2025-08-26T21:30:39.9348317Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:39.9351357Z import pkg_resources 2025-08-26T21:30:40.0624530Z Running cpp/broadcast_test 1/1 ... [2025-08-26 21:30:40.062091] 2025-08-26T21:30:40.0625025Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:40.0628217Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/broadcast_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-559f0451cc74978e.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:40.062554] 2025-08-26T21:30:40.5564196Z 2025-08-26T21:30:40.5565216Z cpp/basic 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.basic_1.1_7a9d5f35cd99dba2_.log 2025-08-26T21:30:40.5566209Z 2025-08-26T21:30:41.3455662Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:41.3458398Z import pkg_resources 2025-08-26T21:30:41.4723503Z Running cpp/cpu_generator_test 1/1 ... [2025-08-26 21:30:41.471894] 2025-08-26T21:30:41.4724002Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:41.4725757Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/cpu_generator_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-a29b4e330bd7b19e.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:41.472320] 2025-08-26T21:30:41.9800826Z 2025-08-26T21:30:41.9802419Z cpp/broadcast_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.broadcast_test_1.1_994455c77545cb09_.log 2025-08-26T21:30:41.9803659Z 2025-08-26T21:30:43.8913725Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:43.8915329Z import pkg_resources 2025-08-26T21:30:44.0192502Z Running cpp/dlconvertor_test 1/1 ... [2025-08-26 21:30:44.018916] 2025-08-26T21:30:44.0192994Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:44.0196173Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/dlconvertor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-6f1d2cbd832a544b.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:44.019334] 2025-08-26T21:30:44.6921327Z 2025-08-26T21:30:44.6922786Z cpp/cpu_generator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.cpu_generator_test_1.1_60f510efbe80dd3c_.log 2025-08-26T21:30:44.6924156Z 2025-08-26T21:30:45.3619892Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:45.3621478Z import pkg_resources 2025-08-26T21:30:45.4901740Z Running cpp/extension_backend_test 1/1 ... [2025-08-26 21:30:45.489766] 2025-08-26T21:30:45.4902611Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:45.4905252Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/extension_backend_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-b0eaa9d3ca7cf18a.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:45.490197] 2025-08-26T21:30:46.1374365Z 2025-08-26T21:30:46.1375491Z cpp/dlconvertor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.dlconvertor_test_1.1_27afbaa82de41896_.log 2025-08-26T21:30:46.1376225Z 2025-08-26T21:30:47.3578383Z 2025-08-26T21:30:47.3579949Z cpp/extension_backend_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.extension_backend_test_1.1_1bde4b79f8557ed1_.log 2025-08-26T21:30:47.3581440Z 2025-08-26T21:30:48.0046295Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:48.0049453Z import pkg_resources 2025-08-26T21:30:48.1324669Z Running cpp/lazy_tensor_test 1/1 ... [2025-08-26 21:30:48.132116] 2025-08-26T21:30:48.1325851Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:48.1328444Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/lazy_tensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-41b12203fc96f8cd.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:48.132535] 2025-08-26T21:30:49.4724041Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:49.4725882Z import pkg_resources 2025-08-26T21:30:49.5991722Z Running cpp/legacy_vmap_test 1/1 ... [2025-08-26 21:30:49.598834] 2025-08-26T21:30:49.5992200Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:49.5995287Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/legacy_vmap_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-98f4431e3e5d2d33.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:49.599262] 2025-08-26T21:30:49.9496925Z 2025-08-26T21:30:49.9497841Z cpp/lazy_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.lazy_tensor_test_1.1_5b711eb4c0dd6952_.log 2025-08-26T21:30:49.9498549Z 2025-08-26T21:30:50.6333353Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:50.6336513Z import pkg_resources 2025-08-26T21:30:50.7625810Z Running cpp/native_test 1/1 ... [2025-08-26 21:30:50.762166] 2025-08-26T21:30:50.7626612Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:50.7629123Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/native_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-976192584a344314.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:50.762609] 2025-08-26T21:30:52.7327998Z 2025-08-26T21:30:52.7328955Z cpp/native_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.native_test_1.1_b3c531d5f451818f_.log 2025-08-26T21:30:52.7329615Z 2025-08-26T21:30:53.3636068Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:53.3639307Z import pkg_resources 2025-08-26T21:30:53.4202091Z 2025-08-26T21:30:53.4203339Z cpp/legacy_vmap_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.legacy_vmap_test_1.1_8acef57c37055ab2_.log 2025-08-26T21:30:53.4204054Z 2025-08-26T21:30:53.4910031Z Running cpp/operators_test 1/1 ... [2025-08-26 21:30:53.490706] 2025-08-26T21:30:53.4910510Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:53.4914471Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/operators_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-615aa143ecf064a4.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:53.491174] 2025-08-26T21:30:55.7092512Z 2025-08-26T21:30:55.7093638Z cpp/operators_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.operators_test_1.1_c0301e4ebbd378c7_.log 2025-08-26T21:30:55.7094370Z 2025-08-26T21:30:56.0311600Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:56.0313413Z import pkg_resources 2025-08-26T21:30:56.1579488Z Running cpp/scalar_tensor_test 1/1 ... [2025-08-26 21:30:56.157618] 2025-08-26T21:30:56.1579964Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:56.1583351Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_tensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-fcee9d9274c86dce.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:56.158065] 2025-08-26T21:30:56.7261934Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:56.7264983Z import pkg_resources 2025-08-26T21:30:56.8788922Z Running cpp/scalar_test 1/1 ... [2025-08-26 21:30:56.878504] 2025-08-26T21:30:56.8789754Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:56.8792749Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/scalar_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-8411c99973516091.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:56.878957] 2025-08-26T21:30:58.1755951Z 2025-08-26T21:30:58.1756893Z cpp/scalar_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_tensor_test_1.1_9fde8ab056426bee_.log 2025-08-26T21:30:58.1757628Z 2025-08-26T21:30:58.9604827Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:30:58.9606429Z import pkg_resources 2025-08-26T21:30:59.0873238Z Running cpp/tensor_iterator_test 1/1 ... [2025-08-26 21:30:59.086975] 2025-08-26T21:30:59.0873742Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:30:59.0876523Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/tensor_iterator_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-1584d75037482555.xml', '-x', '--reruns=2'] ... [2025-08-26 21:30:59.087397] 2025-08-26T21:30:59.0966908Z 2025-08-26T21:30:59.0967537Z cpp/scalar_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.scalar_test_1.1_dbe3fe1b4dfa85bc_.log 2025-08-26T21:30:59.0968267Z 2025-08-26T21:31:01.5097719Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:01.5099341Z import pkg_resources 2025-08-26T21:31:01.6431732Z Running cpp/undefined_tensor_test 1/1 ... [2025-08-26 21:31:01.642772] 2025-08-26T21:31:01.6432247Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:31:01.6435274Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/undefined_tensor_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-9d796ed7f29b6aff.xml', '-x', '--reruns=2'] ... [2025-08-26 21:31:01.643233] 2025-08-26T21:31:02.4092531Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:02.4095698Z import pkg_resources 2025-08-26T21:31:02.5388844Z Running cpp/wrapdim_test 1/1 ... [2025-08-26 21:31:02.538477] 2025-08-26T21:31:02.5389323Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:31:02.5391958Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/wrapdim_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-47d7ba7659db53d6.xml', '-x', '--reruns=2'] ... [2025-08-26 21:31:02.538919] 2025-08-26T21:31:03.5611054Z 2025-08-26T21:31:03.5612309Z cpp/undefined_tensor_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.undefined_tensor_test_1.1_10f85c7963b304e4_.log 2025-08-26T21:31:03.5613355Z 2025-08-26T21:31:04.4570454Z 2025-08-26T21:31:04.4571833Z cpp/wrapdim_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.wrapdim_test_1.1_01e9b744b9443cb5_.log 2025-08-26T21:31:04.4573039Z 2025-08-26T21:31:07.0148677Z 2025-08-26T21:31:07.0150015Z cpp/tensor_iterator_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.tensor_iterator_test_1.1_0d555876eb2f0f01_.log 2025-08-26T21:31:07.0151194Z 2025-08-26T21:31:07.1256506Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:07.1258721Z import pkg_resources 2025-08-26T21:31:07.7926448Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:07.7928051Z import pkg_resources 2025-08-26T21:31:08.5605060Z Running test batch 'tests to run' cost 72.22 seconds 2025-08-26T21:31:09.2765119Z + run_if_exists tensor_interop_test 2025-08-26T21:31:09.2765605Z + local test_name=tensor_interop_test 2025-08-26T21:31:09.2766101Z + [[ -x build/bin/tensor_interop_test ]] 2025-08-26T21:31:09.2766550Z + echo 'Warning: tensor_interop_test does not exist.' 2025-08-26T21:31:09.2767048Z Warning: tensor_interop_test does not exist. 2025-08-26T21:31:09.2767465Z + run_if_exists cudnn_test 2025-08-26T21:31:09.2767840Z + local test_name=cudnn_test 2025-08-26T21:31:09.2768221Z + [[ -x build/bin/cudnn_test ]] 2025-08-26T21:31:09.2768696Z + echo 'Warning: cudnn_test does not exist.' 2025-08-26T21:31:09.2769199Z Warning: cudnn_test does not exist. 2025-08-26T21:31:09.2769663Z + run_if_exists cuda_generator_test 2025-08-26T21:31:09.2770020Z + local test_name=cuda_generator_test 2025-08-26T21:31:09.2770642Z + [[ -x build/bin/cuda_generator_test ]] 2025-08-26T21:31:09.2771035Z + echo 'Warning: cuda_generator_test does not exist.' 2025-08-26T21:31:09.2771442Z Warning: cuda_generator_test does not exist. 2025-08-26T21:31:09.2771859Z + run_if_exists apply_test 2025-08-26T21:31:09.2772141Z + local test_name=apply_test 2025-08-26T21:31:09.2772441Z + [[ -x build/bin/apply_test ]] 2025-08-26T21:31:09.2772769Z + echo 'Warning: apply_test does not exist.' 2025-08-26T21:31:09.2773166Z Warning: apply_test does not exist. 2025-08-26T21:31:09.2773477Z + run_if_exists stream_test 2025-08-26T21:31:09.2773772Z + local test_name=stream_test 2025-08-26T21:31:09.2774076Z + [[ -x build/bin/stream_test ]] 2025-08-26T21:31:09.2774406Z + echo 'Warning: stream_test does not exist.' 2025-08-26T21:31:09.2774750Z Warning: stream_test does not exist. 2025-08-26T21:31:09.2775073Z + run_if_exists cuda_half_test 2025-08-26T21:31:09.2775395Z + local test_name=cuda_half_test 2025-08-26T21:31:09.2775772Z + [[ -x build/bin/cuda_half_test ]] 2025-08-26T21:31:09.2776124Z + echo 'Warning: cuda_half_test does not exist.' 2025-08-26T21:31:09.2776486Z Warning: cuda_half_test does not exist. 2025-08-26T21:31:09.2776830Z + run_if_exists cuda_vectorized_test 2025-08-26T21:31:09.2777167Z + local test_name=cuda_vectorized_test 2025-08-26T21:31:09.2777517Z + [[ -x build/bin/cuda_vectorized_test ]] 2025-08-26T21:31:09.2777899Z + echo 'Warning: cuda_vectorized_test does not exist.' 2025-08-26T21:31:09.2778312Z Warning: cuda_vectorized_test does not exist. 2025-08-26T21:31:09.2778682Z + run_if_exists cuda_distributions_test 2025-08-26T21:31:09.2779039Z + local test_name=cuda_distributions_test 2025-08-26T21:31:09.2779391Z + [[ -x build/bin/cuda_distributions_test ]] 2025-08-26T21:31:09.2779854Z + echo 'Warning: cuda_distributions_test does not exist.' 2025-08-26T21:31:09.2780287Z Warning: cuda_distributions_test does not exist. 2025-08-26T21:31:09.2780664Z + run_if_exists cuda_optional_test 2025-08-26T21:31:09.2780984Z + local test_name=cuda_optional_test 2025-08-26T21:31:09.2781326Z + [[ -x build/bin/cuda_optional_test ]] 2025-08-26T21:31:09.2781706Z + echo 'Warning: cuda_optional_test does not exist.' 2025-08-26T21:31:09.2782103Z Warning: cuda_optional_test does not exist. 2025-08-26T21:31:09.2782448Z + run_if_exists cuda_tensor_interop_test 2025-08-26T21:31:09.2782802Z + local test_name=cuda_tensor_interop_test 2025-08-26T21:31:09.2783161Z + [[ -x build/bin/cuda_tensor_interop_test ]] 2025-08-26T21:31:09.2783569Z + echo 'Warning: cuda_tensor_interop_test does not exist.' 2025-08-26T21:31:09.2783990Z Warning: cuda_tensor_interop_test does not exist. 2025-08-26T21:31:09.2784362Z + run_if_exists cuda_complex_test 2025-08-26T21:31:09.2784681Z + local test_name=cuda_complex_test 2025-08-26T21:31:09.2785014Z + [[ -x build/bin/cuda_complex_test ]] 2025-08-26T21:31:09.2785368Z + echo 'Warning: cuda_complex_test does not exist.' 2025-08-26T21:31:09.2785759Z Warning: cuda_complex_test does not exist. 2025-08-26T21:31:09.2786113Z + run_if_exists cuda_complex_math_test 2025-08-26T21:31:09.2786450Z + local test_name=cuda_complex_math_test 2025-08-26T21:31:09.2786787Z + [[ -x build/bin/cuda_complex_math_test ]] 2025-08-26T21:31:09.2787186Z + echo 'Warning: cuda_complex_math_test does not exist.' 2025-08-26T21:31:09.2787607Z Warning: cuda_complex_math_test does not exist. 2025-08-26T21:31:09.2787968Z + run_if_exists cuda_cub_test 2025-08-26T21:31:09.2788266Z + local test_name=cuda_cub_test 2025-08-26T21:31:09.2788562Z + [[ -x build/bin/cuda_cub_test ]] 2025-08-26T21:31:09.2788902Z + echo 'Warning: cuda_cub_test does not exist.' 2025-08-26T21:31:09.2789267Z Warning: cuda_cub_test does not exist. 2025-08-26T21:31:09.2789602Z + run_if_exists cuda_atomic_ops_test 2025-08-26T21:31:09.2789924Z + local test_name=cuda_atomic_ops_test 2025-08-26T21:31:09.2790268Z + [[ -x build/bin/cuda_atomic_ops_test ]] 2025-08-26T21:31:09.2790655Z + echo 'Warning: cuda_atomic_ops_test does not exist.' 2025-08-26T21:31:09.2791071Z Warning: cuda_atomic_ops_test does not exist. 2025-08-26T21:31:09.2791448Z + '[' ON == ON ']' 2025-08-26T21:31:09.2792171Z + valgrind --suppressions=/var/lib/jenkins/workspace/aten/tools/valgrind.sup --error-exitcode=1 build/bin/basic '--gtest_filter=-*CUDA' 2025-08-26T21:31:09.3042594Z ==77876== Memcheck, a memory error detector 2025-08-26T21:31:09.3043117Z ==77876== Copyright (C) 2002-2022, and GNU GPL'd, by Julian Seward et al. 2025-08-26T21:31:09.3043697Z ==77876== Using Valgrind-3.20.0 and LibVEX; rerun with -h for copyright info 2025-08-26T21:31:09.3044228Z ==77876== Command: build/bin/basic --gtest_filter=-*CUDA 2025-08-26T21:31:09.3044596Z ==77876== 2025-08-26T21:31:09.8630418Z ==77876== Warning: set address range perms: large range [0x4a4c000, 0x1a629000) (defined) 2025-08-26T21:31:09.8631142Z ==77876== Warning: set address range perms: large range [0x5c2f000, 0x173f8000) (defined) 2025-08-26T21:31:33.6273752Z Running main() from /var/lib/jenkins/workspace/third_party/googletest/googletest/src/gtest_main.cc 2025-08-26T21:31:33.6564049Z Note: Google Test filter = -*CUDA 2025-08-26T21:31:33.6615150Z [==========] Running 6 tests from 1 test suite. 2025-08-26T21:31:33.6642585Z [----------] Global test environment set-up. 2025-08-26T21:31:33.6714148Z [----------] 6 tests from BasicTest 2025-08-26T21:31:33.6738603Z [ RUN ] BasicTest.BasicTestCPU 2025-08-26T21:31:34.2411524Z hwloc x86 backend cannot work under Valgrind, disabling. 2025-08-26T21:31:34.2412061Z May be reenabled by dumping CPUIDs with hwloc-gather-cpuid 2025-08-26T21:31:34.2412536Z and reloading them under Valgrind with HWLOC_CPUID_PATH. 2025-08-26T21:31:34.2997378Z hwloc x86 backend cannot work under Valgrind, disabling. 2025-08-26T21:31:34.2997940Z May be reenabled by dumping CPUIDs with hwloc-gather-cpuid 2025-08-26T21:31:34.2998628Z and reloading them under Valgrind with HWLOC_CPUID_PATH. 2025-08-26T21:31:34.3795626Z hwloc x86 backend cannot work under Valgrind, disabling. 2025-08-26T21:31:34.3796120Z May be reenabled by dumping CPUIDs with hwloc-gather-cpuid 2025-08-26T21:31:34.3796682Z and reloading them under Valgrind with HWLOC_CPUID_PATH. 2025-08-26T21:31:35.5482619Z 724 ms 2025-08-26T21:31:35.6330778Z 56 ms 2025-08-26T21:31:35.7080588Z 66 ms 2025-08-26T21:31:36.9291991Z [ OK ] BasicTest.BasicTestCPU (3253 ms) 2025-08-26T21:31:36.9319173Z [ RUN ] BasicTest.BasicTestHalfCPU 2025-08-26T21:31:37.2301742Z 247 ms 2025-08-26T21:31:37.2828170Z 47 ms 2025-08-26T21:31:37.3506879Z 65 ms 2025-08-26T21:31:37.4052867Z [ OK ] BasicTest.BasicTestHalfCPU (469 ms) 2025-08-26T21:31:37.4053286Z [ RUN ] BasicTest.FactoryMethodsTest 2025-08-26T21:31:37.4386516Z [ OK ] BasicTest.FactoryMethodsTest (33 ms) 2025-08-26T21:31:37.4386908Z [ RUN ] BasicTest.BasicStdTestCPU 2025-08-26T21:31:37.5188749Z Simple example: called once 2025-08-26T21:31:37.6065183Z throw: call_once will retry 2025-08-26T21:31:37.6464963Z throw: call_once will retry 2025-08-26T21:31:37.6470592Z Didn't throw, call_once will not attempt again 2025-08-26T21:31:37.6490446Z [ OK ] BasicTest.BasicStdTestCPU (210 ms) 2025-08-26T21:31:37.6490864Z [ RUN ] BasicTest.TestForBlobResizeCPU 2025-08-26T21:31:37.6666446Z [ OK ] BasicTest.TestForBlobResizeCPU (17 ms) 2025-08-26T21:31:37.6666873Z [ RUN ] BasicTest.TestForBlobStridesResizeCPU 2025-08-26T21:31:37.6700030Z [ OK ] BasicTest.TestForBlobStridesResizeCPU (3 ms) 2025-08-26T21:31:37.6721520Z [----------] 6 tests from BasicTest (3997 ms total) 2025-08-26T21:31:37.6721802Z 2025-08-26T21:31:37.6733877Z [----------] Global test environment tear-down 2025-08-26T21:31:37.6762441Z [==========] 6 tests from 1 test suite ran. (4023 ms total) 2025-08-26T21:31:37.6774970Z [ PASSED ] 6 tests. 2025-08-26T21:31:39.6224180Z ==77876== 2025-08-26T21:31:39.6227662Z ==77876== HEAP SUMMARY: 2025-08-26T21:31:39.6228031Z ==77876== in use at exit: 433,012 bytes in 6,391 blocks 2025-08-26T21:31:39.6228556Z ==77876== total heap usage: 651,808 allocs, 645,417 frees, 199,634,563 bytes allocated 2025-08-26T21:31:39.6229015Z ==77876== 2025-08-26T21:31:39.6597439Z ==77876== LEAK SUMMARY: 2025-08-26T21:31:39.6597763Z ==77876== definitely lost: 0 bytes in 0 blocks 2025-08-26T21:31:39.6598155Z ==77876== indirectly lost: 0 bytes in 0 blocks 2025-08-26T21:31:39.6598604Z ==77876== possibly lost: 69,920 bytes in 2 blocks 2025-08-26T21:31:39.6599023Z ==77876== still reachable: 363,092 bytes in 6,389 blocks 2025-08-26T21:31:39.6599430Z ==77876== suppressed: 0 bytes in 0 blocks 2025-08-26T21:31:39.6599899Z ==77876== Rerun with --leak-check=full to see details of leaked memory 2025-08-26T21:31:39.6600306Z ==77876== 2025-08-26T21:31:39.6600642Z ==77876== For lists of detected and suppressed errors, rerun with: -s 2025-08-26T21:31:39.6601191Z ==77876== ERROR SUMMARY: 0 errors from 0 contexts (suppressed: 0 from 0) 2025-08-26T21:31:39.7026117Z + [[ -x build/bin/tensor_interop_test ]] 2025-08-26T21:31:39.7028053Z + [[ -n '' ]] 2025-08-26T21:31:39.7028281Z + assert_git_not_dirty 2025-08-26T21:31:39.7028728Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]] 2025-08-26T21:31:39.7029101Z + [[ linux-jammy-py3.13-clang12 != *xla* ]] 2025-08-26T21:31:39.7034421Z ++ git status --porcelain 2025-08-26T21:31:39.7035725Z ++ grep -v '?? third_party' 2025-08-26T21:31:39.9556029Z ++ true 2025-08-26T21:31:39.9556597Z + git_status= 2025-08-26T21:31:39.9556869Z + [[ -n '' ]] 2025-08-26T21:31:39.9557117Z + test_libtorch 1 2025-08-26T21:31:39.9557374Z + local SHARD=1 2025-08-26T21:31:39.9557625Z + [[ default != \s\l\o\w ]] 2025-08-26T21:31:39.9557910Z + echo 'Testing libtorch' 2025-08-26T21:31:39.9558183Z Testing libtorch 2025-08-26T21:31:39.9559001Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libbackend_with_compiler.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9569121Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libjitbackend_test.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9579249Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libcaffe2_nvrtc.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9589808Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libc10.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9599941Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libshm /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libshm.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libshm_windows /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9612203Z + ln -sf /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_cpu.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_global_deps.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorch_python.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libtorchbind_test.so /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9621714Z + ln -sf '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/lib/libnvfuser*' /opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9630987Z + export CPP_TESTS_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9631667Z + CPP_TESTS_DIR=/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin 2025-08-26T21:31:39.9632137Z + [[ -z 1 ]] 2025-08-26T21:31:39.9632370Z + [[ 1 == \1 ]] 2025-08-26T21:31:39.9632614Z + test_libtorch_api 2025-08-26T21:31:39.9632948Z + MNIST_DIR=/var/lib/jenkins/workspace/test/cpp/api/mnist 2025-08-26T21:31:39.9633559Z + python tools/download_mnist.py --quiet -d /var/lib/jenkins/workspace/test/cpp/api/mnist 2025-08-26T21:31:40.0110090Z Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz ... 2025-08-26T21:31:40.0541870Z Failed to download (trying next): 2025-08-26T21:31:40.0542254Z HTTP Error 404: Not Found 2025-08-26T21:31:40.0542952Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz ... 2025-08-26T21:31:40.3906581Z Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz ... 2025-08-26T21:31:40.3963536Z Failed to download (trying next): 2025-08-26T21:31:40.3963895Z HTTP Error 404: Not Found 2025-08-26T21:31:40.3964417Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz ... 2025-08-26T21:31:40.4438117Z Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz ... 2025-08-26T21:31:40.4492199Z Failed to download (trying next): 2025-08-26T21:31:40.4492540Z HTTP Error 404: Not Found 2025-08-26T21:31:40.4493056Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz ... 2025-08-26T21:31:40.5429710Z Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz ... 2025-08-26T21:31:40.5479027Z Failed to download (trying next): 2025-08-26T21:31:40.5479541Z HTTP Error 404: Not Found 2025-08-26T21:31:40.5480064Z Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz ... 2025-08-26T21:31:40.5857225Z + [[ linux-jammy-py3.13-clang12 == *asan* ]] 2025-08-26T21:31:40.5857682Z + [[ linux-jammy-py3.13-clang12 == *slow-gradcheck* ]] 2025-08-26T21:31:40.5858126Z + OMP_NUM_THREADS=2 2025-08-26T21:31:40.5858523Z + TORCH_CPP_TEST_MNIST_PATH=/var/lib/jenkins/workspace/test/cpp/api/mnist 2025-08-26T21:31:40.5859144Z + python test/run_test.py --cpp --verbose -i cpp/test_api -k 'not IMethodTest' 2025-08-26T21:31:42.8554635Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:42.8556441Z import pkg_resources 2025-08-26T21:31:44.3689560Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-08-26T21:31:44.3816855Z Found test times from artifacts 2025-08-26T21:31:44.4328344Z Found test times from artifacts 2025-08-26T21:31:44.4342489Z Running all tests 2025-08-26T21:31:44.4345753Z Running parallel tests on 3 processes 2025-08-26T21:31:44.4346119Z Name: tests to run (est. time: 0.0min) 2025-08-26T21:31:44.4346425Z Serial tests (0): 2025-08-26T21:31:44.4346681Z Parallel tests (1): 2025-08-26T21:31:44.4346944Z cpp/test_api 1/1 2025-08-26T21:31:44.4347218Z Name: excluded (est. time: 0.0min) 2025-08-26T21:31:44.4347510Z Serial tests (0): 2025-08-26T21:31:44.4347762Z Parallel tests (0): 2025-08-26T21:31:44.4350940Z Running cpp/test_api 1/1 ... [2025-08-26 21:31:44.434948] 2025-08-26T21:31:44.4351355Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:31:44.4356272Z Executing ['pytest', '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin/test_api', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-74100f5381b6850c.xml', '-k', 'not IMethodTest', '-x', '--reruns=2'] ... [2025-08-26 21:31:44.435377] 2025-08-26T21:31:46.4527075Z 2025-08-26T21:31:46.4528071Z cpp/test_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.test_api_1.1_d937a68de58f84e7_.log 2025-08-26T21:31:46.4528771Z 2025-08-26T21:31:47.8417623Z Uploading artifacts took 1.39 seconds 2025-08-26T21:31:50.2124225Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:50.2125846Z import pkg_resources 2025-08-26T21:31:50.2202532Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:50.2204081Z import pkg_resources 2025-08-26T21:31:50.2249205Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:31:50.2250726Z import pkg_resources 2025-08-26T21:31:50.3353982Z Running cpp/test_api 1/1 ... [2025-08-26 21:31:50.335101] 2025-08-26T21:31:50.3354413Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:31:50.3357541Z Executing ['pytest', '/opt/conda/envs/py_3.13/lib/python3.13/site-packages/torch/bin/test_api', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-584a9739a3d6c2b5.xml', '-k', 'not IMethodTest', '-x', '--reruns=2'] ... [2025-08-26 21:31:50.335496] 2025-08-26T21:33:46.2808479Z 2025-08-26T21:33:46.2809377Z cpp/test_api 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.test_api_1.1_ee7ae37b81c1946f_.log 2025-08-26T21:33:46.2821463Z 2025-08-26T21:33:47.0253139Z Running test batch 'tests to run' cost 122.59 seconds 2025-08-26T21:33:47.8608589Z + [[ linux-jammy-py3.13-clang12 != *android* ]] 2025-08-26T21:33:47.8609179Z + [[ linux-jammy-py3.13-clang12 != *cuda* ]] 2025-08-26T21:33:47.8609603Z + [[ linux-jammy-py3.13-clang12 != *asan* ]] 2025-08-26T21:33:47.8610416Z + [[ linux-jammy-py3.13-clang12 != *s390x* ]] 2025-08-26T21:33:47.8610765Z + export CPP_TESTS_DIR=build/bin 2025-08-26T21:33:47.8611140Z + CPP_TESTS_DIR=build/bin 2025-08-26T21:33:47.8611544Z + python test/run_test.py --cpp --verbose -i cpp/static_runtime_test 2025-08-26T21:33:50.1305617Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:33:50.1307165Z import pkg_resources 2025-08-26T21:33:51.6536235Z Downloading https://ossci-metrics.s3.amazonaws.com/disabled-tests-condensed.json to /var/lib/jenkins/workspace/test/.pytorch-disabled-tests.json 2025-08-26T21:33:51.6659484Z Found test times from artifacts 2025-08-26T21:33:51.7157058Z Found test times from artifacts 2025-08-26T21:33:51.7172312Z Running all tests 2025-08-26T21:33:51.7175436Z Running parallel tests on 3 processes 2025-08-26T21:33:51.7175800Z Name: tests to run (est. time: 0.0min) 2025-08-26T21:33:51.7176100Z Serial tests (0): 2025-08-26T21:33:51.7176354Z Parallel tests (1): 2025-08-26T21:33:51.7176639Z cpp/static_runtime_test 1/1 2025-08-26T21:33:51.7177021Z Name: excluded (est. time: 0.0min) 2025-08-26T21:33:51.7177310Z Serial tests (0): 2025-08-26T21:33:51.7177555Z Parallel tests (0): 2025-08-26T21:33:51.7177933Z Running cpp/static_runtime_test 1/1 ... [2025-08-26 21:33:51.717614] 2025-08-26T21:33:51.7178371Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:33:51.7182200Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/static_runtime_test', '-m', 'serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-ef02f0614f51f323.xml', '-x', '--reruns=2'] ... [2025-08-26 21:33:51.718005] 2025-08-26T21:33:53.1848107Z 2025-08-26T21:33:53.1849088Z cpp/static_runtime_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.static_runtime_test_1.1_e6c196bd110ca514_.log 2025-08-26T21:33:53.1849840Z 2025-08-26T21:33:54.7778947Z Uploading artifacts took 1.59 seconds 2025-08-26T21:33:57.1792438Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:33:57.1794014Z import pkg_resources 2025-08-26T21:33:57.1996750Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:33:57.1998286Z import pkg_resources 2025-08-26T21:33:57.1999743Z /opt/conda/envs/py_3.13/lib/python3.13/site-packages/hypothesis/entry_points.py:23: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81. 2025-08-26T21:33:57.2001384Z import pkg_resources 2025-08-26T21:33:57.3039967Z Running cpp/static_runtime_test 1/1 ... [2025-08-26 21:33:57.303695] 2025-08-26T21:33:57.3040411Z SCRIBE_GRAPHQL_ACCESS_TOKEN is set 2025-08-26T21:33:57.3043737Z Executing ['pytest', '/var/lib/jenkins/workspace/build/bin/static_runtime_test', '-m', 'not serial', '-v', '-vv', '-rfEX', '-n', '3', '--junit-xml-reruns', 'test-reports/python-pytest/test.run_test/test.run_test-396265fbc3246ce9.xml', '-x', '--reruns=2'] ... [2025-08-26 21:33:57.304145] 2025-08-26T21:40:50.8223896Z 2025-08-26T21:40:50.8224838Z cpp/static_runtime_test 1/1 was successful, full logs can be found in artifacts with path test/test-reports/cpp.static_runtime_test_1.1_b732f289878bc6b9_.log 2025-08-26T21:40:50.8228497Z 2025-08-26T21:40:51.5948588Z Running test batch 'tests to run' cost 419.88 seconds 2025-08-26T21:40:52.3170999Z + [[ -z 1 ]] 2025-08-26T21:40:52.3171288Z + [[ 1 == \2 ]] 2025-08-26T21:40:52.3171550Z + assert_git_not_dirty 2025-08-26T21:40:52.3171849Z + [[ linux-jammy-py3.13-clang12 != *rocm* ]] 2025-08-26T21:40:52.3172217Z + [[ linux-jammy-py3.13-clang12 != *xla* ]] 2025-08-26T21:40:52.3176301Z ++ git status --porcelain 2025-08-26T21:40:52.3176941Z ++ grep -v '?? third_party' 2025-08-26T21:40:52.5699959Z ++ true 2025-08-26T21:40:52.5700272Z + git_status= 2025-08-26T21:40:52.5700661Z + [[ -n '' ]] 2025-08-26T21:40:52.5701021Z + [[ linux-jammy-py3.13-clang12 == *xpu* ]] 2025-08-26T21:40:52.5701408Z + sccache_epilogue 2025-08-26T21:40:52.5701696Z + echo '::group::Sccache Compilation Log' 2025-08-26T21:40:52.5702446Z ##[group]Sccache Compilation Log 2025-08-26T21:40:52.5702813Z + echo '=================== sccache compilation log ===================' 2025-08-26T21:40:52.5703274Z =================== sccache compilation log =================== 2025-08-26T21:40:52.5703936Z + python /var/lib/jenkins/workspace/.ci/pytorch/print_sccache_log.py /var/lib/jenkins/sccache_error.log 2025-08-26T21:40:52.5840246Z + echo '=========== If your build fails, please take a look at the log above for possible reasons ===========' 2025-08-26T21:40:52.5840978Z =========== If your build fails, please take a look at the log above for possible reasons =========== 2025-08-26T21:40:52.5861731Z + sccache --show-stats 2025-08-26T21:40:52.5862060Z Compile requests 2641 2025-08-26T21:40:52.5862404Z Compile requests executed 151 2025-08-26T21:40:52.5862736Z Cache hits 94 2025-08-26T21:40:52.5863038Z Cache hits (C/C++) 94 2025-08-26T21:40:52.5863350Z Cache misses 56 2025-08-26T21:40:52.5863664Z Cache misses (C/C++) 56 2025-08-26T21:40:52.5863999Z Cache hits rate 62.67 % 2025-08-26T21:40:52.5864313Z Cache hits rate (C/C++) 62.67 % 2025-08-26T21:40:52.5864635Z Cache timeouts 0 2025-08-26T21:40:52.5864955Z Cache read errors 0 2025-08-26T21:40:52.5865471Z Forced recaches 0 2025-08-26T21:40:52.5865783Z Cache write errors 0 2025-08-26T21:40:52.5866101Z Cache errors 0 2025-08-26T21:40:52.5866505Z Compilations 56 2025-08-26T21:40:52.5866830Z Compilation failures 1 2025-08-26T21:40:52.5867165Z Non-cacheable compilations 0 2025-08-26T21:40:52.5867497Z Non-cacheable calls 54 2025-08-26T21:40:52.5867820Z Non-compilation calls 2436 2025-08-26T21:40:52.5868152Z Unsupported compiler calls 0 2025-08-26T21:40:52.5868477Z Average cache write 0.055 s 2025-08-26T21:40:52.5868815Z Average compiler 9.445 s 2025-08-26T21:40:52.5869151Z Average cache read hit 0.055 s 2025-08-26T21:40:52.5869491Z Failed distributed compilations 0 2025-08-26T21:40:52.5869711Z 2025-08-26T21:40:52.5869827Z Non-cacheable reasons: 2025-08-26T21:40:52.5870151Z -E 38 2025-08-26T21:40:52.5870481Z unknown source language 16 2025-08-26T21:40:52.5870690Z 2025-08-26T21:40:52.5870942Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-08-26T21:40:52.5871406Z Version (client) 0.10.0 2025-08-26T21:40:52.5871708Z + sccache --stop-server 2025-08-26T21:40:52.5882512Z Stopping sccache server... 2025-08-26T21:40:52.5885270Z Compile requests 2641 2025-08-26T21:40:52.5885732Z Compile requests executed 151 2025-08-26T21:40:52.5886057Z Cache hits 94 2025-08-26T21:40:52.5886379Z Cache hits (C/C++) 94 2025-08-26T21:40:52.5886701Z Cache misses 56 2025-08-26T21:40:52.5887195Z Cache misses (C/C++) 56 2025-08-26T21:40:52.5887524Z Cache hits rate 62.67 % 2025-08-26T21:40:52.5887850Z Cache hits rate (C/C++) 62.67 % 2025-08-26T21:40:52.5888192Z Cache timeouts 0 2025-08-26T21:40:52.5888590Z Cache read errors 0 2025-08-26T21:40:52.5888991Z Forced recaches 0 2025-08-26T21:40:52.5889374Z Cache write errors 0 2025-08-26T21:40:52.5889702Z Cache errors 0 2025-08-26T21:40:52.5890097Z Compilations 56 2025-08-26T21:40:52.5890430Z Compilation failures 1 2025-08-26T21:40:52.5890760Z Non-cacheable compilations 0 2025-08-26T21:40:52.5891117Z Non-cacheable calls 54 2025-08-26T21:40:52.5891454Z Non-compilation calls 2436 2025-08-26T21:40:52.5891797Z Unsupported compiler calls 0 2025-08-26T21:40:52.5892131Z Average cache write 0.055 s 2025-08-26T21:40:52.5892472Z Average compiler 9.445 s 2025-08-26T21:40:52.5892812Z Average cache read hit 0.055 s 2025-08-26T21:40:52.5893162Z Failed distributed compilations 0 2025-08-26T21:40:52.5893393Z 2025-08-26T21:40:52.5893496Z Non-cacheable reasons: 2025-08-26T21:40:52.5893769Z -E 38 2025-08-26T21:40:52.5894097Z unknown source language 16 2025-08-26T21:40:52.5894312Z 2025-08-26T21:40:52.5894568Z Cache location s3, name: ossci-compiler-cache-circleci-v2, prefix: / 2025-08-26T21:40:52.5895044Z Version (client) 0.10.0 2025-08-26T21:40:52.5895357Z + echo ::endgroup:: 2025-08-26T21:40:52.5895836Z ##[endgroup] 2025-08-26T21:40:52.5896112Z + cleanup_workspace 2025-08-26T21:40:52.5896691Z + echo 'sudo may print the following warning message that can be ignored. The chown command will still run.' 2025-08-26T21:40:52.5897539Z sudo may print the following warning message that can be ignored. The chown command will still run. 2025-08-26T21:40:52.5898370Z + echo ' sudo: setrlimit(RLIMIT_STACK): Operation not permitted' 2025-08-26T21:40:52.5898850Z sudo: setrlimit(RLIMIT_STACK): Operation not permitted 2025-08-26T21:40:52.5899578Z + echo 'For more details refer to https://github.com/sudo-project/sudo/issues/42' 2025-08-26T21:40:52.5900219Z For more details refer to https://github.com/sudo-project/sudo/issues/42 2025-08-26T21:40:52.5900761Z + sudo chown -R 1000 /var/lib/jenkins/workspace 2025-08-26T21:40:53.2610057Z ##[group]Run pytorch/test-infra/.github/actions/upload-benchmark-results@main 2025-08-26T21:40:53.2610572Z with: 2025-08-26T21:40:53.2610827Z benchmark-results-dir: test/test-reports 2025-08-26T21:40:53.2611169Z dry-run: false 2025-08-26T21:40:53.2611415Z schema-version: v3 2025-08-26T21:40:53.2611879Z github-token: *** 2025-08-26T21:40:53.2612120Z env: 2025-08-26T21:40:53.2612330Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:40:53.2612811Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:40:53.2613341Z ##[endgroup] 2025-08-26T21:40:53.2640448Z ##[group]Run set -eux 2025-08-26T21:40:53.2640743Z set -eux 2025-08-26T21:40:53.2641204Z python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-08-26T21:40:53.2641661Z  2025-08-26T21:40:53.2641895Z DEVICE_NAME="" 2025-08-26T21:40:53.2642167Z DEVICE_TYPE="" 2025-08-26T21:40:53.2642431Z  2025-08-26T21:40:53.2642725Z if command -v nvidia-smi; then 2025-08-26T21:40:53.2643191Z  # NB: I'm using PyTorch here to get the device name, however, it needs to 2025-08-26T21:40:53.2643807Z  # install the correct version of PyTorch manually for now. Any PyTorch 2025-08-26T21:40:53.2644380Z  # version is fine, I just use 2.7.1 to satify PYPIDEP linter 2025-08-26T21:40:53.2644838Z  python3 -mpip install torch==2.7.1 2025-08-26T21:40:53.2645262Z elif command -v rocminfo; then 2025-08-26T21:40:53.2645716Z  # NB: Installing torch on ROCm runner with pip here causes CI to fail 2025-08-26T21:40:53.2646307Z  # with a memoryview is too large error only on MI300 runners. Is pip 2025-08-26T21:40:53.2646902Z  # version on ROCm runner there too old? As a workaround, let's use the 2025-08-26T21:40:53.2647428Z  # GPU device name coming from rocminfo instead 2025-08-26T21:40:53.2647815Z  DEVICE_NAME=rocm 2025-08-26T21:40:53.2648312Z  DEVICE_TYPE=$(rocminfo | grep "Marketing Name" | tail -n1 | awk -F':' '{print $2}' | xargs) 2025-08-26T21:40:53.2648915Z fi 2025-08-26T21:40:53.2649142Z  2025-08-26T21:40:53.2649430Z echo "DEVICE_NAME=$DEVICE_NAME" >> $GITHUB_ENV 2025-08-26T21:40:53.2649858Z echo "DEVICE_TYPE=$DEVICE_TYPE" >> $GITHUB_ENV 2025-08-26T21:40:53.2659052Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:40:53.2659462Z env: 2025-08-26T21:40:53.2659693Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:40:53.2660177Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:40:53.2660684Z ##[endgroup] 2025-08-26T21:40:53.2690154Z + python3 -mpip install boto3==1.35.33 psutil==7.0.0 pynvml==12.0.0 2025-08-26T21:40:53.5187594Z Defaulting to user installation because normal site-packages is not writeable 2025-08-26T21:40:54.6047886Z Collecting boto3==1.35.33 2025-08-26T21:40:54.6221914Z Downloading boto3-1.35.33-py3-none-any.whl (139 kB) 2025-08-26T21:40:54.9355150Z Collecting psutil==7.0.0 2025-08-26T21:40:54.9397470Z Downloading psutil-7.0.0-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (277 kB) 2025-08-26T21:40:54.9672332Z Collecting pynvml==12.0.0 2025-08-26T21:40:54.9704179Z Downloading pynvml-12.0.0-py3-none-any.whl (26 kB) 2025-08-26T21:40:55.0167022Z Collecting s3transfer<0.11.0,>=0.10.0 2025-08-26T21:40:55.0213538Z Downloading s3transfer-0.10.4-py3-none-any.whl (83 kB) 2025-08-26T21:40:55.0267833Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.33) (0.10.0) 2025-08-26T21:40:56.2437853Z Collecting botocore<1.36.0,>=1.35.33 2025-08-26T21:40:56.2474494Z Downloading botocore-1.35.99-py3-none-any.whl (13.3 MB) 2025-08-26T21:40:56.4389442Z Collecting nvidia-ml-py<13.0.0a0,>=12.0.0 2025-08-26T21:40:56.4446108Z Downloading nvidia_ml_py-12.575.51-py3-none-any.whl (47 kB) 2025-08-26T21:40:56.4535440Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.25.10) 2025-08-26T21:40:56.4541658Z Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.33->boto3==1.35.33) (2.8.1) 2025-08-26T21:40:56.6968920Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.36.0,>=1.35.33->boto3==1.35.33) (1.15.0) 2025-08-26T21:40:56.8346783Z Installing collected packages: botocore, s3transfer, nvidia-ml-py, pynvml, psutil, boto3 2025-08-26T21:40:57.3382406Z Attempting uninstall: nvidia-ml-py 2025-08-26T21:40:57.3383591Z Found existing installation: nvidia-ml-py 11.525.84 2025-08-26T21:40:57.3397766Z Uninstalling nvidia-ml-py-11.525.84: 2025-08-26T21:40:57.3579174Z Successfully uninstalled nvidia-ml-py-11.525.84 2025-08-26T21:40:57.4156956Z Attempting uninstall: psutil 2025-08-26T21:40:57.4157882Z Found existing installation: psutil 5.9.8 2025-08-26T21:40:57.4227708Z Uninstalling psutil-5.9.8: 2025-08-26T21:40:57.4234012Z Successfully uninstalled psutil-5.9.8 2025-08-26T21:40:57.5877213Z Successfully installed boto3-1.35.33 botocore-1.35.99 nvidia-ml-py-12.575.51 psutil-7.0.0 pynvml-12.0.0 s3transfer-0.10.4 2025-08-26T21:40:57.6953419Z + DEVICE_NAME= 2025-08-26T21:40:57.6953677Z + DEVICE_TYPE= 2025-08-26T21:40:57.6953936Z + command -v nvidia-smi 2025-08-26T21:40:57.6954471Z + command -v rocminfo 2025-08-26T21:40:57.6954733Z + echo DEVICE_NAME= 2025-08-26T21:40:57.6954972Z + echo DEVICE_TYPE= 2025-08-26T21:40:57.6981516Z ##[group]Run set -eux 2025-08-26T21:40:57.6981798Z set -eux 2025-08-26T21:40:57.6982034Z  2025-08-26T21:40:57.6982291Z if [[ -z "${GITHUB_TOKEN}" ]]; then 2025-08-26T21:40:57.6982656Z  echo "Missing github-token input" 2025-08-26T21:40:57.6982987Z  exit 1 2025-08-26T21:40:57.6983223Z fi 2025-08-26T21:40:57.6988994Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:40:57.6989387Z env: 2025-08-26T21:40:57.6989611Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:40:57.6990084Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:40:57.6990578Z DEVICE_NAME: 2025-08-26T21:40:57.6990813Z DEVICE_TYPE: 2025-08-26T21:40:57.6991269Z GITHUB_TOKEN: *** 2025-08-26T21:40:57.6991516Z ##[endgroup] 2025-08-26T21:40:57.7018304Z + [[ -z *** ]] 2025-08-26T21:40:57.7072618Z ##[group]Run pytorch/test-infra/.github/actions/get-workflow-job-id@main 2025-08-26T21:40:57.7073081Z with: 2025-08-26T21:40:57.7073450Z github-token: *** 2025-08-26T21:40:57.7073690Z env: 2025-08-26T21:40:57.7073914Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:40:57.7074398Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:40:57.7074919Z DEVICE_NAME: 2025-08-26T21:40:57.7075143Z DEVICE_TYPE: 2025-08-26T21:40:57.7075383Z ##[endgroup] 2025-08-26T21:40:57.7096262Z ##[group]Run set -eux 2025-08-26T21:40:57.7096546Z set -eux 2025-08-26T21:40:57.7096791Z  2025-08-26T21:40:57.7097290Z python3 "${GITHUB_ACTION_PATH}/../../scripts/get_workflow_job_id.py" "${GITHUB_RUN_ID}" "${RUNNER_NAME}" 2025-08-26T21:40:57.7103485Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:40:57.7103912Z env: 2025-08-26T21:40:57.7104147Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:40:57.7104638Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:40:57.7105152Z DEVICE_NAME: 2025-08-26T21:40:57.7105394Z DEVICE_TYPE: 2025-08-26T21:40:57.7105791Z GITHUB_TOKEN: *** 2025-08-26T21:40:57.7106042Z ##[endgroup] 2025-08-26T21:40:57.7143403Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/get-workflow-job-id/../../scripts/get_workflow_job_id.py 17248463620 i-04da9546f7741a2d4 2025-08-26T21:40:59.9090151Z setting job-id=48944862553 2025-08-26T21:40:59.9090698Z setting job-name=linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T21:40:59.9207001Z ##[group]Run set -eux 2025-08-26T21:40:59.9207282Z set -eux 2025-08-26T21:40:59.9207514Z  2025-08-26T21:40:59.9207914Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_metadata.py" \ 2025-08-26T21:40:59.9208448Z  --schema-version "${SCHEMA_VERSION}" \ 2025-08-26T21:40:59.9208905Z  --repo "${REPO}" \ 2025-08-26T21:40:59.9209226Z  --head-branch "${HEAD_BRANCH}" \ 2025-08-26T21:40:59.9209574Z  --head-sha "${HEAD_SHA}" \ 2025-08-26T21:40:59.9210016Z  --workflow-id "${WORKFLOW_RUN_ID}" \ 2025-08-26T21:40:59.9210377Z  --run-attempt "${RUN_ATTEMPT}" \ 2025-08-26T21:40:59.9210720Z  --job-id "${JOB_ID}" \ 2025-08-26T21:40:59.9211036Z  --job-name "${JOB_NAME}" 2025-08-26T21:40:59.9216721Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:40:59.9217117Z env: 2025-08-26T21:40:59.9217332Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:40:59.9217802Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:40:59.9218311Z DEVICE_NAME: 2025-08-26T21:40:59.9218547Z DEVICE_TYPE: 2025-08-26T21:40:59.9218768Z SCHEMA_VERSION: v3 2025-08-26T21:40:59.9219032Z REPO: pytorch/pytorch 2025-08-26T21:40:59.9219302Z HEAD_BRANCH: refs/heads/main 2025-08-26T21:40:59.9219726Z HEAD_SHA: 262640fd220236042fbf4443cc163c8838c84c3d 2025-08-26T21:40:59.9220074Z WORKFLOW_RUN_ID: 17248463620 2025-08-26T21:40:59.9220355Z RUN_ATTEMPT: 1 2025-08-26T21:40:59.9220594Z JOB_ID: 48944862553 2025-08-26T21:40:59.9221005Z JOB_NAME: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T21:40:59.9221591Z ##[endgroup] 2025-08-26T21:40:59.9250218Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_metadata.py --schema-version v3 --repo pytorch/pytorch --head-branch refs/heads/main --head-sha 262640fd220236042fbf4443cc163c8838c84c3d --workflow-id 17248463620 --run-attempt 1 --job-id 48944862553 --job-name 'linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge)' 2025-08-26T21:40:59.9573064Z ##[group]Run set -eux 2025-08-26T21:40:59.9573345Z set -eux 2025-08-26T21:40:59.9573581Z  2025-08-26T21:40:59.9573983Z python3 "${GITHUB_ACTION_PATH}/../../scripts/benchmarks/gather_runners_info.py" 2025-08-26T21:40:59.9579949Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:40:59.9580346Z env: 2025-08-26T21:40:59.9580589Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:40:59.9581073Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:40:59.9581582Z DEVICE_NAME: 2025-08-26T21:40:59.9581825Z DEVICE_TYPE: 2025-08-26T21:40:59.9582065Z ##[endgroup] 2025-08-26T21:40:59.9605312Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/benchmarks/gather_runners_info.py 2025-08-26T21:41:00.0004186Z INFO:root:Fail to import torch to get the device name 2025-08-26T21:41:00.0112061Z ##[group]Run set -eux 2025-08-26T21:41:00.0112340Z set -eux 2025-08-26T21:41:00.0112579Z  2025-08-26T21:41:00.0112824Z # TODO (huydhn): Implement this part 2025-08-26T21:41:00.0113238Z echo "dependencies={}" >> "${GITHUB_OUTPUT}" 2025-08-26T21:41:00.0119044Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:00.0119444Z env: 2025-08-26T21:41:00.0119669Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:00.0120148Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:00.0120670Z DEVICE_NAME: 2025-08-26T21:41:00.0120908Z DEVICE_TYPE: 2025-08-26T21:41:00.0121139Z ##[endgroup] 2025-08-26T21:41:00.0143193Z + echo 'dependencies={}' 2025-08-26T21:41:00.0169505Z ##[group]Run set -eux 2025-08-26T21:41:00.0169798Z set -eux 2025-08-26T21:41:00.0170040Z  2025-08-26T21:41:00.0170319Z if [[ ! -d "${BENCHMARK_RESULTS_DIR}" ]]; then 2025-08-26T21:41:00.0170783Z  echo "${BENCHMARK_RESULTS_DIR} does not exist, skipping" 2025-08-26T21:41:00.0171289Z  # We don't want the job to fail if the directory doesn't exist 2025-08-26T21:41:00.0171713Z  exit 0 2025-08-26T21:41:00.0171949Z fi 2025-08-26T21:41:00.0172171Z  2025-08-26T21:41:00.0172405Z if [[ "${DRY_RUN}" == "true" ]]; then 2025-08-26T21:41:00.0172909Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-08-26T21:41:00.0173586Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-08-26T21:41:00.0174040Z  --metadata "${BENCHMARK_METADATA}" \ 2025-08-26T21:41:00.0174425Z  --runners "${RUNNER_INFO}" \ 2025-08-26T21:41:00.0174779Z  --dependencies "${DEPENDENCIES}" \ 2025-08-26T21:41:00.0175130Z  --dry-run 2025-08-26T21:41:00.0175391Z else 2025-08-26T21:41:00.0175792Z  python3 "${GITHUB_ACTION_PATH}/../../scripts/upload_benchmark_results.py" \ 2025-08-26T21:41:00.0176597Z  --benchmark-results-dir "${BENCHMARK_RESULTS_DIR}" \ 2025-08-26T21:41:00.0177046Z  --metadata "${BENCHMARK_METADATA}" \ 2025-08-26T21:41:00.0178049Z  --runners "${RUNNER_INFO}" \ 2025-08-26T21:41:00.0178417Z  --dependencies "${DEPENDENCIES}" 2025-08-26T21:41:00.0178752Z fi 2025-08-26T21:41:00.0184124Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:00.0184523Z env: 2025-08-26T21:41:00.0184752Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:00.0185238Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:00.0185754Z DEVICE_NAME: 2025-08-26T21:41:00.0185996Z DEVICE_TYPE: 2025-08-26T21:41:00.0186266Z BENCHMARK_RESULTS_DIR: test/test-reports 2025-08-26T21:41:00.0186601Z DRY_RUN: false 2025-08-26T21:41:00.0188174Z BENCHMARK_METADATA: {"timestamp": 1756244459, "schema_version": "v3", "name": "linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "262640fd220236042fbf4443cc163c8838c84c3d", "workflow_id": 17248463620, "run_attempt": 1, "job_id": 48944862553} 2025-08-26T21:41:00.0189938Z RUNNER_INFO: [{"cpu_info": "x86_64", "cpu_count": 16, "avail_mem_in_gb": 30, "extra_info": {"hostname": "ip-10-0-28-8.ec2.internal"}, "name": "", "type": ""}] 2025-08-26T21:41:00.0190620Z DEPENDENCIES: {} 2025-08-26T21:41:00.0190871Z ##[endgroup] 2025-08-26T21:41:00.0212972Z + [[ ! -d test/test-reports ]] 2025-08-26T21:41:00.0213309Z + [[ false == \t\r\u\e ]] 2025-08-26T21:41:00.0216192Z + python3 /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py --benchmark-results-dir test/test-reports --metadata '{"timestamp": 1756244459, "schema_version": "v3", "name": "linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge)", "repo": "pytorch/pytorch", "head_branch": "refs/heads/main", "head_sha": "262640fd220236042fbf4443cc163c8838c84c3d", "workflow_id": 17248463620, "run_attempt": 1, "job_id": 48944862553}' --runners '[{"cpu_info": "x86_64", "cpu_count": 16, "avail_mem_in_gb": 30, "extra_info": {"hostname": "ip-10-0-28-8.ec2.internal"}, "name": "", "type": ""}]' --dependencies '{}' 2025-08-26T21:41:00.1615803Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'lazy/test_ts_opinfo'}], 'excluded': []} from test/test-reports/td_exclusions-1180137ec5a52cb432e0.json is not a benchmark record, skipping 2025-08-26T21:41:00.1617871Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-08-26T21:41:00.1699337Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'inductor/test_flex_attention'}, {'test_file': 'inductor/test_aot_inductor_arrayref'}, {'test_file': 'inductor/test_torchinductor'}, {'test_file': 'inductor/test_extension_backend'}, {'test_file': 'inductor/test_compiled_autograd'}, {'test_file': 'inductor/test_torchinductor_dynamic_shapes'}, {'test_file': 'dynamo/cpython/3_13/test_sort'}, {'test_file': 'inductor/test_torchinductor_codegen_dynamic_shapes'}, {'test_file': 'inductor/test_triton_kernels'}, {'test_file': 'inductor/test_compiled_optimizers'}, {'test_file': 'dynamo/test_utils'}, {'test_file': 'dynamo/test_dynamic_shapes'}, {'test_file': 'inductor/test_cpu_cpp_wrapper'}, {'test_file': 'inductor/test_minifier'}, {'test_file': 'inductor/test_compile_subprocess'}, {'test_file': 'dynamo/test_dicts'}, {'test_file': 'inductor/test_memory'}, {'test_file': 'inductor/test_split_cat_fx_aten_passes'}, {'test_file': 'inductor/test_inductor_freezing'}, {'test_file': 'dynamo/test_modes'}, {'test_file': 'export/test_torchbind'}, {'test_file': 'dynamo/test_package'}, {'test_file': 'dynamo/test_functions'}, {'test_file': 'dynamo/test_logging'}, {'test_file': 'dynamo/test_repros'}, {'test_file': 'dynamo/test_structured_trace'}, {'test_file': 'dynamo/test_higher_order_ops'}, {'test_file': 'inductor/test_torchbind'}, {'test_file': 'inductor/test_cpu_repro'}, {'test_file': 'dynamo/test_error_messages'}, {'test_file': 'dynamo/test_exceptions'}, {'test_file': 'dynamo/test_aot_autograd_cache'}, {'test_file': 'dynamo/test_trace_rules'}, {'test_file': 'dynamo/test_misc'}, {'test_file': 'dynamo/test_recompile_ux'}, {'test_file': 'dynamo/test_subclasses'}, {'test_file': 'test_autograd'}, {'test_file': 'export/test_draft_export'}, {'test_file': 'test_nestedtensor'}, {'test_file': 'test_ci_sanity_check_fail'}, {'test_file': 'test_type_hints'}, {'test_file': 'nn/test_parametrization'}, {'test_file': 'test_jit_fuser_te'}, {'test_file': 'test_jit'}, {'test_file': 'test_binary_ufuncs'}, {'test_file': 'higher_order_ops/test_with_effects'}, {'test_file': 'test_overrides'}, {'test_file': 'test_content_store'}, {'test_file': 'test_numpy_interop'}, {'test_file': 'functorch/test_control_flow'}, {'test_file': 'test_reductions'}, {'test_file': 'functorch/test_aotdispatch'}, {'test_file': 'test_tensor_creation_ops'}, {'test_file': 'test_cpp_extensions_mtia_backend'}, {'test_file': 'test_nn'}, {'test_file': 'test_cpp_extensions_stream_and_event'}, {'test_file': 'test_indexing'}, {'test_file': 'test_type_promotion'}, {'test_file': 'functorch/test_eager_transforms'}, {'test_file': 'doctests'}, {'test_file': 'inductor/test_aot_inductor'}, {'test_file': 'inductor/test_max_autotune'}, {'test_file': 'inductor/test_flex_decoding'}, {'test_file': 'inductor/test_perf'}, {'test_file': 'export/test_export_training_ir_to_run_decomp'}, {'test_file': 'inductor/test_provenance_tracing'}, {'test_file': 'inductor/test_torchinductor_opinfo'}, {'test_file': 'dynamo/cpython/3_13/test_generator_stop'}, {'test_file': 'inductor/test_kernel_benchmark'}, {'test_file': 'dynamo/cpython/3_13/test_exception_variations'}, {'test_file': 'dynamo/test_fx_graph_runnable'}, {'test_file': 'inductor/test_inplace_padding'}, {'test_file': 'dynamo/cpython/3_13/test_int_literal'}, {'test_file': 'dynamo/cpython/3_13/test_itertools'}, {'test_file': 'dynamo/cpython/3_13/test_contextlib'}, {'test_file': 'dynamo/cpython/3_13/test_numeric_tower'}, {'test_file': 'dynamo/cpython/3_13/test_ordered_dict'}, {'test_file': 'dynamo/cpython/3_13/test_with'}, {'test_file': 'dynamo/cpython/3_13/test_baseexception'}, {'test_file': 'dynamo/cpython/3_13/test_exceptions'}, {'test_file': 'dynamo/cpython/3_13/test_raise'}, {'test_file': 'dynamo/cpython/3_13/test_userlist'}, {'test_file': 'dynamo/cpython/3_13/test_generators'}, {'test_file': 'inductor/test_pattern_matcher'}, {'test_file': 'inductor/test_analysis'}, {'test_file': 'dynamo/cpython/3_13/test_int'}, {'test_file': 'dynamo/cpython/3_13/test_userdict'}, {'test_file': 'dynamo/cpython/3_13/test_defaultdict'}, {'test_file': 'dynamo/cpython/3_13/test_collections'}, {'test_file': 'dynamo/cpython/3_13/test_heapq'}, {'test_file': 'dynamo/cpython/3_13/test_cmath'}, {'test_file': 'dynamo/cpython/3_13/test_operator'}, {'test_file': 'dynamo/cpython/3_13/test_set'}, {'test_file': 'dynamo/cpython/3_13/test_math'}, {'test_file': 'dynamo/cpython/3_13/test_iter'}, {'test_file': 'dynamo/cpython/3_13/test_sys'}, {'test_file': 'inductor/test_snode_runtime'}, {'test_file': 'dynamo/cpython/3_13/test_bool'}, {'test_file': 'dynamo/cpython/3_13/test_list'}, {'test_file': 'dynamo/cpython/3_13/test_float'}, {'test_file': 'dynamo/cpython/3_13/test_tuple'}, {'test_file': 'dynamo/cpython/3_13/test_dict'}, {'test_file': 'dynamo/cpython/3_13/test_complex'}, {'test_file': 'inductor/test_external_callables'}, {'test_file': 'inductor/test_fused_attention'}, {'test_file': 'inductor/test_triton_syntax'}, {'test_file': 'inductor/test_halide'}, {'test_file': 'inductor/test_pad_mm'}, {'test_file': 'dynamo/test_deque_reconstruct'}, {'test_file': 'inductor/test_cpp_wrapper_hipify'}, {'test_file': 'inductor/test_segmented_tree'}, {'test_file': 'inductor/test_inductor_utils'}, {'test_file': 'inductor/test_triton_extension_backend'}, {'test_file': 'export/test_retraceability'}, {'test_file': 'inductor/test_b2b_gemm'}, {'test_file': 'inductor/test_async_compile'}, {'test_file': 'inductor/test_indexing'}, {'test_file': 'inductor/test_inductor_annotations'}, {'test_file': 'inductor/test_fx_fusion'}, {'test_file': 'inductor/test_triton_cpu_backend'}, {'test_file': 'export/test_functionalized_assertions'}, {'test_file': 'export/test_unflatten_training_ir'}, {'test_file': 'dynamo/test_fx_passes_pre_grad'}, {'test_file': 'inductor/test_ck_backend'}, {'test_file': 'inductor/test_torchinductor_strided_blocks'}, {'test_file': 'dynamo/test_backends'}, {'test_file': 'inductor/test_op_completeness'}, {'test_file': 'inductor/test_metrics'}, {'test_file': 'dynamo/test_base_output'}, {'test_file': 'inductor/test_autoheuristic'}, {'test_file': 'inductor/test_compile_worker'}, {'test_file': 'dynamo/test_inline_and_install'}, {'test_file': 'test_model_exports_to_core_aten'}, {'test_file': 'inductor/test_move_constructors_to_cuda'}, {'test_file': 'export/test_tree_utils'}, {'test_file': 'inductor/test_remote_cache'}, {'test_file': 'inductor/test_minifier_utils'}, {'test_file': 'inductor/test_xpu_basic'}, {'test_file': 'dynamo/test_decorators'}, {'test_file': 'inductor/test_utils'}, {'test_file': 'export/test_export_strict'}, {'test_file': 'inductor/test_subgraph_choice'}, {'test_file': 'dynamo/test_recompiles'}, {'test_file': 'export/test_serdes'}, {'test_file': 'inductor/test_mps_basic'}, {'test_file': 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{'test_file': 'dynamo/test_resume'}, {'test_file': 'dynamo/test_pgo'}, {'test_file': 'dynamo/test_export_mutations'}, {'test_file': 'inductor/test_aot_inductor_utils'}, {'test_file': 'inductor/test_control_flow'}, {'test_file': 'inductor/test_config'}, {'test_file': 'inductor/test_ordered_set'}, {'test_file': 'export/test_db'}, {'test_file': 'dynamo/test_unittest'}, {'test_file': 'dynamo/test_compile'}, {'test_file': 'inductor/test_custom_lowering'}, {'test_file': 'inductor/test_dependencies'}, {'test_file': 'inductor/test_alignment'}, {'test_file': 'dynamo/test_guard_serialization'}, {'test_file': 'dynamo/test_autograd_function'}, {'test_file': 'dynamo/test_install_free_tensors'}, {'test_file': 'inductor/test_compile'}, {'test_file': 'dynamo/test_after_aot'}, {'test_file': 'inductor/test_scatter_optimization'}, {'test_file': 'inductor/test_layout_optim'}, {'test_file': 'inductor/test_torchinductor_codegen_config_overrides'}, {'test_file': 'export/test_passes'}, {'test_file': 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'export/test_converter'}, {'test_file': 'dynamo/test_torchrec'}, {'test_file': 'export/test_experimental'}, {'test_file': 'export/test_pass_infra'}, {'test_file': 'dynamo/test_guard_manager'}, {'test_file': 'dynamo/test_minifier'}, {'test_file': 'dynamo/test_activation_checkpointing'}, {'test_file': 'inductor/test_cudagraph_trees_expandable_segments'}, {'test_file': 'dynamo/test_exc'}, {'test_file': 'dynamo/test_precompile_context'}, {'test_file': 'export/test_lift_unlift'}, {'test_file': 'export/test_serialize'}, {'test_file': 'inductor/test_distributed_patterns'}, {'test_file': 'dynamo/test_hooks'}, {'test_file': 'dynamo/test_fake_distributed'}, {'test_file': 'dynamo/test_generator'}, {'test_file': 'dynamo/test_reorder_logs'}, {'test_file': 'export/test_verifier'}, {'test_file': 'export/test_sparse'}, {'test_file': 'dynamo/test_comptime'}, {'test_file': 'dynamo/test_python_autograd'}, {'test_file': 'test_utils'}, {'test_file': 'test_ao_sparsity'}, {'test_file': 'test_package'}, {'test_file': 'profiler/test_kineto'}, {'test_file': 'higher_order_ops/test_invoke_subgraph'}, {'test_file': 'test_comparison_utils'}, {'test_file': 'functorch/test_ac_logging'}, {'test_file': 'test_mkl_verbose'}, {'test_file': 'test_fx'}, {'test_file': 'test_decomp'}, {'test_file': 'test_transformers'}, {'test_file': 'test_transformers_privateuse1'}, {'test_file': 'test_mkldnn_verbose'}, {'test_file': 'test_utils_config_module'}, {'test_file': 'test_ops_jit'}, {'test_file': 'test_cpp_api_parity'}, {'test_file': 'test_dataloader'}, {'test_file': 'test_modules'}, {'test_file': 'test_appending_byte_serializer'}, {'test_file': 'profiler/test_profiler'}, {'test_file': 'test_hop_infra'}, {'test_file': 'test_matmul_cuda'}, {'test_file': 'test_cuda'}, {'test_file': 'xpu/test_fusion'}, {'test_file': 'test_license'}, {'test_file': 'test_autoload'}, {'test_file': 'test_rename_privateuse1_to_existing_device'}, {'test_file': 'test_extension_utils'}, {'test_file': 'test_openreg'}, {'test_file': 'torch_np/test_binary_ufuncs'}, {'test_file': 'typing/test_python_operators'}, {'test_file': 'torch_np/test_unary_ufuncs'}, {'test_file': 'test_proxy_tensor'}, {'test_file': 'torch_np/test_dtype'}, {'test_file': 'test_datapipe'}, {'test_file': 'test_foreach'}, {'test_file': 'test_flop_counter'}, {'test_file': 'test_expanded_weights'}, {'test_file': 'test_file_check'}, {'test_file': 'test_functionalization'}, {'test_file': 'test_testing'}, {'test_file': 'backends/xeon/test_launch'}, {'test_file': 'functorch/test_ops'}, {'test_file': 'test_openmp'}, {'test_file': 'test_show_pickle'}, {'test_file': 'test_fx_experimental'}, {'test_file': 'test_torch'}, {'test_file': 'torch_np/test_nep50_examples'}, {'test_file': 'test_module_tracker'}, {'test_file': 'test_ops'}, {'test_file': 'test_tensorexpr_pybind'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarinherit'}, {'test_file': 'functorch/test_minifier'}, {'test_file': 'test_native_functions'}, {'test_file': 'test_namedtensor'}, {'test_file': 'xpu/test_gemm'}, {'test_file': 'test_custom_ops'}, {'test_file': 'profiler/test_memory_profiler'}, {'test_file': 'test_tensorexpr'}, {'test_file': 'torch_np/test_basic'}, {'test_file': 'test_typing'}, {'test_file': 'test_optim'}, {'test_file': 'test_utils_filelock'}, {'test_file': 'test_fx_passes'}, {'test_file': 'lazy/test_bindings'}, {'test_file': 'test_pytree'}, {'test_file': 'functorch/test_logging'}, {'test_file': 'test_jiterator'}, {'test_file': 'test_complex'}, {'test_file': 'functorch/test_ac_knapsack'}, {'test_file': 'higher_order_ops/test_invoke_quant'}, {'test_file': 'torch_np/test_random'}, {'test_file': 'xpu/test_conv'}, {'test_file': 'test_weak'}, {'test_file': 'test_compile_benchmark_util'}, {'test_file': 'test_cuda_multigpu'}, {'test_file': 'test_per_overload_api'}, {'test_file': 'test_legacy_vmap'}, {'test_file': 'test_hub'}, {'test_file': 'lazy/test_functionalization'}, {'test_file': 'torch_np/numpy_tests/core/test_einsum'}, {'test_file': 'test_set_default_mobile_cpu_allocator'}, {'test_file': 'test_meta'}, {'test_file': 'test_stateless'}, {'test_file': 'functorch/test_ac'}, {'test_file': 'test_namedtuple_return_api'}, {'test_file': 'distributions/test_constraints'}, {'test_file': 'cpp_extensions/python_agnostic_extension/test/test_python_agnostic'}, {'test_file': 'torch_np/test_ufuncs_basic'}, {'test_file': 'test_out_dtype_op'}, {'test_file': 'test_ops_gradients'}, {'test_file': 'test_ops_fwd_gradients'}, {'test_file': 'lazy/test_step_closures'}, {'test_file': 'test_multiprocessing'}, {'test_file': 'test_sparse_semi_structured'}, {'test_file': 'nn/test_packed_sequence'}, {'test_file': 'test_autograd_fallback'}, {'test_file': 'profiler/test_record_function'}, {'test_file': 'nn/test_lazy_modules'}, {'test_file': 'test_fx_reinplace_pass'}, {'test_file': 'profiler/test_cpp_thread'}, {'test_file': 'test_cuda_expandable_segments'}, {'test_file': 'test_numba_integration'}, {'test_file': 'test_segment_reductions'}, {'test_file': 'test_fake_tensor'}, {'test_file': 'test_logging'}, {'test_file': 'test_functionalization_of_rng_ops'}, {'test_file': 'functorch/test_aot_joint_with_descriptors'}, {'test_file': 'test_python_dispatch'}, {'test_file': 'test_subclass'}, {'test_file': 'test_itt'}, {'test_file': 'profiler/test_torch_tidy'}, {'test_file': 'torch_np/numpy_tests/core/test_numeric'}, {'test_file': 'test_bundled_inputs'}, {'test_file': 'test_masked'}, {'test_file': 'test_monitor'}, {'test_file': 'test_sympy_utils'}, {'test_file': 'torch_np/numpy_tests/lib/test_function_base'}, {'test_file': 'test_autocast'}, {'test_file': 'functorch/test_vmap_registrations'}, {'test_file': 'torch_np/test_indexing'}, {'test_file': 'test_cuda_sanitizer'}, {'test_file': 'optim/test_swa_utils'}, {'test_file': 'optim/test_lrscheduler'}, {'test_file': 'test_jit_disabled'}, {'test_file': 'cpp_extensions/libtorch_agnostic_extension/test/test_libtorch_agnostic'}, {'test_file': 'dynamo/test_nested_graph_breaks'}, {'test_file': 'test_mkldnn_fusion'}, {'test_file': 'test_import_stats'}, {'test_file': 'test_tensorboard'}, {'test_file': 'nn/test_embedding'}, {'test_file': 'nn/test_dropout'}, {'test_file': 'torch_np/numpy_tests/lib/test_type_check'}, {'test_file': 'test_public_bindings'}, {'test_file': 'torch_np/numpy_tests/core/test_indexing'}, {'test_file': 'test_maskedtensor'}, {'test_file': 'torch_np/numpy_tests/lib/test_histograms'}, {'test_file': 'lazy/test_ts_opinfo'}, {'test_file': 'test_schema_check'}, {'test_file': 'test_functional_optim'}, {'test_file': 'profiler/test_execution_trace'}, {'test_file': 'test_futures'}, {'test_file': 'test_dispatch'}, {'test_file': 'test_linalg'}, {'test_file': 'benchmark_utils/test_benchmark_utils'}, {'test_file': 'optim/test_optim'}, {'test_file': 'test_native_mha'}, {'test_file': 'torch_np/numpy_tests/core/test_scalarmath'}, {'test_file': 'test_vulkan'}, {'test_file': 'nn/test_load_state_dict'}, {'test_file': 'torch_np/numpy_tests/core/test_shape_base'}, {'test_file': 'test_shape_ops'}, {'test_file': 'torch_np/numpy_tests/core/test_dtype'}, {'test_file': 'nn/test_module_hooks'}, {'test_file': 'test_sort_and_select'}, {'test_file': 'test_dynamic_shapes'}, {'test_file': 'torch_np/numpy_tests/lib/test_twodim_base'}, {'test_file': 'test_jit_llga_fuser'}, {'test_file': 'test_type_info'}, {'test_file': 'torch_np/numpy_tests/linalg/test_linalg'}, {'test_file': 'test_serialization'}, {'test_file': 'test_sparse_csr'}, {'test_file': 'lazy/test_generator'}, {'test_file': 'lazy/test_debug_util'}, {'test_file': 'test_numa_binding'}, {'test_file': 'test_view_ops'}, {'test_file': 'torch_np/numpy_tests/fft/test_pocketfft'}, {'test_file': 'torch_np/test_ndarray_methods'}, {'test_file': 'torch_np/numpy_tests/lib/test_shape_base_'}, {'test_file': 'torch_np/numpy_tests/core/test_getlimits'}, {'test_file': 'test_scatter_gather_ops'}, {'test_file': 'functorch/test_vmap'}, {'test_file': 'test_mkldnn'}, {'test_file': 'torch_np/numpy_tests/core/test_dlpack'}, {'test_file': 'test_unary_ufuncs'}, {'test_file': 'test_cpp_extensions_jit'}, {'test_file': 'nn/test_pooling'}, {'test_file': 'test_xnnpack_integration'}, {'test_file': 'torch_np/numpy_tests/lib/test_index_tricks'}, {'test_file': 'nn/test_init'}, {'test_file': 'nn/test_convolution'}, {'test_file': 'test_multiprocessing_spawn'}, {'test_file': 'test_cuda_primary_ctx'}, {'test_file': 'test_accelerator'}, {'test_file': 'torch_np/numpy_tests/core/test_numerictypes'}, {'test_file': 'torch_np/numpy_tests/fft/test_helper'}, {'test_file': 'test_function_schema'}, {'test_file': 'torch_np/test_function_base'}, {'test_file': 'test_mobile_optimizer'}, {'test_file': 'test_cuda_trace'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_methods'}, {'test_file': 'test_cuda_nvml_based_avail'}, {'test_file': 'test_sparse'}, {'test_file': 'torch_np/test_scalars_0D_arrays'}, {'test_file': 'test_jit_autocast'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraysetops'}, {'test_file': 'test_dlpack'}, {'test_file': 'profiler/test_profiler_tree'}, {'test_file': 'torch_np/numpy_tests/core/test_scalar_ctors'}, {'test_file': 'torch_np/test_reductions'}, {'test_file': 'lazy/test_reuse_ir'}, {'test_file': 'torch_np/numpy_tests/lib/test_arraypad'}, {'test_file': 'test_quantization'}, {'test_file': 'test_spectral_ops'}, {'test_file': 'test_functional_autograd_benchmark'}, {'test_file': 'test_prims'}, {'test_file': 'profiler/test_python_tracer'}, {'test_file': 'distributions/test_distributions'}, {'test_file': 'test_cpp_extensions_aot_no_ninja'}, {'test_file': 'test_autoload_disable'}, {'test_file': 'test_autoload_enable'}, {'test_file': 'test_cpp_extensions_aot_ninja'}], 'excluded': []} from test/test-reports/td_exclusions-0c524fe4f3e86cfa47f1.json is not a benchmark record, skipping 2025-08-26T21:41:00.1779004Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-08-26T21:41:00.1780777Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/static_runtime_test'}], 'excluded': []} from test/test-reports/td_exclusions-a60c0ad5354c5980bd9f.json is not a benchmark record, skipping 2025-08-26T21:41:00.1782510Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-08-26T21:41:00.1784191Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/test_api'}], 'excluded': []} from test/test-reports/td_exclusions-27da19f69b5b341ee5f3.json is not a benchmark record, skipping 2025-08-26T21:41:00.1785855Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-08-26T21:41:00.1789972Z /home/ec2-user/actions-runner/_work/_actions/pytorch/test-infra/main/.github/actions/upload-benchmark-results/../../scripts/upload_benchmark_results.py:236: UserWarning: {'included': [{'test_file': 'cpp/Dict_test'}, {'test_file': 'cpp/Dimname_test'}, {'test_file': 'cpp/NamedTensor_test'}, {'test_file': 'cpp/apply_utils_test'}, {'test_file': 'cpp/atest'}, {'test_file': 'cpp/basic'}, {'test_file': 'cpp/broadcast_test'}, {'test_file': 'cpp/cpu_generator_test'}, {'test_file': 'cpp/dlconvertor_test'}, {'test_file': 'cpp/extension_backend_test'}, {'test_file': 'cpp/lazy_tensor_test'}, {'test_file': 'cpp/legacy_vmap_test'}, {'test_file': 'cpp/native_test'}, {'test_file': 'cpp/operators_test'}, {'test_file': 'cpp/scalar_tensor_test'}, {'test_file': 'cpp/scalar_test'}, {'test_file': 'cpp/tensor_iterator_test'}, {'test_file': 'cpp/undefined_tensor_test'}, {'test_file': 'cpp/wrapdim_test'}], 'excluded': []} from test/test-reports/td_exclusions-3f67fc1acdf1ed67b487.json is not a benchmark record, skipping 2025-08-26T21:41:00.1793927Z warn(f"{result} from {filepath} is not a benchmark record, skipping") 2025-08-26T21:41:00.1887617Z ##[group]Run cat test/**/*_toprint.log || true 2025-08-26T21:41:00.1888058Z cat test/**/*_toprint.log || true 2025-08-26T21:41:00.1893898Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:00.1894307Z env: 2025-08-26T21:41:00.1894535Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:00.1895006Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:00.1895596Z DEVICE_NAME: 2025-08-26T21:41:00.1895831Z DEVICE_TYPE: 2025-08-26T21:41:00.1896063Z ##[endgroup] 2025-08-26T21:41:00.1980266Z cat: 'test/**/*_toprint.log': No such file or directory 2025-08-26T21:41:00.2014683Z ##[group]Run kill "$MONITOR_SCRIPT_PID" 2025-08-26T21:41:00.2015070Z kill "$MONITOR_SCRIPT_PID" 2025-08-26T21:41:00.2020552Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:00.2020951Z env: 2025-08-26T21:41:00.2021178Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:00.2021660Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:00.2022168Z DEVICE_NAME: 2025-08-26T21:41:00.2022409Z DEVICE_TYPE: 2025-08-26T21:41:00.2022739Z MONITOR_SCRIPT_PID: 42433 2025-08-26T21:41:00.2023024Z ##[endgroup] 2025-08-26T21:41:00.2170494Z Prepare all required actions 2025-08-26T21:41:00.2170965Z Getting action download info 2025-08-26T21:41:00.3618864Z Download action repository 'seemethere/upload-artifact-s3@v5' (SHA:baba72d0712b404f646cebe0730933554ebce96a) 2025-08-26T21:41:00.5690794Z Download action repository 'actions/upload-artifact@v4' (SHA:ea165f8d65b6e75b540449e92b4886f43607fa02) 2025-08-26T21:41:01.0517897Z ##[group]Run ./.github/actions/upload-test-artifacts 2025-08-26T21:41:01.0518286Z with: 2025-08-26T21:41:01.0518608Z file-suffix: test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T21:41:01.0519025Z s3-bucket: gha-artifacts 2025-08-26T21:41:01.0519289Z env: 2025-08-26T21:41:01.0519513Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:01.0520018Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:01.0520540Z DEVICE_NAME: 2025-08-26T21:41:01.0520766Z DEVICE_TYPE: 2025-08-26T21:41:01.0521016Z ##[endgroup] 2025-08-26T21:41:01.0550132Z ##[group]Run # Remove any previous test jsons if they exist 2025-08-26T21:41:01.0550619Z # Remove any previous test jsons if they exist 2025-08-26T21:41:01.0551010Z rm -f test-jsons-*.zip 2025-08-26T21:41:01.0551461Z zip -r "test-jsons-${FILE_SUFFIX}.zip" test/test-reports -i '*.json' 2025-08-26T21:41:01.0557352Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:01.0557752Z env: 2025-08-26T21:41:01.0557969Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:01.0558455Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:01.0558982Z DEVICE_NAME: 2025-08-26T21:41:01.0559222Z DEVICE_TYPE: 2025-08-26T21:41:01.0559552Z FILE_SUFFIX: test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T21:41:01.0559939Z ##[endgroup] 2025-08-26T21:41:01.0701406Z adding: test/test-reports/td_exclusions-1180137ec5a52cb432e0.json (deflated 16%) 2025-08-26T21:41:01.0705838Z adding: test/test-reports/td_exclusions-0c524fe4f3e86cfa47f1.json (deflated 82%) 2025-08-26T21:41:01.0706528Z adding: test/test-reports/td_exclusions-a60c0ad5354c5980bd9f.json (deflated 14%) 2025-08-26T21:41:01.0707217Z adding: test/test-reports/td_exclusions-27da19f69b5b341ee5f3.json (deflated 18%) 2025-08-26T21:41:01.0707898Z adding: test/test-reports/td_exclusions-3f67fc1acdf1ed67b487.json (deflated 73%) 2025-08-26T21:41:01.0738637Z ##[group]Run # Remove any previous test reports if they exist 2025-08-26T21:41:01.0739145Z # Remove any previous test reports if they exist 2025-08-26T21:41:01.0739562Z rm -f test-reports-*.zip 2025-08-26T21:41:01.0740072Z zip -r "test-reports-${FILE_SUFFIX}.zip" test/test-reports -i '*.xml' -i '*.csv' 2025-08-26T21:41:01.0745859Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:01.0746259Z env: 2025-08-26T21:41:01.0746499Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:01.0747006Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:01.0747530Z DEVICE_NAME: 2025-08-26T21:41:01.0747771Z DEVICE_TYPE: 2025-08-26T21:41:01.0748112Z FILE_SUFFIX: test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T21:41:01.0748608Z ##[endgroup] 2025-08-26T21:41:01.0839302Z adding: test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-5cc8bd85a1498caf.xml (deflated 28%) 2025-08-26T21:41:01.0842965Z adding: test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-cd63d02c944adb3e.xml (deflated 94%) 2025-08-26T21:41:01.0843953Z adding: test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-0bf7d4a3c7abf948.xml (deflated 28%) 2025-08-26T21:41:01.0846709Z adding: test/test-reports/python-pytest/lazy.test_ts_opinfo/lazy.test_ts_opinfo-9d0c1fb742b9f512.xml (deflated 94%) 2025-08-26T21:41:01.0861347Z adding: test/test-reports/python-pytest/inductor.test_flex_attention/inductor.test_flex_attention-1498ded6bba2a0b0.xml (deflated 98%) 2025-08-26T21:41:01.0875676Z adding: test/test-reports/python-pytest/test_overrides/test_overrides-448d5cf38ed6e754.xml (deflated 95%) 2025-08-26T21:41:01.0924502Z adding: test/test-reports/python-pytest/test_reductions/test_reductions-3e1b31535824d418.xml (deflated 96%) 2025-08-26T21:41:01.0933598Z adding: test/test-reports/python-pytest/test_tensor_creation_ops/test_tensor_creation_ops-a836e5876fab52a3.xml (deflated 94%) 2025-08-26T21:41:01.0934773Z adding: test/test-reports/python-pytest/test_cpp_extensions_mtia_backend/test_cpp_extensions_mtia_backend-7679d8e7462dfd72.xml (deflated 72%) 2025-08-26T21:41:01.0973955Z adding: test/test-reports/python-pytest/test_nn/test_nn-c1aa3763e440c919.xml (deflated 96%) 2025-08-26T21:41:01.0975016Z adding: test/test-reports/python-pytest/test_cpp_extensions_stream_and_event/test_cpp_extensions_stream_and_event-48f55e38de15d0b2.xml (deflated 54%) 2025-08-26T21:41:01.0976308Z adding: test/test-reports/python-pytest/inductor.test_benchmark_fusion/inductor.test_benchmark_fusion-71a74b237acadf2f.xml (deflated 72%) 2025-08-26T21:41:01.0977596Z adding: test/test-reports/python-pytest/inductor.test_distributed_patterns/inductor.test_distributed_patterns-808ad7565259b26e.xml (deflated 87%) 2025-08-26T21:41:01.0978844Z adding: test/test-reports/python-pytest/dynamo.test_fake_distributed/dynamo.test_fake_distributed-24f4d29142b7e3da.xml (deflated 49%) 2025-08-26T21:41:01.1042810Z adding: test/test-reports/python-pytest/test_utils/test_utils-1a9dcbdfc4eb6942.xml (deflated 96%) 2025-08-26T21:41:01.1068887Z adding: test/test-reports/python-pytest/test_fx/test_fx-0ae3af7485961000.xml 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pipefail {0} 2025-08-26T21:41:01.2344649Z env: 2025-08-26T21:41:01.2344883Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:01.2345371Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:01.2345887Z DEVICE_NAME: 2025-08-26T21:41:01.2346129Z DEVICE_TYPE: 2025-08-26T21:41:01.2346467Z FILE_SUFFIX: test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T21:41:01.2346869Z ##[endgroup] 2025-08-26T21:41:01.2576943Z adding: usage_log.txt (deflated 96%) 2025-08-26T21:41:01.2747562Z adding: test/test-reports/test_ops_3.7_c6b7e90087f70ccc_.log (deflated 92%) 2025-08-26T21:41:01.2748383Z adding: test/test-reports/lazy.test_ts_opinfo_1.1_532edf2792b89407_.log (deflated 50%) 2025-08-26T21:41:01.2749339Z adding: test/test-reports/test_logging_1.1_844368347f2917aa_.log (deflated 50%) 2025-08-26T21:41:01.2754639Z adding: test/test-reports/lazy.test_ts_opinfo_1.1_6b9006e432a812df_.log (deflated 92%) 2025-08-26T21:41:01.2755469Z adding: 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test/test-reports/cpp.legacy_vmap_test_1.1_961ae24fee757dec_.log (deflated 73%) 2025-08-26T21:41:01.4565396Z adding: test/test-reports/cpp.scalar_tensor_test_1.1_e5729d9bdfa72250_.log (deflated 73%) 2025-08-26T21:41:01.4566158Z adding: test/test-reports/cpp.tensor_iterator_test_1.1_a65f5b4b1261d48a_.log (deflated 73%) 2025-08-26T21:41:01.4566933Z adding: test/test-reports/cpp.undefined_tensor_test_1.1_90ffc74f9614b433_.log (deflated 73%) 2025-08-26T21:41:01.4567678Z adding: test/test-reports/cpp.NamedTensor_test_1.1_3857c684c09185b3_.log (deflated 77%) 2025-08-26T21:41:01.4568406Z adding: test/test-reports/cpp.apply_utils_test_1.1_9e12aca868fa6cb6_.log (deflated 75%) 2025-08-26T21:41:01.4569199Z adding: test/test-reports/cpp.cpu_generator_test_1.1_60f510efbe80dd3c_.log (deflated 80%) 2025-08-26T21:41:01.4569945Z adding: test/test-reports/cpp.dlconvertor_test_1.1_27afbaa82de41896_.log (deflated 75%) 2025-08-26T21:41:01.4570701Z adding: test/test-reports/cpp.extension_backend_test_1.1_1bde4b79f8557ed1_.log (deflated 72%) 2025-08-26T21:41:01.4571524Z adding: test/test-reports/cpp.lazy_tensor_test_1.1_5b711eb4c0dd6952_.log (deflated 72%) 2025-08-26T21:41:01.4572360Z adding: test/test-reports/cpp.legacy_vmap_test_1.1_8acef57c37055ab2_.log (deflated 82%) 2025-08-26T21:41:01.4573382Z adding: test/test-reports/cpp.scalar_tensor_test_1.1_9fde8ab056426bee_.log (deflated 74%) 2025-08-26T21:41:01.4574271Z adding: test/test-reports/cpp.undefined_tensor_test_1.1_10f85c7963b304e4_.log (deflated 72%) 2025-08-26T21:41:01.4575151Z adding: test/test-reports/cpp.tensor_iterator_test_1.1_0d555876eb2f0f01_.log (deflated 88%) 2025-08-26T21:41:01.4605179Z adding: test/test-reports/cpp.test_api_1.1_ee7ae37b81c1946f_.log (deflated 93%) 2025-08-26T21:41:01.4606017Z adding: test/test-reports/cpp.static_runtime_test_1.1_e6c196bd110ca514_.log (deflated 73%) 2025-08-26T21:41:01.4616771Z adding: test/test-reports/cpp.static_runtime_test_1.1_b732f289878bc6b9_.log (deflated 89%) 2025-08-26T21:41:01.4654660Z ##[group]Run # Remove any previous debugging artifacts if they exist 2025-08-26T21:41:01.4655244Z # Remove any previous debugging artifacts if they exist 2025-08-26T21:41:01.4655682Z rm -f debug-*.zip 2025-08-26T21:41:01.4655992Z if [ -d 'test/debug' ]; then 2025-08-26T21:41:01.4656363Z  zip -r "debug-${FILE_SUFFIX}.zip" test/debug 2025-08-26T21:41:01.4656730Z fi 2025-08-26T21:41:01.4662515Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:01.4662920Z env: 2025-08-26T21:41:01.4663144Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:01.4663641Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:01.4664173Z DEVICE_NAME: 2025-08-26T21:41:01.4664433Z DEVICE_TYPE: 2025-08-26T21:41:01.4664768Z FILE_SUFFIX: test-default-1-5-lf.linux.4xlarge_48944862553 2025-08-26T21:41:01.4665172Z ##[endgroup] 2025-08-26T21:41:01.4781776Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-08-26T21:41:01.4782247Z with: 2025-08-26T21:41:01.4782470Z s3-bucket: gha-artifacts 2025-08-26T21:41:01.4782811Z s3-prefix: pytorch/pytorch/17248463620/1/artifact 2025-08-26T21:41:01.4783179Z retention-days: 14 2025-08-26T21:41:01.4783450Z if-no-files-found: warn 2025-08-26T21:41:01.4783723Z path: test-jsons-*.zip 2025-08-26T21:41:01.4783998Z name: artifact 2025-08-26T21:41:01.4784241Z region: us-east-1 2025-08-26T21:41:01.4784480Z env: 2025-08-26T21:41:01.4784692Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:01.4785181Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:01.4785703Z DEVICE_NAME: 2025-08-26T21:41:01.4785944Z DEVICE_TYPE: 2025-08-26T21:41:01.4786167Z ##[endgroup] 2025-08-26T21:41:01.8412708Z NOTE: s3-prefix specified, ignoring name parameter 2025-08-26T21:41:01.8413570Z With the provided path, there will be 1 file uploaded 2025-08-26T21:41:01.8414060Z Uploading to s3 prefix: pytorch/pytorch/17248463620/1/artifact 2025-08-26T21:41:01.8455469Z Starting upload of test-jsons-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:01.9933131Z Finished upload of test-jsons-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:02.0127333Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-08-26T21:41:02.0127690Z with: 2025-08-26T21:41:02.0127908Z s3-bucket: gha-artifacts 2025-08-26T21:41:02.0128249Z s3-prefix: pytorch/pytorch/17248463620/1/artifact 2025-08-26T21:41:02.0128622Z retention-days: 14 2025-08-26T21:41:02.0129009Z if-no-files-found: error 2025-08-26T21:41:02.0129293Z path: test-reports-*.zip 2025-08-26T21:41:02.0129574Z name: artifact 2025-08-26T21:41:02.0129820Z region: us-east-1 2025-08-26T21:41:02.0130047Z env: 2025-08-26T21:41:02.0130277Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:02.0130786Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:02.0131313Z DEVICE_NAME: 2025-08-26T21:41:02.0131550Z DEVICE_TYPE: 2025-08-26T21:41:02.0131779Z ##[endgroup] 2025-08-26T21:41:02.3451358Z NOTE: s3-prefix specified, ignoring name parameter 2025-08-26T21:41:02.3452207Z With the provided path, there will be 1 file uploaded 2025-08-26T21:41:02.3452693Z Uploading to s3 prefix: pytorch/pytorch/17248463620/1/artifact 2025-08-26T21:41:02.3492735Z Starting upload of test-reports-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:02.5425681Z Finished upload of test-reports-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:02.5621392Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-08-26T21:41:02.5621749Z with: 2025-08-26T21:41:02.5621974Z s3-bucket: gha-artifacts 2025-08-26T21:41:02.5622316Z s3-prefix: pytorch/pytorch/17248463620/1/artifact 2025-08-26T21:41:02.5622692Z retention-days: 14 2025-08-26T21:41:02.5622978Z if-no-files-found: ignore 2025-08-26T21:41:02.5623263Z path: logs-*.zip 2025-08-26T21:41:02.5623513Z name: artifact 2025-08-26T21:41:02.5623757Z region: us-east-1 2025-08-26T21:41:02.5624022Z env: 2025-08-26T21:41:02.5624334Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:02.5624819Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:02.5625343Z DEVICE_NAME: 2025-08-26T21:41:02.5625586Z DEVICE_TYPE: 2025-08-26T21:41:02.5625811Z ##[endgroup] 2025-08-26T21:41:02.8950771Z NOTE: s3-prefix specified, ignoring name parameter 2025-08-26T21:41:02.8951314Z With the provided path, there will be 1 file uploaded 2025-08-26T21:41:02.8951786Z Uploading to s3 prefix: pytorch/pytorch/17248463620/1/artifact 2025-08-26T21:41:02.8991899Z Starting upload of logs-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:03.0909844Z Finished upload of logs-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:03.1110776Z ##[group]Run seemethere/upload-artifact-s3@v5 2025-08-26T21:41:03.1111165Z with: 2025-08-26T21:41:03.1111391Z s3-bucket: gha-artifacts 2025-08-26T21:41:03.1111730Z s3-prefix: pytorch/pytorch/17248463620/1/artifact 2025-08-26T21:41:03.1112196Z retention-days: 14 2025-08-26T21:41:03.1112467Z if-no-files-found: ignore 2025-08-26T21:41:03.1112743Z path: debug-*.zip 2025-08-26T21:41:03.1112997Z name: artifact 2025-08-26T21:41:03.1113245Z region: us-east-1 2025-08-26T21:41:03.1113471Z env: 2025-08-26T21:41:03.1113701Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:03.1114187Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:03.1114708Z DEVICE_NAME: 2025-08-26T21:41:03.1114946Z DEVICE_TYPE: 2025-08-26T21:41:03.1115167Z ##[endgroup] 2025-08-26T21:41:03.4429824Z No files were found with the provided path: debug-*.zip. No artifacts will be uploaded. 2025-08-26T21:41:03.4636302Z ##[group]Run # shellcheck disable=SC2156 2025-08-26T21:41:03.4636786Z # shellcheck disable=SC2156 2025-08-26T21:41:03.4637649Z find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \; 2025-08-26T21:41:03.4643710Z shell: /usr/bin/bash -e {0} 2025-08-26T21:41:03.4644008Z env: 2025-08-26T21:41:03.4644237Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:03.4644727Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:03.4645237Z DEVICE_NAME: 2025-08-26T21:41:03.4645479Z DEVICE_TYPE: 2025-08-26T21:41:03.4645720Z ##[endgroup] 2025-08-26T21:41:03.7565475Z Prepare all required actions 2025-08-26T21:41:03.7565910Z Getting action download info 2025-08-26T21:41:03.8786646Z ##[group]Run ./.github/actions/upload-utilization-stats 2025-08-26T21:41:03.8787024Z with: 2025-08-26T21:41:03.8787246Z job_id: 48944862553 2025-08-26T21:41:03.8787658Z job_name: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T21:41:03.8788144Z workflow_name: pull 2025-08-26T21:41:03.8788396Z workflow_run_id: 17248463620 2025-08-26T21:41:03.8788678Z workflow_attempt: 1 2025-08-26T21:41:03.8788923Z env: 2025-08-26T21:41:03.8789145Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:03.8789604Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:03.8790107Z DEVICE_NAME: 2025-08-26T21:41:03.8790340Z DEVICE_TYPE: 2025-08-26T21:41:03.8790574Z ##[endgroup] 2025-08-26T21:41:03.8815395Z ##[group]Run echo "workflow_id: 17248463620" 2025-08-26T21:41:03.8815926Z echo "workflow_id: 17248463620" 2025-08-26T21:41:03.8816268Z echo "workflow_attempt: 1" 2025-08-26T21:41:03.8816581Z echo "workflow_Name: pull" 2025-08-26T21:41:03.8816898Z echo "job_id: 48944862553" 2025-08-26T21:41:03.8817405Z echo "job_name: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge)" 2025-08-26T21:41:03.8817984Z echo "artifact_prefix: " 2025-08-26T21:41:03.8818298Z python3 --version 2025-08-26T21:41:03.8824476Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:03.8824989Z env: 2025-08-26T21:41:03.8825332Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:03.8825795Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:03.8826303Z DEVICE_NAME: 2025-08-26T21:41:03.8826538Z DEVICE_TYPE: 2025-08-26T21:41:03.8826767Z ##[endgroup] 2025-08-26T21:41:03.8850058Z workflow_id: 17248463620 2025-08-26T21:41:03.8850618Z workflow_attempt: 1 2025-08-26T21:41:03.8850933Z workflow_Name: pull 2025-08-26T21:41:03.8851183Z job_id: 48944862553 2025-08-26T21:41:03.8851593Z job_name: linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge) 2025-08-26T21:41:03.8852080Z artifact_prefix: 2025-08-26T21:41:03.8861976Z Python 3.9.23 2025-08-26T21:41:03.8906587Z ##[group]Run nick-fields/retry@v3.0.0 2025-08-26T21:41:03.8906901Z with: 2025-08-26T21:41:03.8907118Z shell: bash 2025-08-26T21:41:03.8907364Z timeout_minutes: 5 2025-08-26T21:41:03.8907618Z max_attempts: 5 2025-08-26T21:41:03.8907854Z retry_wait_seconds: 30 2025-08-26T21:41:03.8908429Z command: set -eu python3 -m pip install python-dateutil==2.8.2 boto3==1.35.42 pandas==2.1.3 dataclasses_json==0.6.7 2025-08-26T21:41:03.8909148Z polling_interval_seconds: 1 2025-08-26T21:41:03.8909447Z warning_on_retry: true 2025-08-26T21:41:03.8909715Z continue_on_error: false 2025-08-26T21:41:03.8909990Z env: 2025-08-26T21:41:03.8910218Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:03.8910707Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:03.8911214Z DEVICE_NAME: 2025-08-26T21:41:03.8911451Z DEVICE_TYPE: 2025-08-26T21:41:03.8911686Z ##[endgroup] 2025-08-26T21:41:04.2432934Z Defaulting to user installation because normal site-packages is not writeable 2025-08-26T21:41:04.3244245Z Collecting python-dateutil==2.8.2 2025-08-26T21:41:04.3414449Z Downloading python_dateutil-2.8.2-py2.py3-none-any.whl (247 kB) 2025-08-26T21:41:05.3582517Z Collecting boto3==1.35.42 2025-08-26T21:41:05.3629803Z Downloading boto3-1.35.42-py3-none-any.whl (139 kB) 2025-08-26T21:41:05.9009932Z Collecting pandas==2.1.3 2025-08-26T21:41:05.9049425Z Downloading pandas-2.1.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (12.3 MB) 2025-08-26T21:41:06.0365402Z Requirement already satisfied: dataclasses_json==0.6.7 in /home/ec2-user/.local/lib/python3.9/site-packages (0.6.7) 2025-08-26T21:41:06.0383903Z Requirement already satisfied: six>=1.5 in /usr/lib/python3.9/site-packages (from python-dateutil==2.8.2) (1.15.0) 2025-08-26T21:41:06.0430451Z Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /usr/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.0) 2025-08-26T21:41:06.0436122Z Requirement already satisfied: botocore<1.36.0,>=1.35.42 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (1.35.99) 2025-08-26T21:41:06.0440616Z Requirement already satisfied: s3transfer<0.11.0,>=0.10.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from boto3==1.35.42) (0.10.4) 2025-08-26T21:41:06.9600541Z Collecting numpy<2,>=1.22.4 2025-08-26T21:41:06.9642774Z Downloading numpy-1.26.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (18.2 MB) 2025-08-26T21:41:07.1868597Z Collecting tzdata>=2022.1 2025-08-26T21:41:07.1912495Z Downloading tzdata-2025.2-py2.py3-none-any.whl (347 kB) 2025-08-26T21:41:07.2033440Z Requirement already satisfied: pytz>=2020.1 in /usr/lib/python3.9/site-packages (from pandas==2.1.3) (2022.7.1) 2025-08-26T21:41:07.2066447Z Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (3.26.1) 2025-08-26T21:41:07.2070682Z Requirement already satisfied: typing-inspect<1,>=0.4.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from dataclasses_json==0.6.7) (0.9.0) 2025-08-26T21:41:07.2131676Z Requirement already satisfied: urllib3<1.27,>=1.25.4 in /usr/lib/python3.9/site-packages (from botocore<1.36.0,>=1.35.42->boto3==1.35.42) (1.25.10) 2025-08-26T21:41:07.2243383Z Requirement already satisfied: packaging>=17.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses_json==0.6.7) (25.0) 2025-08-26T21:41:07.2347412Z Requirement already satisfied: mypy-extensions>=0.3.0 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (1.1.0) 2025-08-26T21:41:07.2351946Z Requirement already satisfied: typing-extensions>=3.7.4 in /home/ec2-user/.local/lib/python3.9/site-packages (from typing-inspect<1,>=0.4.0->dataclasses_json==0.6.7) (4.15.0) 2025-08-26T21:41:07.4024635Z Installing collected packages: python-dateutil, tzdata, numpy, pandas, boto3 2025-08-26T21:41:12.4505734Z Attempting uninstall: boto3 2025-08-26T21:41:12.4506235Z Found existing installation: boto3 1.35.33 2025-08-26T21:41:12.4609625Z Uninstalling boto3-1.35.33: 2025-08-26T21:41:12.4622580Z Successfully uninstalled boto3-1.35.33 2025-08-26T21:41:12.5196821Z Successfully installed boto3-1.35.42 numpy-1.26.4 pandas-2.1.3 python-dateutil-2.8.2 tzdata-2025.2 2025-08-26T21:41:12.9731989Z Command completed after 1 attempt(s). 2025-08-26T21:41:12.9789295Z ##[group]Run python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-08-26T21:41:12.9790019Z python3 -m tools.stats.upload_utilization_stats.upload_utilization_stats \ 2025-08-26T21:41:12.9790551Z  --workflow-run-id "17248463620" \ 2025-08-26T21:41:12.9790922Z  --workflow-name "pull" \ 2025-08-26T21:41:12.9791261Z  --workflow-run-attempt "1" \ 2025-08-26T21:41:12.9791593Z  --job-id "48944862553" \ 2025-08-26T21:41:12.9792077Z  --job-name "linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge)" \ 2025-08-26T21:41:12.9792599Z  --local-path "" \ 2025-08-26T21:41:12.9792896Z  --artifact-prefix "" 2025-08-26T21:41:12.9798609Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:12.9798984Z env: 2025-08-26T21:41:12.9799211Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:12.9799685Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:12.9800201Z DEVICE_NAME: 2025-08-26T21:41:12.9800423Z DEVICE_TYPE: 2025-08-26T21:41:12.9800658Z ##[endgroup] 2025-08-26T21:41:15.0373694Z repo: pytorch/pytorch 2025-08-26T21:41:15.0374084Z Search for test log in s3 bucket: ossci-utilization 2025-08-26T21:41:15.0374894Z Downloading logs-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:15.0375559Z extracting usage_log.txt from zip file logs-test-default-1-5-lf.linux.4xlarge_48944862553.zip 2025-08-26T21:41:15.0376132Z Converted Log Model: UtilizationMetadata: 2025-08-26T21:41:15.0377503Z UtilizationMetadata(level='metadata', workflow_id='17248463620', job_id='48944862553', workflow_name='pull', job_name='linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge)', usage_collect_interval=1.0, data_model_version=1.5, start_at=1756237625, gpu_count=0, cpu_count=16, gpu_type=None, error=None) 2025-08-26T21:41:15.0378959Z [Db Segments] detected pytest cmd: 18, generated segments: 18 2025-08-26T21:41:15.0379381Z [db model] Peek db timeseries 2025-08-26T21:41:15.0379650Z :{ 2025-08-26T21:41:15.0379866Z "created_at": 1756244474, 2025-08-26T21:41:15.0380157Z "type": "utilization", 2025-08-26T21:41:15.0380411Z "tags": [ 2025-08-26T21:41:15.0380634Z "record" 2025-08-26T21:41:15.0380855Z ], 2025-08-26T21:41:15.0381075Z "time_stamp": 1756237625, 2025-08-26T21:41:15.0381350Z "repo": "pytorch/pytorch", 2025-08-26T21:41:15.0381637Z "workflow_id": 17248463620, 2025-08-26T21:41:15.0381914Z "run_attempt": 1, 2025-08-26T21:41:15.0382164Z "job_id": 48944862553, 2025-08-26T21:41:15.0382422Z "workflow_name": "pull", 2025-08-26T21:41:15.0382861Z "job_name": "linux-jammy-py3.13-clang12 / test (default, 1, 5, lf.linux.4xlarge)", 2025-08-26T21:41:15.0383336Z "json_data": "{}" 2025-08-26T21:41:15.0383577Z } 2025-08-26T21:41:15.0384087Z Writing 1 documents to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17248463620/1/48944862553/metadata 2025-08-26T21:41:15.0385038Z Done! Finish writing document to S3 ossci-utilization/util_metadata/v_1.5/pytorch/pytorch/17248463620/1/48944862553/metadata 2025-08-26T21:41:15.0386025Z Writing 1364 documents to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17248463620/1/48944862553/time_series 2025-08-26T21:41:15.0387034Z Done! Finish writing document to S3 ossci-utilization/util_timeseries/v_1.5/pytorch/pytorch/17248463620/1/48944862553/time_series 2025-08-26T21:41:15.1404621Z ##[group]Run pytorch/test-infra/.github/actions/teardown-linux@main 2025-08-26T21:41:15.1405071Z with: 2025-08-26T21:41:15.1405281Z env: 2025-08-26T21:41:15.1405491Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:15.1405966Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:15.1406482Z DEVICE_NAME: 2025-08-26T21:41:15.1406714Z DEVICE_TYPE: 2025-08-26T21:41:15.1406934Z ##[endgroup] 2025-08-26T21:41:15.1433211Z ##[group]Run set -eou pipefail 2025-08-26T21:41:15.1433640Z set -eou pipefail 2025-08-26T21:41:15.1433920Z  2025-08-26T21:41:15.1434309Z echo "Holding runner for 2 hours until all ssh sessions have logged out" 2025-08-26T21:41:15.1434777Z for _ in $(seq 1440); do 2025-08-26T21:41:15.1435124Z  # Break if no ssh session exists anymore 2025-08-26T21:41:15.1435488Z  if [ "$(who)" = "" ]; then 2025-08-26T21:41:15.1435796Z  break 2025-08-26T21:41:15.1436115Z  fi 2025-08-26T21:41:15.1436358Z  echo "." 2025-08-26T21:41:15.1436600Z  sleep 5 2025-08-26T21:41:15.1436851Z done 2025-08-26T21:41:15.1443320Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:15.1443717Z env: 2025-08-26T21:41:15.1444004Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:15.1444483Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:15.1444997Z DEVICE_NAME: 2025-08-26T21:41:15.1445243Z DEVICE_TYPE: 2025-08-26T21:41:15.1445461Z ##[endgroup] 2025-08-26T21:41:15.1468358Z Holding runner for 2 hours until all ssh sessions have logged out 2025-08-26T21:41:15.1548958Z ##[group]Run # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T21:41:15.1549641Z # ignore expansion of "docker ps -q" since it could be empty 2025-08-26T21:41:15.1550085Z # shellcheck disable=SC2046 2025-08-26T21:41:15.1550450Z docker stop $(docker ps -q) || true 2025-08-26T21:41:15.1550798Z # Prune all of the docker images 2025-08-26T21:41:15.1551139Z docker system prune -af 2025-08-26T21:41:15.1556332Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:15.1556721Z env: 2025-08-26T21:41:15.1556934Z GIT_DEFAULT_BRANCH: main 2025-08-26T21:41:15.1557415Z DOCKER_CONTAINER_ID: e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:15.1557932Z DEVICE_NAME: 2025-08-26T21:41:15.1558171Z DEVICE_TYPE: 2025-08-26T21:41:15.1558413Z ##[endgroup] 2025-08-26T21:41:26.4552628Z e12c338ce7d9 2025-08-26T21:41:26.9724052Z Deleted Containers: 2025-08-26T21:41:26.9724501Z e12c338ce7d9538a47bb64513ca956655ea7e72a18a217079f711149d8a678e5 2025-08-26T21:41:26.9724841Z 2025-08-26T21:41:29.9630122Z Deleted Images: 2025-08-26T21:41:29.9631428Z untagged: 308535385114.dkr.ecr.us-east-1.amazonaws.com/pytorch/ci-image:pytorch-linux-jammy-py3.13-clang12-16b1c8d10f4f7ec1a604612d52021e8c98b48fe6 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2025-08-26T21:41:30.7948383Z Entering 'third_party/ideep/mkl-dnn' 2025-08-26T21:41:30.7980973Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8017686Z Entering 'third_party/ittapi' 2025-08-26T21:41:30.8051433Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8081559Z Entering 'third_party/kineto' 2025-08-26T21:41:30.8116483Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8147501Z Entering 'third_party/kineto/libkineto/third_party/dynolog' 2025-08-26T21:41:30.8180814Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8211871Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/DCGM' 2025-08-26T21:41:30.8245667Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8278221Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/cpr' 2025-08-26T21:41:30.8311707Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8343608Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/fmt' 2025-08-26T21:41:30.8376903Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8407520Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags' 2025-08-26T21:41:30.8442455Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8472497Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/gflags/doc' 2025-08-26T21:41:30.8506524Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8539959Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/glog' 2025-08-26T21:41:30.8573259Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8604937Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/googletest' 2025-08-26T21:41:30.8638866Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8670250Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/json' 2025-08-26T21:41:30.8704167Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8739406Z Entering 'third_party/kineto/libkineto/third_party/dynolog/third_party/pfs' 2025-08-26T21:41:30.8773238Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8805522Z Entering 'third_party/kineto/libkineto/third_party/fmt' 2025-08-26T21:41:30.8841577Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8871613Z Entering 'third_party/kineto/libkineto/third_party/googletest' 2025-08-26T21:41:30.8905958Z http.https://github.com/.extraheader 2025-08-26T21:41:30.8938918Z Entering 'third_party/kleidiai' 2025-08-26T21:41:30.8974277Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9005245Z Entering 'third_party/mimalloc' 2025-08-26T21:41:30.9040647Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9071594Z Entering 'third_party/nlohmann' 2025-08-26T21:41:30.9105421Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9137642Z Entering 'third_party/onnx' 2025-08-26T21:41:30.9171260Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9218155Z Entering 'third_party/onnx/third_party/pybind11' 2025-08-26T21:41:30.9253219Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9285338Z Entering 'third_party/opentelemetry-cpp' 2025-08-26T21:41:30.9319745Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9353068Z Entering 'third_party/opentelemetry-cpp/third_party/benchmark' 2025-08-26T21:41:30.9386337Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9416809Z Entering 'third_party/opentelemetry-cpp/third_party/googletest' 2025-08-26T21:41:30.9450249Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9480162Z Entering 'third_party/opentelemetry-cpp/third_party/ms-gsl' 2025-08-26T21:41:30.9513480Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9544904Z Entering 'third_party/opentelemetry-cpp/third_party/nlohmann-json' 2025-08-26T21:41:30.9578200Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9609411Z Entering 'third_party/opentelemetry-cpp/third_party/opentelemetry-proto' 2025-08-26T21:41:30.9643010Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9672238Z Entering 'third_party/opentelemetry-cpp/third_party/opentracing-cpp' 2025-08-26T21:41:30.9705591Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9736125Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp' 2025-08-26T21:41:30.9769091Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9797894Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/civetweb' 2025-08-26T21:41:30.9831595Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9864408Z Entering 'third_party/opentelemetry-cpp/third_party/prometheus-cpp/3rdparty/googletest' 2025-08-26T21:41:30.9898319Z http.https://github.com/.extraheader 2025-08-26T21:41:30.9930457Z Entering 'third_party/opentelemetry-cpp/tools/vcpkg' 2025-08-26T21:41:30.9963792Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0014967Z Entering 'third_party/pocketfft' 2025-08-26T21:41:31.0049842Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0080524Z Entering 'third_party/protobuf' 2025-08-26T21:41:31.0115012Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0150005Z Entering 'third_party/protobuf/third_party/benchmark' 2025-08-26T21:41:31.0183282Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0213374Z Entering 'third_party/protobuf/third_party/googletest' 2025-08-26T21:41:31.0247278Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0279892Z Entering 'third_party/psimd' 2025-08-26T21:41:31.0315622Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0347608Z Entering 'third_party/pthreadpool' 2025-08-26T21:41:31.0382801Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0414039Z Entering 'third_party/pybind11' 2025-08-26T21:41:31.0449220Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0480000Z Entering 'third_party/python-peachpy' 2025-08-26T21:41:31.0514919Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0547671Z Entering 'third_party/sleef' 2025-08-26T21:41:31.0582989Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0614107Z Entering 'third_party/tensorpipe' 2025-08-26T21:41:31.0651168Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0682547Z Entering 'third_party/tensorpipe/third_party/googletest' 2025-08-26T21:41:31.0716622Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0748251Z Entering 'third_party/tensorpipe/third_party/libnop' 2025-08-26T21:41:31.0782002Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0812673Z Entering 'third_party/tensorpipe/third_party/libuv' 2025-08-26T21:41:31.0848038Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0878297Z Entering 'third_party/tensorpipe/third_party/pybind11' 2025-08-26T21:41:31.0912639Z http.https://github.com/.extraheader 2025-08-26T21:41:31.0944338Z Entering 'third_party/tensorpipe/third_party/pybind11/tools/clang' 2025-08-26T21:41:31.0978507Z http.https://github.com/.extraheader 2025-08-26T21:41:31.1093831Z A job completed hook has been configured by the self-hosted runner administrator 2025-08-26T21:41:31.1119402Z ##[group]Run '/home/ec2-user/runner-scripts/after_job.sh' 2025-08-26T21:41:31.1124467Z shell: /usr/bin/bash --noprofile --norc -e -o pipefail {0} 2025-08-26T21:41:31.1124871Z ##[endgroup] 2025-08-26T21:41:31.1219852Z [!ALERT!] Swap in detected! [!ALERT!] 2025-08-26T21:41:41.9217600Z [!ALERT!] Swap out detected [!ALERT!] 2025-08-26T21:42:00.4799585Z Cleaning up orphan processes